Method, device and equipment for determining feature code matching parameters and computer program
By obtaining the initial waveform signal of feature encoding and generating multiple target waveform signals for correlation calculation, determining the matching parameters of feature encoding, the problem of low matching accuracy of feature encoding in the prior art is solved, and the matching accuracy is improved.
Patent Information
- Application Number
- CN202411758876.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-29
- Publication Date
- 2025-03-25
AI Technical Summary
When there is a large noise, the existing feature encoding matching method has low matching accuracy, resulting in large errors.
By obtaining the initial waveform signal of the feature code, the cumulative distribution information of its waveform amplitude is determined, the logical matching threshold is determined based on the cumulative distribution information, multiple target waveform signals are generated, and the correlation degree calculation is performed for each target waveform signal to the preset standard feature code, and the matching parameters of the feature code are finally determined.
The matching accuracy of feature encoding is improved, and the optimal matching parameters are determined by generating multiple target waveform signals and calculating the correlation degree, thereby reducing errors.
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Figure CN119696705A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the field of signal processing technology, and in particular, relates to a method, device, equipment and computer program for determining feature coding matching parameters. Background Art
[0002] The current feature code matching method usually first determines the amplitude average value of the waveform signal of the feature code, then determines the feature code exceeding the amplitude average value as logic 1, and determines the feature code below the amplitude average value as logic 0.
[0003] However, when there is a large amount of noise in the waveform signal of the feature coding, the above feature coding matching method will produce a large error, which shows that there is a problem of low matching accuracy. Summary of the invention
[0004] In view of this, the embodiments of the present application provide a method, apparatus, device and computer program for determining feature coding matching parameters to solve the technical problem of low matching accuracy of existing feature coding.
[0005] In a first aspect, an embodiment of the present application provides a method for determining a feature coding matching parameter, including:
[0006] Acquire an initial waveform signal of feature coding;
[0007] Determining cumulative distribution information of the waveform amplitude of the initial waveform signal;
[0008] Determining a logic matching threshold according to the cumulative distribution information;
[0009] Generate a plurality of target waveform signals according to the logic matching threshold and the initial waveform signal;
[0010] For each of the target waveform signals, a correlation calculation is performed between the target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal;
[0011] According to the correlation calculation result corresponding to each of the target waveform signals, the matching parameters of the feature code are determined.
[0012] Optionally, the determining of the cumulative distribution information of the waveform amplitude of the initial waveform signal includes:
[0013] Determining the maximum amplitude and the minimum amplitude of the initial waveform signal;
[0014] Determining a plurality of amplitude intervals according to the maximum amplitude value and the minimum amplitude value;
[0015] Determining the probability density of each of the amplitude intervals according to the initial waveform signal;
[0016] The cumulative distribution information is determined according to the probability density of each of the amplitude intervals.
[0017] Optionally, determining a logic matching threshold according to the cumulative distribution information includes:
[0018] Determining a first cumulative probability threshold and a second cumulative probability threshold according to the standard feature code and a preset error tolerance range;
[0019] Determining an upper threshold value of the logic matching threshold according to the cumulative distribution information and the first cumulative probability threshold;
[0020] Determining a lower threshold value of the logic matching threshold according to the cumulative distribution information and the second cumulative probability threshold;
[0021] The logic matching threshold is determined according to the upper threshold value and the lower threshold value.
[0022] Optionally, after determining the logic matching threshold according to the cumulative distribution information, the method further includes:
[0023] If the difference between the upper threshold value and the lower threshold value is smaller than a preset threshold value, it is determined that the initial waveform signal is a noise signal.
[0024] Optionally, generating a plurality of target waveform signals according to the logic matching threshold and the initial waveform signal includes:
[0025] Determine the difference between the upper threshold value and the lower threshold value, and the number of the target waveform signals;
[0026] The lower threshold value, the difference value and the quantity are used to determine the amplitude threshold value corresponding to each of the target waveform signals;
[0027] Each of the target waveform signals is generated according to each of the amplitude thresholds and the initial waveform signal.
[0028] Optionally, the performing correlation calculation on the target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal includes:
[0029] Perform sliding window processing on the target waveform signal with a preset step length through the standard feature code to obtain several groups of sub-waveform data;
[0030] For each group of the sub-waveform data, a correlation calculation is performed between the sub-waveform data and the standard feature code to obtain a correlation corresponding to the sub-waveform data;
[0031] The correlation calculation result corresponding to the target waveform signal is determined according to the correlation corresponding to each of the sub-waveform data.
[0032] Optionally, determining the matching parameter of the feature code according to the correlation calculation result corresponding to each of the target waveform signals includes:
[0033] Determine the target sub-waveform data with the highest correlation among the sub-waveform data in each of the target waveform signals;
[0034] Determine adjacent sub-waveform data of the target sub-waveform data;
[0035] If the correlation corresponding to the target sub-waveform data and the correlation corresponding to any adjacent sub-waveform data are greater than a preset correlation threshold, the sliding window subscript corresponding to the target sub-waveform data and the correlation corresponding to the target sub-waveform data are determined as matching parameters of the feature code.
[0036] In a second aspect, an embodiment of the present application provides a device for determining a feature coding matching parameter, including:
[0037] A waveform signal acquisition unit, used to acquire an initial waveform signal of a feature code;
[0038] A first determining unit, configured to determine cumulative distribution information of the waveform amplitude of the initial waveform signal;
[0039] A second determining unit, configured to determine a logic matching threshold according to the cumulative distribution information;
[0040] A signal generating unit, configured to generate a plurality of target waveform signals according to the logic matching threshold and the initial waveform signal;
[0041] A correlation calculation unit, used for performing correlation calculation on each target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal;
[0042] The third determination unit is used to determine the matching parameters of the feature code according to the correlation calculation result corresponding to each of the target waveform signals.
[0043] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, each step of the method for determining feature coding matching parameters as described in the first aspect is implemented.
[0044] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for determining feature coding matching parameters as described in the first aspect above.
[0045] In a fifth aspect, an embodiment of the present application provides a computer program. When the computer program is run on an electronic device, the electronic device executes each step of the method for determining feature coding matching parameters as described in the first aspect above.
[0046] The method, device, apparatus and computer program for determining feature coding matching parameters provided by the embodiments of the present application have the following beneficial effects:
[0047] In the method for determining the feature coding matching parameters provided in the embodiment of the present application, the initial waveform signal of the feature coding is first obtained, and then the cumulative distribution information of the waveform amplitude of the initial waveform signal is determined, and then the logical matching threshold is determined based on the cumulative distribution information, and then a plurality of target waveform signals are generated based on the logical matching threshold and the initial waveform signal, and then for each target waveform signal, the correlation between the target waveform signal and the preset standard feature code is calculated to obtain the corresponding correlation calculation result, and finally the matching parameters are determined based on each correlation calculation result. Through the method for determining the feature coding matching parameters of the present application, a plurality of target waveform signals can be generated based on the initial waveform signal, and then the correlation calculation results corresponding to each target waveform signal can be determined respectively, so that the matching parameters of the feature coding corresponding to the target waveform signal with the highest correlation can be determined as the optimal matching parameters of the feature coding, so that the optimal matching parameters of the feature coding can be used for feature coding matching, thereby improving the matching accuracy of the feature coding. BRIEF DESCRIPTION OF THE DRAWINGS
[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.
[0049] Figure 1 A flowchart of a method for determining feature coding matching parameters provided in an embodiment of the present application;
[0050] Figure 2 A schematic diagram of an initial waveform signal of a feature code provided in an embodiment of the present application;
[0051] Figure 3 A schematic diagram of the probability density of each amplitude interval provided in an embodiment of the present application;
[0052] Figure 4 A schematic diagram of cumulative distribution information of the waveform amplitude of an initial waveform signal provided in an embodiment of the present application;
[0053] Figure 5 A schematic diagram of each target waveform signal provided in an embodiment of the present application;
[0054] Figure 6 A schematic diagram of correlation calculation results corresponding to various target waveform signals provided in an embodiment of the present application;
[0055] Figure 7 A schematic diagram of the structure of a device for determining feature coding matching parameters provided in an embodiment of the present application;
[0056] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0057] It should be noted that the terms used in the embodiments of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application. In the description of the embodiments of the present application, unless otherwise specified, "multiple" refers to two or more than two, and "at least one", "one or more" refers to one, two or more. The terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, it is defined that the "first" and "second" features can explicitly or implicitly include one or more of the features.
[0058] References to "one embodiment" or "some embodiments" etc. described in this specification mean that a particular feature, structure or characteristic described in conjunction with the embodiment is included in one or more embodiments of the present application. Thus, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear at different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.
[0059] The executor of the method for determining the characteristic coding matching parameters provided in the embodiment of the present application may be an electronic device. As an example but not limitation, the executor of the method for determining the characteristic coding matching parameters provided in the embodiment of the present application may be an electric meter in an electric power system. Specifically, the executor of the method for determining the characteristic coding matching parameters provided in the embodiment of the present application may be a single-chip microcomputer in an electric meter in an electric power system.
[0060] The method for determining the feature coding matching parameters provided in the embodiment of the present application can be applied to various scenarios where feature coding needs to be matched. For example, when feature coding needs to be matched, the user can use an electronic device to perform the various steps of the method for determining the feature coding matching parameters provided in the embodiment of the present application, thereby improving the matching accuracy of the feature coding.
[0061] See also Figure 1 , Figure 1 The present invention provides a flowchart of a method for determining a feature coding matching parameter according to an embodiment of the present invention. The method for determining a feature coding matching parameter according to an embodiment of the present invention may include steps S101 to S106, which are described in detail as follows:
[0062] In S101, an initial waveform signal of feature coding is obtained.
[0063] In the embodiment of the present application, when it is necessary to match the characteristic code, the electronic device may first obtain an initial waveform signal of the characteristic code.
[0064] For example, see Figure 2 , Figure 2 A schematic diagram of an initial waveform signal of a feature code provided in an embodiment of the present application.
[0065] Figure 2 The characteristic-coded initial waveform signal shown is a typical characteristic-coded waveform signal, which has the following characteristics:
[0066] 1. The background noise is relatively large, with an amplitude close to 100, which is close to the power amplitude of the weaker carrier wave.
[0067] 2. The carrier power is unbalanced, and the power of the latter part is weak.
[0068] 3. Some coded signals are superimposed with harmonics, resulting in excessively high amplitudes in individual feature code intervals.
[0069] In practical applications, the accuracy of matching waveform signals with feature codes having the above characteristics using existing feature code matching methods is low.
[0070] In S102, cumulative distribution information of the waveform amplitude of the initial waveform signal is determined.
[0071] In an embodiment of the present application, after acquiring the characteristic-coded initial waveform signal, the electronic device may determine the cumulative distribution information of the waveform amplitude of the initial waveform signal.
[0072] In a possible implementation manner, the electronic device may first determine the maximum amplitude value and the minimum amplitude value of the initial waveform signal.
[0073] After determining the maximum amplitude and the minimum amplitude of the initial waveform signal, the electronic device can determine several amplitude intervals based on the maximum amplitude and the minimum amplitude. Specifically, the electronic device can divide the interval between the maximum amplitude and the minimum amplitude into several equal parts, thereby obtaining several amplitude intervals.
[0074] After obtaining several amplitude intervals, the electronic device can determine the probability density of each amplitude interval according to the initial waveform signal. Specifically, for each waveform amplitude of the initial waveform signal, if the waveform amplitude is within a certain amplitude interval, the electronic device can add one to the number of waveform amplitudes in the amplitude interval, thereby obtaining the number of waveform amplitudes in each amplitude interval, and finally determine the probability density of each amplitude interval according to the number of waveform amplitudes in each amplitude interval.
[0075] For example, see Figure 3 , Figure 3 A schematic diagram of the probability density of each amplitude interval provided in an embodiment of the present application.
[0076] After obtaining the probability density of each amplitude interval, the electronic device can determine the cumulative distribution information of the waveform amplitude of the initial waveform signal according to the probability density of each amplitude interval. Exemplarily, if the amplitude intervals are (0, 100), (100, 200), (200, 300), (300, 400) and (400, 500), where the probability density of the amplitude interval (0, 100) is 20%, the probability density of the amplitude interval (100, 200) is 20%, the probability density of the amplitude interval (200, 300) is 20%, the probability density of the amplitude interval (300, 400) is 20%, and the probability density of the amplitude interval (400, 500) is 20%, then the cumulative distribution information of the waveform amplitude can be as follows: the amplitude corresponding to an amplitude of 100 accounts for 80%, the amplitude corresponding to an amplitude of 200 accounts for 60%, the amplitude corresponding to an amplitude of 300 accounts for 40%, the amplitude corresponding to an amplitude of 400 accounts for 20%, and the amplitude corresponding to an amplitude of 500 accounts for 0%. It should be noted that the above examples are different from Figure 3 The corresponding schematic diagrams of the probability density of each amplitude interval are two independent examples.
[0077] For example, see Figure 4 , Figure 4 This is a schematic diagram of the cumulative distribution information of the waveform amplitude of an initial waveform signal provided in an embodiment of the present application. It should be noted that: Figure 4 The schematic diagram of the cumulative distribution information of the waveform amplitude of the initial waveform signal in is based on Figure 3 The schematic diagram of the probability density of each amplitude interval in is obtained.
[0078] In S103, a logic matching threshold is determined according to the cumulative distribution information.
[0079] In the embodiment of the present application, after determining the cumulative distribution information of the waveform amplitude of the initial waveform signal, the electronic device may determine the logic matching threshold according to the cumulative distribution information of the waveform amplitude of the initial waveform signal.
[0080] In a possible implementation, the electronic device may first determine the first cumulative probability threshold and the second cumulative probability threshold according to the standard feature code and the preset error tolerance range. Specifically, the electronic device may first determine the first proportion of logic 1 and the second proportion of logic 0 in the standard feature code, and then determine the first cumulative probability threshold according to the first proportion and the preset error tolerance range, and determine the second cumulative probability threshold according to the second proportion and the preset error tolerance range. Exemplarily, the standard feature code may be 10101010, then the first proportion of logic 1 in the standard feature code is 50%, the second proportion of logic 0 in the standard feature code is 50%, and the preset error tolerance range may be 20%. Based on this, the difference of 30% between the first proportion of 50% and the error tolerance range of 20% may be determined as the first cumulative probability threshold, and the sum of the second proportion of 50% and the error tolerance range of 20% may be determined as the second cumulative probability threshold.
[0081] After determining the first cumulative probability threshold and the second cumulative probability threshold, the electronic device can determine the upper threshold value of the logical match threshold based on the cumulative distribution information of the waveform amplitude and the first cumulative probability threshold, and can determine the lower threshold value of the logical match threshold based on the cumulative distribution information of the waveform amplitude and the second cumulative probability threshold.
[0082] by Figure 4 Taking the cumulative distribution information of the waveform amplitude of the corresponding initial waveform signal as an example, when the first cumulative probability threshold is 30%, it can be Figure 4 The value of the horizontal axis corresponding to the ordinate being 30% in the cumulative distribution information of the waveform amplitude of the corresponding initial waveform signal is determined as the upper threshold value of the logic matching threshold.
[0083] by Figure 4 Taking the cumulative distribution information of the waveform amplitude of the corresponding initial waveform signal as an example, when the second cumulative probability threshold is 70%, it can be Figure 4 The value of the horizontal axis corresponding to 70% of the vertical axis in the cumulative distribution information of the waveform amplitude of the corresponding initial waveform signal is determined as the lower threshold value of the logic matching threshold.
[0084] After determining the upper threshold value of the logic match threshold and the lower threshold value of the logic match threshold, the electronic device may determine the logic match threshold according to the upper threshold value of the logic match threshold and the lower threshold value of the logic match threshold.
[0085] In a possible implementation, after determining the upper threshold value of the logic match threshold and the lower threshold value of the logic match threshold, the electronic device may also determine whether the difference between the upper threshold value of the logic match threshold and the lower threshold value of the logic match threshold is less than a preset threshold value, and if the difference between the upper threshold value of the logic match threshold and the lower threshold value of the logic match threshold is less than the preset threshold value, the electronic device may determine that the initial waveform signal is a noise signal. After determining that the initial waveform signal is a noise signal, the electronic device may choose not to perform subsequent steps.
[0086] In S104, a plurality of target waveform signals are generated according to the logic matching threshold and the initial waveform signal.
[0087] In the embodiment of the present application, after the logic matching threshold is determined, the electronic device may generate a plurality of target waveform signals according to the logic matching threshold and the initial waveform signal.
[0088] Specifically, the electronic device may first determine the difference between the upper threshold value and the lower threshold value, and the number of target waveform signals.
[0089] Afterwards, the electronic device can determine the amplitude threshold corresponding to each target waveform signal according to the lower threshold value, the difference value and the number. Exemplarily, the lower threshold value can be 100, the upper threshold value can be 233, the difference between the upper threshold value and the lower threshold value is 133, and the number of target waveform signals can be 3. Based on this, the amplitude thresholds corresponding to each target waveform signal are: 100+(133 / 3), 100+2(133 / 3) and 100+3(133 / 3).
[0090] After determining the amplitude thresholds corresponding to the respective target waveform signals, the electronic device can generate the respective target waveform signals according to the respective amplitude thresholds and the initial waveform signal. Figure 5 , Figure 5 A schematic diagram of various target waveform signals provided in an embodiment of the present application. Figure 5 The schematic diagram of each target waveform signal shown is obtained by Figure 2 The initial waveform signal shown and the amplitude thresholds of the above examples are 100+(133 / 3), 100+2(133 / 3) and 100+3(133 / 3).
[0091] exist Figure 5In the figure, WAVE_TM[0] represents the target waveform signal corresponding to the amplitude threshold 100+(133 / 3), WAVE_TM[1] represents the target waveform signal corresponding to the amplitude threshold 100+2(133 / 3), and WAVE_TM[2] represents the target waveform signal corresponding to the amplitude threshold 100+3(133 / 3).
[0092] Among them, each amplitude threshold corresponds to a target waveform signal, that is, the corresponding target waveform signal can be generated by an amplitude threshold. The method for generating an arbitrary target waveform signal is: for the amplitude threshold corresponding to the target waveform signal, traverse each amplitude of the initial waveform signal, if any amplitude value of the initial waveform signal is greater than or equal to the amplitude threshold corresponding to the target waveform signal, then the amplitude corresponding to the target waveform signal is determined as the amplitude threshold corresponding to the target waveform signal, if any amplitude value of the initial waveform signal is less than the amplitude threshold corresponding to the target waveform signal, then the amplitude corresponding to the target waveform signal is determined to be 0.
[0093] For example, when generating a target waveform signal corresponding to a threshold amplitude of 100+(133 / 3), for each amplitude of the initial waveform signal, if the amplitude is greater than or equal to the threshold amplitude of 100+(133 / 3), the amplitude corresponding to the target waveform signal is determined to be the threshold amplitude of 100+(133 / 3); if the amplitude is less than the threshold amplitude of 100+(133 / 3), the amplitude corresponding to the target waveform signal is determined to be 0.
[0094] In S105 , for each target waveform signal, a correlation calculation is performed between the target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal.
[0095] In an embodiment of the present application, after generating multiple target waveform signals, the electronic device can perform a correlation calculation between each target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal.
[0096] Specifically, the electronic device can obtain the correlation calculation result corresponding to the target waveform signal in the following manner:
[0097] The electronic device may first perform sliding window processing on the target waveform signal with a preset step length through the standard feature code to obtain a plurality of groups of sub-waveform data. For example, the preset step length may be 1, the length of the standard feature code is N, and the length of the target waveform signal is N1. Then, the number of sub-waveform data obtained by performing sliding window processing on the target waveform signal with a step length of 1 through the standard feature code is N1-N+1.
[0098] After obtaining several groups of sub-waveform data, the electronic device can calculate the correlation between each group of sub-waveform data and the standard feature code to obtain the correlation corresponding to the sub-waveform data, thereby obtaining the correlation corresponding to each group of sub-waveform data.
[0099] Exemplarily, the electronic device may calculate the correlation between the sub-waveform data and the standard feature code by the following formula to obtain the correlation corresponding to the sub-waveform data:
[0100]
[0101] Among them, WAVE_TM[0][j:j+N-1] can represent the various amplitudes in the sub-waveform data, WAVE_STD[j] can represent the various amplitudes in the standard feature code, x=[0:N1-N], so N1-N+1 coherence calculation results f0[0:N1-N] can be generated, f0[0] is the correlation operation result of WAVE_TM[0][0:N-1] and WAVE_STD[0:N-1], and f0[1] is the correlation operation result of WAVE_TM[0][1:1+N-1] and WAVE_STD[0:N-1].
[0102] After obtaining the correlation corresponding to each group of sub-waveform data, the electronic device can determine the correlation calculation result corresponding to the target waveform signal according to the correlation corresponding to each group of sub-waveform data.
[0103] The electronic device can obtain the correlation calculation results corresponding to each target waveform signal in the above manner.
[0104] For example, see Figure 6 , Figure 6 A schematic diagram of correlation calculation results corresponding to various target waveform signals provided in an embodiment of the present application. Figure 6 Included are the correlations corresponding to each different sliding window subscript in each target waveform signal.
[0105] In S106, matching parameters of the feature code are determined according to the correlation calculation results corresponding to each target waveform signal.
[0106] In the embodiment of the present application, after obtaining the correlation calculation result corresponding to each target waveform signal, the electronic device can determine the matching parameters of the feature code according to the correlation calculation result corresponding to each target waveform signal.
[0107] Specifically, the electronic device may first determine the target sub-waveform data with the highest correlation among the sub-waveform data in each target waveform signal. Figure 6In the above, the target sub-waveform data with the highest correlation among the sub-waveform data in each target waveform signal is the sub-waveform data corresponding to the sliding window subscript 3 in the target waveform signal WAVE_TM[0] and the sub-waveform data corresponding to the sliding window subscript 4 in the target waveform signal WAVE_TM[0].
[0108] After determining the target sub-waveform data with the highest correlation among the sub-waveform data, the electronic device can determine the adjacent sub-waveform data of the target sub-waveform data. Taking the sub-waveform data corresponding to the sliding window subscript 4 in the target waveform signal WAVE_TM[0] as an example, its adjacent sub-waveform data are the sub-waveform data corresponding to the sliding window subscript 3 in the target waveform signal WAVE_TM[0] and the sub-waveform data corresponding to the sliding window subscript 5 in the target waveform signal WAVE_TM[0].
[0109] After determining the adjacent sub-waveform data of the target sub-waveform data, the electronic device can determine whether the correlation corresponding to the target sub-waveform data and the correlation of any adjacent sub-waveform data are both greater than a preset correlation threshold. If the correlation corresponding to the target sub-waveform data and the correlation of any adjacent sub-waveform data are both greater than the preset correlation threshold, the sliding window subscript corresponding to the target sub-waveform data and the correlation corresponding to the target sub-waveform data can be determined as matching parameters of the feature code.
[0110] Exemplarily, the preset correlation threshold is 95%. Taking the sub-waveform data corresponding to the sliding window subscript 4 in the target waveform signal WAVE_TM[0] as an example, since the correlation of the sub-waveform data corresponding to the sliding window subscript 4 in the target waveform signal WAVE_TM[0] is greater than 95, and the sub-waveform data corresponding to the sliding window subscript 3 in the target waveform signal WAVE_TM[0] is also greater than 95%, the sliding window subscript 4 and the corresponding correlation 100% can be jointly determined as the matching parameters of the feature code.
[0111] Exemplarily, the preset correlation threshold is 95%. Taking the sub-waveform data corresponding to the sliding window subscript 3 in the target waveform signal WAVE_TM[0] as an example, since the correlation of the sub-waveform data corresponding to the sliding window subscript 3 in the target waveform signal WAVE_TM[0] is greater than 95, and the sub-waveform data corresponding to the sliding window subscript 4 in the target waveform signal WAVE_TM[0] is also greater than 95%, the sliding window subscript 3 and the corresponding correlation 100% can be jointly determined as the matching parameters of the feature code.
[0112] Based on this, the matching parameters of the feature code may be a sliding window subscript 3 and a corresponding correlation of 100%, and a sliding window subscript 4 and a corresponding correlation of 100%.
[0113] In the embodiment of the present application, after determining the matching parameters of the feature code, the electronic device can determine the matching result of the feature code according to the matching parameters of the feature code. In addition, after determining the matching parameters of the feature code, the electronic device can also train a preset feature code matching model through the matching parameters of the feature code to improve the feature code matching model.
[0114] It can be seen from the above that in the method for determining the feature coding matching parameters provided in the embodiment of the present application, the initial waveform signal of the feature coding is first obtained, and then the cumulative distribution information of the waveform amplitude of the initial waveform signal is determined, and then the logical matching threshold is determined based on the cumulative distribution information, and then a plurality of target waveform signals are generated based on the logical matching threshold and the initial waveform signal, and then for each target waveform signal, the correlation between the target waveform signal and the preset standard feature code is calculated to obtain the corresponding correlation calculation result, and finally the matching parameters are determined based on each correlation calculation result. Through the method for determining the feature coding matching parameters of the present application, a plurality of target waveform signals can be generated based on the initial waveform signal, and then the correlation calculation results corresponding to each target waveform signal can be determined respectively, so that the matching parameters of the feature coding corresponding to the target waveform signal with the highest correlation can be determined as the optimal matching parameters of the feature coding, so that the optimal matching parameters of the feature coding can be used for feature coding matching, thereby improving the matching accuracy of the feature coding.
[0115] Based on the method for determining the feature coding matching parameters provided in the above embodiment, the present application further provides a device for determining the feature coding matching parameters to implement the above method embodiment. Figure 7 , Figure 7 A schematic diagram of a structure of a device for determining feature coding matching parameters provided in an embodiment of the present application. Figure 7 As shown, the feature coding matching parameter determination device 70 may include: a waveform signal acquisition unit 71, a first determination unit 72, a second determination unit 73, a signal generation unit 74, a correlation calculation unit 75 and a third determination unit 76. Among them:
[0116] The waveform signal acquisition unit 71 is used to acquire an initial waveform signal of feature coding.
[0117] The first determining unit 72 is used to determine the cumulative distribution information of the waveform amplitude of the initial waveform signal.
[0118] The second determining unit 73 is used to determine a logic matching threshold according to the cumulative distribution information.
[0119] The signal generating unit 74 is used to generate a plurality of target waveform signals according to the logic matching threshold and the initial waveform signal.
[0120] The correlation calculation unit 75 is used to perform correlation calculation on each target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal.
[0121] The third determination unit 76 is used to determine the matching parameters of the feature code according to the correlation calculation result corresponding to each target waveform signal.
[0122] Optionally, the first determining unit 72 is specifically configured to:
[0123] Determine the maximum amplitude and the minimum amplitude of the initial waveform signal;
[0124] According to the maximum amplitude value and the minimum amplitude value, several amplitude intervals are determined;
[0125] According to the initial waveform signal, the probability density of each amplitude interval is determined;
[0126] The cumulative distribution information is determined based on the probability density of each amplitude interval.
[0127] Optionally, the second determining unit 73 is specifically configured to:
[0128] Determine a first cumulative probability threshold and a second cumulative probability threshold according to the standard characteristic code and a preset error tolerance range;
[0129] Determine an upper threshold value of a logic matching threshold according to the cumulative distribution information and the first cumulative probability threshold;
[0130] Determine a lower threshold value of a logic matching threshold according to the cumulative distribution information and a second cumulative probability threshold;
[0131] A logic match threshold is determined based on the upper threshold and the lower threshold.
[0132] Optionally, the second determining unit 73 is further configured to:
[0133] If the difference between the upper threshold value and the lower threshold value is smaller than the preset threshold value, it is determined that the initial waveform signal is a noise signal.
[0134] Optionally, the signal generating unit 74 is specifically used for:
[0135] Determine the difference between the upper threshold value and the lower threshold value, and the number of target waveform signals;
[0136] The lower threshold value, difference value and quantity are used to determine the amplitude threshold value corresponding to each target waveform signal;
[0137] According to the amplitude thresholds and the initial waveform signal, each target waveform signal is generated.
[0138] Optionally, the correlation calculation unit 75 is specifically used for:
[0139] Perform sliding window processing on the target waveform signal with a preset step length through a standard feature code to obtain several groups of sub-waveform data;
[0140] For each group of sub-waveform data, the correlation between the sub-waveform data and the standard feature code is calculated to obtain the correlation corresponding to the sub-waveform data;
[0141] According to the correlations corresponding to the sub-waveform data, the correlation calculation result corresponding to the target waveform signal is determined.
[0142] Optionally, the third determining unit 76 is specifically configured to:
[0143] Determine the target sub-waveform data with the highest correlation among the sub-waveform data in each target waveform signal;
[0144] Determine adjacent sub-waveform data of the target sub-waveform data;
[0145] If the correlation corresponding to the target sub-waveform data and the correlation corresponding to any adjacent sub-waveform data are greater than the preset correlation threshold, the sliding window subscript corresponding to the target sub-waveform data and the correlation corresponding to the target sub-waveform data are determined as matching parameters of the feature code.
[0146] See also Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 8 As shown, the electronic device 8 provided in this embodiment may include: a processor 80, a memory 81, and a computer program 82 stored in the memory 81 and executable on the processor 80, such as a program corresponding to the method for determining feature coding matching parameters. When the processor 80 executes the computer program 82, the steps in the above-mentioned method for determining feature coding matching parameters are implemented, such as Figure 1 Alternatively, when the processor 80 executes the computer program 82, the functions of each module / unit in the above-mentioned feature coding matching parameter determination device embodiment are realized, for example Figure 3 The functions of the units 71 to 76 are shown.
[0147] Exemplarily, the computer program 82 may be divided into one or more modules / units, one or more modules / units are stored in the memory 81 and executed by the processor 80 to complete the present application. The one or more modules / units may be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program 82 in the electronic device 8. For example, the computer program 82 may be divided into a waveform signal acquisition unit 71, a first determination unit 72, a second determination unit 73, a signal generation unit 74, a correlation calculation unit 75, and a third determination unit 76. For the specific functions of each unit, please refer to Figure 7 The relevant descriptions in the corresponding embodiments are not repeated here.
[0148] Those skilled in the art will understand that Figure 8 The electronic device 8 is merely an example and does not limit the electronic device 8 , and may include more or less components than those shown in the figure, or may combine certain components, or may include different components.
[0149] The processor 80 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.
[0150] The memory 81 may be an internal storage unit of the electronic device 8, such as a hard disk or memory of the electronic device 8. The memory 81 may also be an external storage device of the electronic device 8, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, or a flash card, etc., equipped on the electronic device 8. Further, the memory 81 may also include both an internal storage unit of the electronic device 8 and an external storage device. The memory 81 is used to store computer programs and other programs and data required by the electronic device. The memory 81 may also be used to temporarily store data that has been output or is to be output.
[0151] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units is used as an example for illustration. In practical applications, the above-mentioned functions can be assigned to different functional units as needed, that is, the internal structure of the device for determining the feature coding matching parameters can be divided into different functional units to complete all or part of the functions described above. The functional units in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.
[0152] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.
[0153] An embodiment of the present application provides a computer program product. When the computer program product is executed on a terminal device, the terminal device implements the steps in the above-mentioned various method embodiments.
[0154] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0155] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.
[0156] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.
Claims
1. A method for determining feature coding matching parameters, characterized in that: include: Acquire an initial waveform signal of feature coding; Determining cumulative distribution information of the waveform amplitude of the initial waveform signal; Determining a logic matching threshold according to the cumulative distribution information; Generate a plurality of target waveform signals according to the logic matching threshold and the initial waveform signal; For each of the target waveform signals, a correlation calculation is performed between the target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal; According to the correlation calculation result corresponding to each of the target waveform signals, the matching parameters of the feature code are determined.
2. The method according to claim 1, characterized in that The step of determining the cumulative distribution information of the waveform amplitude of the initial waveform signal comprises: Determining the maximum amplitude and the minimum amplitude of the initial waveform signal; Determining a plurality of amplitude intervals according to the maximum amplitude value and the minimum amplitude value; Determining the probability density of each of the amplitude intervals according to the initial waveform signal; The cumulative distribution information is determined according to the probability density of each of the amplitude intervals.
3. The method according to claim 2, characterized in that The step of determining a logic matching threshold according to the cumulative distribution information includes: Determining a first cumulative probability threshold and a second cumulative probability threshold according to the standard feature code and a preset error tolerance range; Determining an upper threshold value of the logic matching threshold according to the cumulative distribution information and the first cumulative probability threshold; Determining a lower threshold value of the logic matching threshold according to the cumulative distribution information and the second cumulative probability threshold; The logic matching threshold is determined according to the upper threshold value and the lower threshold value.
4. The method according to claim 3, characterized in that After determining the logic matching threshold according to the cumulative distribution information, the method further includes: If the difference between the upper threshold value and the lower threshold value is smaller than a preset threshold value, it is determined that the initial waveform signal is a noise signal.
5. The method according to claim 3, characterized in that: The step of generating a plurality of target waveform signals according to the logic matching threshold and the initial waveform signal comprises: Determine the difference between the upper threshold value and the lower threshold value, and the number of the target waveform signals; The lower threshold value, the difference value and the quantity are used to determine the amplitude threshold value corresponding to each of the target waveform signals; Each of the target waveform signals is generated according to each of the amplitude thresholds and the initial waveform signal.
6. The method according to any one of claims 1 to 5, characterized in that: The step of performing correlation calculation on the target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal includes: Perform sliding window processing on the target waveform signal with a preset step length through the standard feature code to obtain several groups of sub-waveform data; For each group of the sub-waveform data, a correlation calculation is performed between the sub-waveform data and the standard feature code to obtain a correlation corresponding to the sub-waveform data; The correlation calculation result corresponding to the target waveform signal is determined according to the correlation corresponding to each of the sub-waveform data.
7. The method according to claim 6, characterized in that Determining the matching parameters of the feature code according to the correlation calculation results corresponding to each of the target waveform signals includes: Determine the target sub-waveform data with the highest correlation among the sub-waveform data in each of the target waveform signals; Determine adjacent sub-waveform data of the target sub-waveform data; If the correlation corresponding to the target sub-waveform data and the correlation corresponding to any adjacent sub-waveform data are greater than a preset correlation threshold, the sliding window subscript corresponding to the target sub-waveform data and the correlation corresponding to the target sub-waveform data are determined as matching parameters of the feature code.
8. A device for determining feature coding matching parameters, characterized in that: include: A waveform signal acquisition unit, used to acquire an initial waveform signal of a feature code; A first determining unit, configured to determine cumulative distribution information of the waveform amplitude of the initial waveform signal; A second determining unit, configured to determine a logic matching threshold according to the cumulative distribution information; A signal generating unit, configured to generate a plurality of target waveform signals according to the logic matching threshold and the initial waveform signal; A correlation calculation unit, used for performing correlation calculation on each target waveform signal and a preset standard feature code to obtain a correlation calculation result corresponding to the target waveform signal; The third determination unit is used to determine the matching parameters of the feature code according to the correlation calculation result corresponding to each of the target waveform signals.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the processor implements the steps in the method for determining feature coding matching parameters as described in any one of claims 1 to 7.
10. A computer program, characterized in that When the computer program is executed by a processor, each step of the method for determining feature coding matching parameters as claimed in any one of claims 1 to 7 is implemented.