Digital wireless audio signal noise reduction optimization method based on Matlab

Abstract

The invention relates to the technical field of digital signal processing, in particular to a digital wireless audio signal noise reduction optimization method based on Matlab, and the method comprises the steps: S1, obtaining the real-time transmission data of a digital wireless audio signal; s2, performing noise identification processing according to the real-time transmission data of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal; s3, performing feature analysis processing based on Matlab according to the real-time transmission data and the noise type data of the digital wireless audio signal to establish a noise feature database of the digital wireless audio signal; s4, establishing a noise reduction model of the digital wireless audio signal based on SVM-LSTM by using the real-time transmission data of the digital wireless audio signal and the noise feature database; s5, utilizing the noise reduction model of the digital wireless audio signal to obtain a noise reduction optimization result of the digital wireless audio signal; compared with the prior art, the limitation of the existing filtering noise reduction technology is solved, and the noise reduction accuracy and processing efficiency are improved.

Description

Technical Field

[0001] The invention relates to the technical field of digital signal processing, and in particular to a digital wireless audio signal noise reduction optimization method based on Matlab. Background Art

[0002] With the development of wireless communication technology, digital wireless audio signals are being used more and more widely, such as Bluetooth headsets, wireless microphones, car audio systems, etc. However, in the process of wireless audio signal transmission, due to the influence of various factors, such as electromagnetic interference, multipath propagation, etc., noise will inevitably be mixed into the signal. These noises will seriously affect the quality of the audio signal and the user's auditory experience, and need to be processed by noise reduction.

[0003] Existing noise reduction technologies mainly focus on filtering processing, including time domain filtering, frequency domain filtering, spectral subtraction, etc. Although these methods can reduce the impact of noise to a certain extent, they are often aimed at filtering out specific types of noise and have poor adaptability to complex and changeable noise environments. They cannot achieve comprehensive noise filtering and are prone to introducing additional noise, causing signal distortion, which in turn affects the noise reduction effect. At the same time, the high complexity of the algorithm used will cause signal processing delays, making it difficult to meet communication needs. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a digital wireless audio signal noise reduction optimization method based on Matlab, which achieves effective noise reduction while maintaining low latency in a complex and changeable noise environment.

[0005] A digital wireless audio signal noise reduction optimization method based on Matlab, comprising:

[0006] S1, obtaining real-time transmission data of digital wireless audio signals;

[0007] S2. performing noise identification processing according to the real-time transmission data of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal;

[0008] S3, establishing a noise feature database of the digital wireless audio signal by performing feature analysis based on Matlab according to the real-time transmission data and noise type data of the digital wireless audio signal;

[0009] S4, using the real-time transmission data of the digital wireless audio signal and the noise feature database to establish a noise reduction model for the digital wireless audio signal based on SVM-LSTM;

[0010] S5. Obtain a digital wireless audio signal noise reduction optimization result using the digital wireless audio signal noise reduction model.

[0011] Furthermore, obtaining real-time transmission data of the digital wireless audio signal includes:

[0012] S1-1, obtaining source data of a digital wireless audio signal;

[0013] S1-2, acquiring corresponding sampling environment information data and sampling device information data respectively according to the source data of the digital wireless audio signal;

[0014] S1-3, using the source data, sampling environment information data and sampling device information data of the digital wireless audio signal as transmission data of the digital wireless audio signal;

[0015] S1-5, collecting the transmission data of the digital wireless audio signal corresponding to the current time t as the real-time transmission data of the digital wireless audio signal;

[0016] The sampling environment information data includes the number of channels, sampling frequency, sampling time and frame structure data, and the sampling device information data includes MAC address, sampling device voltage and sampling device current.

[0017] Furthermore, the noise type data of the digital wireless audio signal obtained by performing noise identification processing on the real-time transmission data of the digital wireless audio signal includes:

[0018] S2-1, acquiring historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal;

[0019] S2-2, obtaining a noise comparison benchmark of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal;

[0020] S2-3. Perform noise identification processing according to the noise ratio of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal.

[0021] Further, acquiring historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal includes:

[0022] S2-1-1, acquiring the collection environment information data and the collection device information data corresponding to the time tn according to the real-time transmission data of the digital wireless audio signal;

[0023] S2-1-2, determine whether the collection environment information data and collection device information data at time tn are consistent with the collection environment information data and collection device information data at time t, if so, use the collection environment information data and collection device information data at time tn as the historical transmission data of the digital wireless audio signal, otherwise, obtain the collection environment information data and collection device information data that are consistent with the collection environment information data and collection device information data at time t as the historical transmission data of the digital wireless audio signal;

[0024] Wherein, tn is any preceding moment corresponding to the current moment, and n is a natural number greater than 1.

[0025] Further, obtaining a noise comparison benchmark of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal includes:

[0026] S2-2-1. Acquire historical noise data of the corresponding digital wireless audio signal according to the historical transmission data of the digital wireless audio signal;

[0027] S2-2-2, performing sampling environment division processing according to the historical noise data of the digital wireless audio signal to respectively obtain channel noise data, frequency noise data and sampling time noise data as sampling environment noise data;

[0028] S2-2-3, performing sampling device division processing according to the historical noise data of the digital wireless audio signal to obtain sampling device noise data corresponding to different MAC addresses;

[0029] S2-2-4. Obtain corresponding sampling environment information data and sampling device information data according to the sampling environment noise data and sampling device noise data;

[0030] S2-2-5. Use the sampled environment information data and the sampled device information data as a noise comparison benchmark for the digital wireless audio signal.

[0031] Further, performing noise identification processing according to the noise ratio of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal includes:

[0032] S2-3-1. Obtain noise data corresponding to changes in the sampling environment, noise data corresponding to changes in the sampling device, and noise data corresponding to changes in the sampling time according to the noise comparison benchmark of the digital wireless audio signal;

[0033] S2-3-2, establishing a first mapping between the sampling environment and the noise according to the noise data of the sampling environment change, and establishing a first trend of the noise changing with the sampling environment;

[0034] S2-3-3, establishing a second mapping between the sampling device and the noise according to the noise data of the sampling device change, and establishing a second trend of the noise changing with the sampling device;

[0035] S2-3-4, establishing a third mapping based on the noise data of sampling time variation and the first mapping, and establishing a third trend of noise variation with sampling time under the same sampling environment;

[0036] S2-3-5, establishing a fourth mapping based on the noise data of sampling time variation and the second mapping, and establishing a fourth trend of noise variation with sampling time under the same sampling device;

[0037] S2-3-6, determining whether the third trend changes periodically, if so, outputting the sampling environment corresponding to the third trend as fixed noise data, otherwise, outputting the sampling environment corresponding to the third trend as random noise data;

[0038] S2-3-7, determining whether the fourth trend changes periodically, if so, outputting the sampling device corresponding to the fourth trend as fixed noise data, otherwise, outputting the sampling device corresponding to the fourth trend as random noise data;

[0039] S2-3-8, using the fixed noise data or the random noise data as noise type data of the digital wireless audio signal;

[0040] The first trend, the second trend, the third trend and the fourth trend are all numerical trends of noise data.

[0041] Further, establishing a noise feature database of a digital wireless audio signal by performing feature analysis based on Matlab according to the real-time transmission data and noise type data of the digital wireless audio signal includes:

[0042] S3-1, according to the real-time transmission data of the digital wireless audio signal, resampling processing, normalization processing and segmentation and windowing processing are performed in sequence based on Matlab to obtain pre-processed data corresponding to the real-time transmission of the digital wireless audio signal;

[0043] S3-2, performing feature extraction based on Matlab according to the pre-processed data of the real-time transmission of the digital wireless audio signal to obtain time domain features and frequency domain features of the corresponding digital wireless audio signal;

[0044] S3-3, obtaining noise data characteristics according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal;

[0045] S3-4. Establish a noise feature database of digital wireless audio signals using the noise data features.

[0046] Further, acquiring noise data features according to the time domain features and frequency domain features of the digital wireless audio signal includes:

[0047] S3-3-1. Obtain the historical average frequency corresponding to the digital wireless audio signal;

[0048] S3-3-2 performing frequency segmentation according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal to respectively obtain a main area and a secondary area of ​​the digital wireless audio signal;

[0049] S3-3-2-1. Obtain a corresponding frequency image according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal;

[0050] S3-3-2-2, performing average frequency division processing on the frequency image of the digital wireless audio signal to obtain corresponding primary areas and secondary areas;

[0051] S3-3-3, performing comparative analysis based on the noise type data of the digital wireless audio signal in the primary area and the secondary area of ​​the digital wireless audio signal to obtain random noise data;

[0052] S3-3-3-1, obtaining corresponding amplitude features according to the main area and the secondary area of ​​the digital wireless audio signal respectively;

[0053] S3-3-3-2. Acquire corresponding sampling environment data and sampling equipment data according to the amplitude characteristics;

[0054] S3-3-3-3, acquiring corresponding random noise data based on the noise type data of the digital wireless audio signal according to the sampling environment data and the sampling device data;

[0055] S3-3-4. Acquire, according to the random noise data, a signal strength feature, an amplitude feature, and a phase feature of the corresponding random noise data as noise data features;

[0056] Among them, the average frequency segmentation is to take the absolute value of the historical average frequency, and perform segmentation processing based on the absolute value of the historical average frequency. The main area is the image area below the positive value of the average frequency and above the negative value of the average frequency, and the secondary area is the image area above the positive value of the average frequency and below the negative value of the average frequency.

[0057] Furthermore, establishing a noise reduction model for digital wireless audio signals based on SVM-LSTM using the real-time transmission data of the digital wireless audio signals and the noise feature database includes:

[0058] S4-1, using the real-time transmission data of the digital wireless audio signal and the historical noise feature data in the noise feature database as a training set, and the noise type data as a verification set, to establish an initial classification model based on SVM;

[0059] S4-2, using the real-time transmission data input of the digital wireless audio signal to obtain an initial data output result based on an initial classification model;

[0060] S4-3, determine whether the initial data output result corresponds to the verification set, if so, execute S4-4, otherwise, use the initial output result as the updated training set and return to S4-1;

[0061] S4-4, obtaining data characteristics of real-time transmission data of digital wireless audio signals;

[0062] S4-5, comparing the data features of the real-time transmission of the digital wireless audio signal with the noise feature database to obtain denoising data features of the corresponding digital wireless audio signal;

[0063] S4-6, taking the output result of the initial data as input, taking the denoised data of the digital wireless audio signal corresponding to the denoised data feature of the digital wireless audio signal as output, and establishing a noise reduction training model based on LSTM;

[0064] S4-7, obtaining the initial feature output result of the noise reduction training model, determining whether the initial feature output result corresponds to the denoising data of the digital wireless audio signal, if so, executing S4-8, otherwise, using the data feature of the digital wireless audio data as input, and returning to S4-6;

[0065] S4-8, respectively obtaining denoising data of the digital wireless audio signal at time t and time t+1 and inputting them into the denoising training model to obtain corresponding model output results;

[0066] S4-9. Determine whether the change trend of the model output result corresponding to time t is consistent with that of the model output result at time t+1. If so, output the initial training model as a noise reduction optimization function model of the digital wireless audio signal. Otherwise, obtain the outliers with inconsistent change trends as the updated training set, and return to S4-1.

[0067] Furthermore, obtaining a digital wireless audio signal noise reduction optimization result by using the digital wireless audio signal noise reduction model includes:

[0068] S5-1, using the noise reduction model of the digital wireless audio signal to obtain a real-time output result of noise reduction data corresponding to the digital wireless audio signal;

[0069] S5-2, obtaining channel data corresponding to the real-time transmission of the digital wireless audio signal according to the real-time output result of the digital wireless audio signal noise reduction data;

[0070] S5-3, obtaining multi-channel data corresponding to the real-time transmission of digital wireless audio signal noise reduction data according to the channel data transmitted in real time by the digital wireless audio signal;

[0071] S5-4, obtaining corresponding first channel output data and second channel output data according to the multi-channel data transmitted in real time by the digital wireless audio signal noise reduction data;

[0072] S5-5, determining whether the first channel output data and the second channel output data are synchronized, if so, outputting the first channel output data and the second channel output data as the initial noise reduction result of the digital wireless audio signal, and directly executing S5-7, otherwise, executing S5-6;

[0073] S5-6, determining whether there is a delay relationship between the second channel output data and the first channel output data, if so, using the second channel output data and the first channel output data as an updated training set, and returning to S4-1, otherwise, using the first channel output data and the second channel output data as the initial noise reduction result of the digital wireless audio signal, and executing S5-7;

[0074] S5-7, obtaining a corresponding signal-to-noise ratio according to an initial noise reduction result of the digital wireless audio signal;

[0075] S5-8. Determine whether the signal-to-noise ratio is lower than the standard signal-to-noise ratio of the historical noise reduction result of the corresponding digital wireless audio signal. If so, output the initial noise reduction result of the digital wireless audio signal as the noise reduction optimization result of the digital wireless audio signal. Otherwise, obtain multi-channel data of the real-time transmission of the digital wireless audio signal noise reduction data corresponding to the initial noise reduction result.

[0076] Compared with the closest prior art, the present invention has the following beneficial effects:

[0077] The present invention provides a digital wireless audio signal noise reduction optimization method based on Matlab. By comparing and analyzing the real-time transmission data of the digital wireless audio signal, taking the noise data under the same acquisition environment and acquisition equipment as a benchmark, the data features and noise data features of the digital wireless audio signal are obtained based on Matlab, and a noise reduction model is constructed by combining a support vector machine and a long short-term memory network. The limitations of the existing filtering noise reduction technology are solved, the dependence on specific noise types is reduced, the change of complex noise environment can be coped with, different types of noise can be flexibly identified, and effective noise reduction of the digital wireless audio signal is performed. Compared with the prior art, the accuracy and processing efficiency of noise recognition are improved, the signal distortion caused by excessive noise reduction is reduced, and the quality of the audio signal is significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 The present invention is a flow chart of a digital wireless audio signal noise reduction optimization method based on Matlab. DETAILED DESCRIPTION

[0079] The specific implementation modes of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0080] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] Embodiment 1:

[0082] The present invention provides a digital wireless audio signal noise reduction optimization method based on Matlab, such as Figure 1 As shown, including:

[0083] S1, obtaining real-time transmission data of digital wireless audio signals;

[0084] S2. performing noise identification processing according to the real-time transmission data of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal;

[0085] S3, establishing a noise feature database of the digital wireless audio signal by performing feature analysis based on Matlab according to the real-time transmission data and noise type data of the digital wireless audio signal;

[0086] S4, using the real-time transmission data of the digital wireless audio signal and the noise feature database to establish a noise reduction model for the digital wireless audio signal based on SVM-LSTM;

[0087] S5. Obtain a digital wireless audio signal noise reduction optimization result using the digital wireless audio signal noise reduction model.

[0088] S1 specifically includes:

[0089] S1-1, obtaining source data of a digital wireless audio signal;

[0090] S1-2, acquiring corresponding sampling environment information data and sampling device information data respectively according to the source data of the digital wireless audio signal;

[0091] S1-3, using the source data, sampling environment information data and sampling device information data of the digital wireless audio signal as transmission data of the digital wireless audio signal;

[0092] S1-5, collecting the transmission data of the digital wireless audio signal corresponding to the current time t as the real-time transmission data of the digital wireless audio signal;

[0093] The sampling environment information data includes the number of channels, sampling frequency, sampling time and frame structure data, and the sampling device information data includes MAC address, sampling device voltage and sampling device current.

[0094] S2 specifically includes:

[0095] S2-1, acquiring historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal;

[0096] S2-2, obtaining a noise comparison benchmark of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal;

[0097] S2-3. Perform noise identification processing according to the noise ratio of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal.

[0098] S2-1 specifically includes:

[0099] S2-1-1, acquiring the collection environment information data and the collection device information data corresponding to the time tn according to the real-time transmission data of the digital wireless audio signal;

[0100] S2-1-2, determine whether the collection environment information data and collection device information data at time tn are consistent with the collection environment information data and collection device information data at time t, if so, use the collection environment information data and collection device information data at time tn as the historical transmission data of the digital wireless audio signal, otherwise, obtain the collection environment information data and collection device information data that are consistent with the collection environment information data and collection device information data at time t as the historical transmission data of the digital wireless audio signal;

[0101] Wherein, tn is any preceding moment corresponding to the current moment, and n is a natural number greater than 1.

[0102] S2-2 specifically includes:

[0103] S2-2-1. Acquire historical noise data of the corresponding digital wireless audio signal according to the historical transmission data of the digital wireless audio signal;

[0104] S2-2-2, performing sampling environment division processing according to the historical noise data of the digital wireless audio signal to respectively obtain channel noise data, frequency noise data and sampling time noise data as sampling environment noise data;

[0105] S2-2-3, performing sampling device division processing according to the historical noise data of the digital wireless audio signal to obtain sampling device noise data corresponding to different MAC addresses;

[0106] S2-2-4. Obtain corresponding sampling environment information data and sampling device information data according to the sampling environment noise data and sampling device noise data;

[0107] S2-2-5. Use the sampled environment information data and the sampled device information data as a noise comparison benchmark for the digital wireless audio signal.

[0108] S2-3 specifically includes:

[0109] S2-3-1. Obtain noise data corresponding to changes in the sampling environment, noise data corresponding to changes in the sampling device, and noise data corresponding to changes in the sampling time according to the noise comparison benchmark of the digital wireless audio signal;

[0110] S2-3-2, establishing a first mapping between the sampling environment and the noise according to the noise data of the sampling environment change, and establishing a first trend of the noise changing with the sampling environment;

[0111] S2-3-3, establishing a second mapping between the sampling device and the noise according to the noise data of the sampling device change, and establishing a second trend of the noise changing with the sampling device;

[0112] S2-3-4, establishing a third mapping based on the noise data of sampling time variation and the first mapping, and establishing a third trend of noise variation with sampling time under the same sampling environment;

[0113] S2-3-5, establishing a fourth mapping based on the noise data of sampling time variation and the second mapping, and establishing a fourth trend of noise variation with sampling time under the same sampling device;

[0114] S2-3-6, determining whether the third trend changes periodically, if so, outputting the sampling environment corresponding to the third trend as fixed noise data, otherwise, outputting the sampling environment corresponding to the third trend as random noise data;

[0115] S2-3-7, determining whether the fourth trend changes periodically, if so, outputting the sampling device corresponding to the fourth trend as fixed noise data, otherwise, outputting the sampling device corresponding to the fourth trend as random noise data;

[0116] S2-3-8, using the fixed noise data or the random noise data as noise type data of the digital wireless audio signal;

[0117] The first trend, the second trend, the third trend and the fourth trend are all numerical trends of noise data.

[0118] S3 specifically includes:

[0119] S3-1, according to the real-time transmission data of the digital wireless audio signal, resampling processing, normalization processing and segmentation and windowing processing are performed in sequence based on Matlab to obtain pre-processed data corresponding to the real-time transmission of the digital wireless audio signal;

[0120] S3-2, performing feature extraction based on Matlab according to the pre-processed data of the real-time transmission of the digital wireless audio signal to obtain time domain features and frequency domain features of the corresponding digital wireless audio signal;

[0121] S3-3, obtaining noise data characteristics according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal;

[0122] S3-4. Establish a noise feature database of digital wireless audio signals using the noise data features.

[0123] S3-3 specifically includes:

[0124] S3-3-1. Obtain the historical average frequency corresponding to the digital wireless audio signal;

[0125] S3-3-2 performing frequency segmentation according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal to respectively obtain a main area and a secondary area of ​​the digital wireless audio signal;

[0126] S3-3-2-1. Obtain a corresponding frequency image according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal;

[0127] S3-3-2-2, performing average frequency division processing on the frequency image of the digital wireless audio signal to obtain corresponding primary areas and secondary areas;

[0128] S3-3-3, performing comparative analysis based on the noise type data of the digital wireless audio signal in the primary area and the secondary area of ​​the digital wireless audio signal to obtain random noise data;

[0129] S3-3-3-1, obtaining corresponding amplitude features according to the main area and the secondary area of ​​the digital wireless audio signal respectively;

[0130] S3-3-3-2. Acquire corresponding sampling environment data and sampling equipment data according to the amplitude characteristics;

[0131] S3-3-3-3, acquiring corresponding random noise data based on the noise type data of the digital wireless audio signal according to the sampling environment data and the sampling device data;

[0132] S3-3-4. Acquire, according to the random noise data, a signal strength feature, an amplitude feature, and a phase feature of the corresponding random noise data as noise data features;

[0133] Among them, the average frequency segmentation is to take the absolute value of the historical average frequency, and perform segmentation processing based on the absolute value of the historical average frequency. The main area is the image area below the positive value of the average frequency and above the negative value of the average frequency, and the secondary area is the image area above the positive value of the average frequency and below the negative value of the average frequency.

[0134] S4 specifically includes:

[0135] S4-1, using the real-time transmission data of the digital wireless audio signal and the historical noise feature data in the noise feature database as a training set, and the noise type data as a verification set, to establish an initial classification model based on SVM;

[0136] S4-2, using the real-time transmission data input of the digital wireless audio signal to obtain an initial data output result based on an initial classification model;

[0137] S4-3, determine whether the initial data output result corresponds to the verification set, if so, execute S4-4, otherwise, use the initial output result as the updated training set and return to S4-1;

[0138] S4-4, obtaining data characteristics of real-time transmission data of digital wireless audio signals;

[0139] S4-5, comparing the data features of the real-time transmission of the digital wireless audio signal with the noise feature database to obtain denoising data features of the corresponding digital wireless audio signal;

[0140] S4-6, taking the output result of the initial data as input, taking the denoised data of the digital wireless audio signal corresponding to the denoised data feature of the digital wireless audio signal as output, and establishing a noise reduction training model based on LSTM;

[0141] S4-7, obtaining the initial feature output result of the noise reduction training model, determining whether the initial feature output result corresponds to the denoising data of the digital wireless audio signal, if so, executing S4-8, otherwise, using the data feature of the digital wireless audio data as input, and returning to S4-6;

[0142] S4-8, respectively obtaining denoising data of the digital wireless audio signal at time t and time t+1 and inputting them into the denoising training model to obtain corresponding model output results;

[0143] S4-9. Determine whether the change trend of the model output result corresponding to time t is consistent with that of the model output result at time t+1. If so, output the initial training model as a noise reduction optimization function model of the digital wireless audio signal. Otherwise, obtain the outliers with inconsistent change trends as the updated training set, and return to S4-1.

[0144] S5 specifically includes:

[0145] S5-1, using the noise reduction model of the digital wireless audio signal to obtain a real-time output result of noise reduction data corresponding to the digital wireless audio signal;

[0146] S5-2, obtaining channel data corresponding to the real-time transmission of the digital wireless audio signal according to the real-time output result of the digital wireless audio signal noise reduction data;

[0147] S5-3, obtaining multi-channel data corresponding to the real-time transmission of digital wireless audio signal noise reduction data according to the channel data transmitted in real time by the digital wireless audio signal;

[0148] S5-4, obtaining corresponding first channel output data and second channel output data according to the multi-channel data transmitted in real time by the digital wireless audio signal noise reduction data;

[0149] S5-5, determining whether the first channel output data and the second channel output data are synchronized, if so, outputting the first channel output data and the second channel output data as the initial noise reduction result of the digital wireless audio signal, and directly executing S5-7, otherwise, executing S5-6;

[0150] S5-6, determining whether there is a delay relationship between the second channel output data and the first channel output data, if so, using the second channel output data and the first channel output data as an updated training set, and returning to S4-1, otherwise, using the first channel output data and the second channel output data as the initial noise reduction result of the digital wireless audio signal, and executing S5-7;

[0151] S5-7, obtaining a corresponding signal-to-noise ratio according to an initial noise reduction result of the digital wireless audio signal;

[0152] S5-8. Determine whether the signal-to-noise ratio is lower than the standard signal-to-noise ratio of the historical noise reduction result of the corresponding digital wireless audio signal. If so, output the initial noise reduction result of the digital wireless audio signal as the noise reduction optimization result of the digital wireless audio signal. Otherwise, obtain multi-channel data of the real-time transmission of the digital wireless audio signal noise reduction data corresponding to the initial noise reduction result.

[0153] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0154] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0155] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0156] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A digital wireless audio signal noise reduction optimization method based on Matlab, characterized in that: include: S1, obtaining real-time transmission data of digital wireless audio signals; S2. performing noise identification processing according to the real-time transmission data of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal; S3, establishing a noise feature database of the digital wireless audio signal by performing feature analysis based on Matlab according to the real-time transmission data and noise type data of the digital wireless audio signal; S4, using the real-time transmission data of the digital wireless audio signal and the noise feature database to establish a noise reduction model for the digital wireless audio signal based on SVM-LSTM; S5. Obtain a digital wireless audio signal noise reduction optimization result using the digital wireless audio signal noise reduction model.

2. A digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 1, characterized in that: Get real-time transmission data of digital wireless audio signals including: S1-1, obtaining source data of a digital wireless audio signal; S1-2, acquiring corresponding sampling environment information data and sampling device information data respectively according to the source data of the digital wireless audio signal; S1-3, using the source data, sampling environment information data and sampling device information data of the digital wireless audio signal as transmission data of the digital wireless audio signal; S1-5, collecting the transmission data of the digital wireless audio signal corresponding to the current time t as the real-time transmission data of the digital wireless audio signal; The sampling environment information data includes the number of channels, sampling frequency, sampling time and frame structure data, and the sampling device information data includes MAC address, sampling device voltage and sampling device current.

3. The digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 2, characterized in that: The noise type data of the digital wireless audio signal obtained by performing noise identification processing according to the real-time transmission data of the digital wireless audio signal includes: S2-1, acquiring historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal; S2-2, obtaining a noise comparison benchmark of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal; S2-3. Perform noise identification processing according to the noise ratio of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal.

4. The digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 3, characterized in that: Acquiring historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal includes: S2-1-1, acquiring the collection environment information data and the collection device information data corresponding to the time tn according to the real-time transmission data of the digital wireless audio signal; S2-1-2, determine whether the collection environment information data and collection device information data at time tn are consistent with the collection environment information data and collection device information data at time t, if so, use the collection environment information data and collection device information data at time tn as the historical transmission data of the digital wireless audio signal, otherwise, obtain the collection environment information data and collection device information data that are consistent with the collection environment information data and collection device information data at time t as the historical transmission data of the digital wireless audio signal; Wherein, tn is any preceding moment corresponding to the current moment, and n is a natural number greater than 1.

5. The digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 3, characterized in that: Acquiring a noise comparison benchmark of a digital wireless audio signal according to historical transmission data of the digital wireless audio signal includes: S2-2-1. Acquire historical noise data of the corresponding digital wireless audio signal according to the historical transmission data of the digital wireless audio signal; S2-2-2, performing sampling environment division processing according to the historical noise data of the digital wireless audio signal to respectively obtain channel noise data, frequency noise data and sampling time noise data as sampling environment noise data; S2-2-3, performing sampling device division processing according to the historical noise data of the digital wireless audio signal to obtain sampling device noise data corresponding to different MAC addresses; S2-2-4. Obtain corresponding sampling environment information data and sampling device information data according to the sampling environment noise data and sampling device noise data; S2-2-5. Use the sampled environment information data and the sampled device information data as a noise comparison benchmark for the digital wireless audio signal.

6. The digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 3, characterized in that: The step of performing noise identification processing according to the noise ratio of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal includes: S2-3-1. Obtain noise data corresponding to changes in the sampling environment, noise data corresponding to changes in the sampling device, and noise data corresponding to changes in the sampling time according to the noise comparison benchmark of the digital wireless audio signal; S2-3-2, establishing a first mapping between the sampling environment and the noise according to the noise data of the sampling environment change, and establishing a first trend of the noise changing with the sampling environment; S2-3-3, establishing a second mapping between the sampling device and the noise according to the noise data of the sampling device change, and establishing a second trend of the noise changing with the sampling device; S2-3-4, establishing a third mapping based on the noise data of sampling time variation and the first mapping, and establishing a third trend of noise variation with sampling time under the same sampling environment; S2-3-5, establishing a fourth mapping based on the noise data of sampling time variation and the second mapping, and establishing a fourth trend of noise variation with sampling time under the same sampling device; S2-3-6, determining whether the third trend changes periodically, if so, outputting the sampling environment corresponding to the third trend as fixed noise data, otherwise, outputting the sampling environment corresponding to the third trend as random noise data; S2-3-7, determining whether the fourth trend changes periodically, if so, outputting the sampling device corresponding to the fourth trend as fixed noise data, otherwise, outputting the sampling device corresponding to the fourth trend as random noise data; S2-3-8, using the fixed noise data or the random noise data as noise type data of the digital wireless audio signal; The first trend, the second trend, the third trend and the fourth trend are all numerical trends of noise data.

7. The digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 3, characterized in that: The noise characteristic database of the digital wireless audio signal is established by performing characteristic analysis and processing based on Matlab according to the real-time transmission data and noise type data of the digital wireless audio signal, including: S3-1, according to the real-time transmission data of the digital wireless audio signal, resampling processing, normalization processing and segmentation and windowing processing are performed in sequence based on Matlab to obtain pre-processed data corresponding to the real-time transmission of the digital wireless audio signal; S3-2, performing feature extraction based on Matlab according to the pre-processed data of the real-time transmission of the digital wireless audio signal to obtain time domain features and frequency domain features of the corresponding digital wireless audio signal; S3-3, obtaining noise data characteristics according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal; S3-4. Establish a noise feature database of digital wireless audio signals using the noise data features.

8. The digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 7, characterized in that: Acquiring noise data features according to the time domain features and frequency domain features of the digital wireless audio signal includes: S3-3-1. Obtain the historical average frequency corresponding to the digital wireless audio signal; S3-3-2 performing frequency segmentation according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal to respectively obtain a main area and a secondary area of ​​the digital wireless audio signal; S3-3-2-1. Obtain a corresponding frequency image according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal; S3-3-2-2, performing average frequency division processing on the frequency image of the digital wireless audio signal to obtain corresponding primary areas and secondary areas; S3-3-3, performing comparative analysis based on the noise type data of the digital wireless audio signal in the primary area and the secondary area of ​​the digital wireless audio signal to obtain random noise data; S3-3-3-1, obtaining corresponding amplitude features according to the main area and the secondary area of ​​the digital wireless audio signal respectively; S3-3-3-2. Acquire corresponding sampling environment data and sampling equipment data according to the amplitude characteristics; S3-3-3-3, acquiring corresponding random noise data based on the noise type data of the digital wireless audio signal according to the sampling environment data and the sampling device data; S3-3-4. Acquire, according to the random noise data, a signal strength feature, an amplitude feature, and a phase feature of the corresponding random noise data as noise data features; Among them, the average frequency segmentation is to take the absolute value of the historical average frequency, and perform segmentation processing based on the absolute value of the historical average frequency. The main area is the image area below the positive value of the average frequency and above the negative value of the average frequency, and the secondary area is the image area above the positive value of the average frequency and below the negative value of the average frequency.

9. The digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 8, characterized in that: The noise reduction model of the digital wireless audio signal is established based on SVM-LSTM using the real-time transmission data of the digital wireless audio signal and the noise feature database, including: S4-1, using the real-time transmission data of the digital wireless audio signal and the historical noise feature data in the noise feature database as a training set, and the noise type data as a verification set, to establish an initial classification model based on SVM; S4-2, using the real-time transmission data input of the digital wireless audio signal to obtain an initial data output result based on an initial classification model; S4-3, determine whether the initial data output result corresponds to the verification set, if so, execute S4-4, otherwise, use the initial output result as the updated training set and return to S4-1; S4-4, obtaining data characteristics of real-time transmission data of digital wireless audio signals; S4-5, comparing the data features of the real-time transmission of the digital wireless audio signal with the noise feature database to obtain denoising data features of the corresponding digital wireless audio signal; S4-6, taking the output result of the initial data as input, taking the denoised data of the digital wireless audio signal corresponding to the denoised data feature of the digital wireless audio signal as output, and establishing a noise reduction training model based on LSTM; S4-7, obtaining the initial feature output result of the noise reduction training model, determining whether the initial feature output result corresponds to the denoising data of the digital wireless audio signal, if so, executing S4-8, otherwise, using the data feature of the digital wireless audio data as input, and returning to S4-6; S4-8, respectively obtaining denoising data of the digital wireless audio signal at time t and time t+1 and inputting them into the denoising training model to obtain corresponding model output results; S4-9. Determine whether the change trend of the model output result corresponding to time t is consistent with that of the model output result at time t+1. If so, output the initial training model as a noise reduction optimization function model of the digital wireless audio signal. Otherwise, obtain the outliers with inconsistent change trends as the updated training set, and return to S4-1.

10. The digital wireless audio signal noise reduction optimization method based on Matlab as claimed in claim 9, characterized in that: The method of obtaining the digital wireless audio signal noise reduction optimization result by using the digital wireless audio signal noise reduction model includes: S5-1, using the noise reduction model of the digital wireless audio signal to obtain a real-time output result of noise reduction data corresponding to the digital wireless audio signal; S5-2, obtaining channel data corresponding to the real-time transmission of the digital wireless audio signal according to the real-time output result of the digital wireless audio signal noise reduction data; S5-3, obtaining multi-channel data corresponding to the real-time transmission of digital wireless audio signal noise reduction data according to the channel data transmitted in real time by the digital wireless audio signal; S5-4, obtaining corresponding first channel output data and second channel output data according to the multi-channel data transmitted in real time by the digital wireless audio signal noise reduction data; S5-5, determining whether the first channel output data and the second channel output data are synchronized, if so, outputting the first channel output data and the second channel output data as the initial noise reduction result of the digital wireless audio signal, and directly executing S5-7, otherwise, executing S5-6; S5-6, determining whether there is a delay relationship between the second channel output data and the first channel output data, if so, using the second channel output data and the first channel output data as an updated training set, and returning to S4-1, otherwise, using the first channel output data and the second channel output data as the initial noise reduction result of the digital wireless audio signal, and executing S5-7; S5-7, obtaining a corresponding signal-to-noise ratio according to an initial noise reduction result of the digital wireless audio signal; S5-8. Determine whether the signal-to-noise ratio is lower than the standard signal-to-noise ratio of the historical noise reduction result of the corresponding digital wireless audio signal. If so, output the initial noise reduction result of the digital wireless audio signal as the noise reduction optimization result of the digital wireless audio signal. Otherwise, obtain multi-channel data of the real-time transmission of the digital wireless audio signal noise reduction data corresponding to the initial noise reduction result.

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