28 results about "Normalized correlation" patented technology

The invention relates to the technical field of digital filters, and discloses a quantization sensing wide linear minimum error mode adaptive filter, which performs non-uniform low-bit quantization on an input signal and an expected signal by using a quantization parameter to obtain a corresponding quantization value; constructing a linear factor based on the quantization parameter; based on the non-roundness of the input signal, constructing a normalized correlation matrix of the input signal and the linearized error signal, and constructing a compensation matrix in combination with a linear factor; obtaining input signal quantized values at a current moment and a historical moment, constructing an augmented input signal vector, calculating a product of the augmented input signal vector and the compensation matrix, and constructing a corrected input vector; performing wide linear filtering on the corrected input vector to obtain an output signal, and calculating an error signal in combination with an expected signal quantized value; and updating the weight vector at the next moment by using the corrected input vector and the error signal. According to the invention, by introducing a non-uniform low-bit quantization and deviation compensation mechanism, the cost and energy consumption of the analog-to-digital converter are remarkably reduced, and a relatively low steady-state error is kept.

The invention relates to the technical field of edge-end collaboration, and discloses an edge-end collaboration AI model construction system and method for energy consumption prediction, and the method comprises the steps: collecting node parameters of edge nodes according to a fixed time interval in a preset time period, and obtaining a parameter matrix; calculating a sample covariance based on the parameter matrix, and executing strip projection to obtain a projection matrix; respectively constructing a variance matrix and a correlation matrix by using the projection matrix; constructing a power grid sparse matrix according to the sensor topology; splicing the power grid sparse matrix and the correlation matrix to form a normalized correlation matrix, and generating a multi-layer covariance matrix in combination with the variance matrix; performing positive definite processing on the multi-layer covariance matrix to obtain a positive definite covariance matrix; and whitening the parameter matrix by using the positive definite covariance matrix to obtain a whitened parameter matrix.

A method includes obtaining a first image of a scene using a first image sensor of an electronic device, and obtaining a second image of the scene using a second image sensor of the electronic device. The method also includes generating a first feature map from the first image and generating a second feature map from the second image. The method also includes generating a third feature map based on the first feature map, the second feature map, and an asymmetric search window. The method also includes generating a depth map by restoring spatial resolution of the third feature map.

The present disclosure provides a method, apparatus, device and storage medium for determining resource element group bundling information, relating to the technical field of wireless communication networks, including obtaining a target demodulation reference signal sequence; respectively performing correlation calculations on the local demodulation reference signal sequence and the target demodulation reference signal sequence according to each interleaving parameter in a preset set of interleaving parameters to obtain a set of normalized correlation values; according to a preset set of offset positions, performing combined calculation on the normalized values in the set of normalized correlation values to obtain a set of combined correlation values corresponding to each interleaving parameter at each aggregation level in a preset set of aggregation levels; calculating the peak-to-average ratio of the set of combined correlation values; when the peak-to-average ratio meets a preset threshold value, determining the numbering information of the resource element group bundling corresponding to the corresponding aggregation level and interleaving parameter according to the set of combined correlation values. The embodiments of the present disclosure can determine the numbering information of the resource element group bundling when the resource set is unknown under the condition of CCE interleaving.

A plurality of shift images are generated by shifting a fluoroscopic image by a prescribed increment within a prescribed range in a craniocaudal direction. Then, a normalized correlation coefficient between a DRR image and each of the plurality of shift images is calculated. Next, a shift amount of the shift image corresponding to the largest normalized correlation coefficient among the plurality of normalized correlation coefficients is determined to be the positional deviation.

The present application belongs to the technical field of integrated circuit design, and also relates to the field of digital signal processing, in particular to an amplitude modulation baseband signal processing and identification method and device, which are used to solve the problem of digital signal identification of amplitude modulation transmission. The processing process includes: quadrature signal equalization, quadrature signal merging, normalized correlation detection, signal peak value search, signal strength screening, and signal decision. The method and device can process the baseband signal converted from analog-digital after being demodulated by the radio frequency analog circuit in the radio equipment, and finally identify the digital coding content of the amplitude modulation signal. It is mainly applied to amplitude modulation radio equipment and near field communication field, and is responsible for the decoding of digital signal. Through this method and device, the coding content can be efficiently and accurately identified; it has strong anti-interference ability and anti-signal distortion ability; it has sensitive identification ability for small signals and certain signal-to-noise ratio gain for low-speed signals.

The invention relates to a synchronous and asynchronous GNSS (Global Navigation Satellite System) signal coherent integral gain mechanism analysis method. The method comprises the following steps: for a synchronous signal generation scene, generating a local copy enabling the total correlation energy to be maximum; coherent integral output is calculated according to a local copy and an intermediate frequency signal, a pseudo-random code normalization correlation function and residual frequency difference simplification are introduced, after an output signal is obtained, an output signal-to-noise ratio is calculated in combination with preset noise power, and a conclusion that the synchronous scene output signal-to-noise ratio is linearly proportional to coherent integral time is deduced. The method comprises the following steps: respectively generating independent local copies for a real signal and a plurality of forwarded signals according to an asynchronous signal forwarding scene; and calculating a correlation integral of conjugation of the local copy and the mixed input signal, simplifying an integral result, deducing an asynchronous scene output signal-to-noise ratio expression, and obtaining a conclusion that the asynchronous scene output signal-to-noise ratio expression is in direct proportion to the input signal-to-noise ratio and coherent integral time. By adopting the method, a theoretical support can be provided for the optimization design of the capturing and tracking link of the GNSS array receiver.

The present application discloses a method, device and equipment for crop change detection, which relates to the technical field of crop detection. By using the normalized correlation between co-polarization channels of crops to eliminate the intensity information of co-polarization channels, the true changes during the growth process of crops can be captured more accurately. The method includes: after acquiring co-polarization synthetic aperture radar data, constructing a polarization covariance matrix according to the image data of crops on co-polarization channels; calculating the normalized correlation between co-polarization channels of crops according to the polarization covariance matrix; calculating the polarization correlation distance between different time points of crops according to the normalized correlation between co-polarization channels of crops; and determining the first change amount feature during the growth process of crops according to the polarization correlation distance between different time points of crops, where the first change amount feature at least includes the change amplitude of the growth process of crops.

The present invention discloses a time-varying environment perception video analysis task offloading method based on regions of interest, including: after capturing video data and obtaining video frames, generating an initial bounding box through an edge server model, and a local terminal decision module determining the packaging size and offloading threshold of the regions of interest, obtaining the regions of interest and their cumulative offsets and normalized correlation values based on the initial bounding box, and determining whether to offload the regions of interest to the edge server based on the offloading threshold and combining and packaging the regions of interest to be offloaded, so as to realize the real-time processing of high-definition video stream data with small targets; the advantages of the present invention are: combining the heterogeneity of terminal-edge resources, analyzing the dependence relationship between the environment and system performance, and having better analysis performance for high-definition videos containing small targets.

Online prediction method and system for coal ash generation amount of power station boilers based on LSTM. The method includes collecting historical data of coal ash generation amount of boilers and main influencing parameters to obtain correlation relation data and performing normalization processing; dividing the normalized correlation relation data into a training set and a test set; using the data in the training set to train and fit a pre-established LSTM network model for coal ash generation amount of boilers; combining the prediction data with the data in the test set to perform overfitting evaluation on the trained and fitted LSTM network model for coal ash generation amount of boilers; online sampling currently occurred data and inputting it into the LSTM network model for coal ash generation amount of boilers without overfitting evaluation to predict the coal ash generation amount value at future times. The present invention can record required data for a long time and can perform online prediction, with a long prediction period and high accuracy, meeting the requirements of power generation enterprises for dynamic prediction of coal ash generation amount of boilers.

The application discloses a method for quickly calculating image correlation, and relates to the technical field of image matching, which comprises the following steps: S1, acquiring a template feature map from a template image and a search feature map from a search image based on a feature extraction network; S2, setting a sliding window, traversing and extracting the search feature map through the sliding window, and extracting a first feature vector; S3, performing cross-correlation operation on the template feature map and the search feature map to obtain a calculation result; S4, performing dimension transformation based on the calculation result obtained in the step S3 to obtain a matching cross-correlation map; and S5, obtaining the position with the maximum correlation of the sliding window based on the position index of the maximum value in the matching cross-correlation map. According to the application, the normalized correlation of each position of a template to be matched on a search image is calculated, the cross-correlation map can be obtained only once, the time for obtaining the cross-correlation map is reduced, and the position of a target can be quickly located in a scene requiring target positioning.

The invention discloses a multipath signal detection method based on correlator signal output and RGB color space combination, and the method comprises the steps: obtaining a plurality of normalized correlation value distribution characteristics and corresponding correlation value vectors according to a normalized correlation value function of a single branch through constructing a correlator output model containing a plurality of correlators and a plurality of signals; and constructing a three-dimensional Gaussian distribution model to generate Gaussian distribution function characteristics of RGB colors, comparing signal correlation values with the Gaussian distribution function characteristics of corresponding channels, and judging whether correlation value distribution is abnormal or not based on a detection threshold value so as to realize detection of multipath signals. According to the invention, through combination of feature distribution of output signals of different types of signal correlators and RGB color space, visual and rapid detection and discrimination of multipath signals are realized on a correlation domain level.

The invention discloses a method for quickly calculating image correlation, and relates to the technical field of image matching, and the method comprises the steps: S1, based on a feature extraction network, obtaining a template feature map from a template image, and obtaining a search feature map from a search image; s2, setting a sliding window, traversing and extracting the search feature map through the sliding window, and extracting a first feature vector; s3, performing cross-correlation operation on the template feature map and the search feature map to obtain a calculation result; s4, performing dimension transformation based on a calculation result obtained in the step S3 to obtain a matched cross-correlation graph; and S5, based on the position index of the maximum value in the matched cross-correlation graph, obtaining the position with the maximum correlation of the sliding window. According to the method, the normalized correlation of each position of the to-be-matched template on the search image is calculated, and the cross-correlation graph can be obtained only through one-time calculation, so that the time for obtaining the cross-correlation graph is shortened, and the position of the target can be quickly positioned in a scene in which the target needs to be positioned.

This invention discloses a machine vision-based method for detecting blockages in coal preparation plant screening tanks, belonging to the field of industrial automation detection technology. The method includes: acquiring continuous video frames; the user defining an irregular polygonal monitoring area and generating a mask; dividing the video frames into equally spaced blocks; performing normalized correlation template matching on each block within the monitoring area using adjacent frames, recording the positional deviation; marking blocks with deviations close to 0 in multiple consecutive frames as continuously stationary blocks; and determining blockage and triggering an alarm when the number of stationary blocks is greater than a threshold. This invention improves robustness to changes in illumination by utilizing normalized correlation matching, effectively filters out instantaneous misjudgments through continuous frame stationary detection and an accumulator mechanism, and solves the problem of water flow interference by combining edge detection preprocessing, thus achieving automatic and accurate detection of blockages in coal preparation plant screening tanks and ensuring production safety.

The present invention belongs to the technical field of image processing, and discloses a method, a system and a device for locating all the spotting points of a microfluidic biochip. The method includes: acquiring the grayscale source image after spotting on the biochip, storing it in a specified directory on the disk, loading it into the memory for subsequent processing, obtaining a first processed image with the spotting area of the magnetic head separated from the circuit background, and generating a template grayscale image; performing template matching on the first processed image by using the normalized correlation matching method to obtain a result matrix dstmat; then through multi-target positioning processing, obtaining the positions of the centers of each magnetic head, and recording them in a list or an array; circularly acquiring the coordinates of the centers of each magnetic head in the list or the array, judging whether there are abnormal coordinate points, and determining whether the chip performs subsequent defect detection. The present invention can perform subsequent defect detection on the microfluidic biochip faster and more accurately, and provides an effective method for realizing the automatic detection of the quality of the spotting chip.

The present invention relates to the technical field of medical image transmission methods, and more specifically, to a medical image transmission method and system based on big data, comprising the following steps: obtaining a fragment sequence; obtaining an initial correlation matrix based on the distribution density gradient of each two adjacent fragments; obtaining a normalized correlation matrix; generating an increasing weight matrix through multi-level projection aggregation to obtain increasing weights for each pair of fragments; based on the increasing weight matrix, applying a differential adaptive filtering method to obtain a differential optimization matrix; based on the differential optimization matrix, applying a power-law distribution model to generate a final allocation matrix to obtain the transmission priority of each fragment; determining the transmission order of the fragments based on the final allocation matrix to achieve orderly transmission of medical image data, and based on the density changes of data information within the fragments, being able to quickly identify areas containing key diagnostic information and assign them a higher priority, thereby giving priority to important data during data transmission.

This invention relates to the field of motor control technology and discloses an optimal dynamic response deadbeat current prediction system for permanent magnet synchronous motors. The system performs the following steps: acquiring motor operating status data and historical sequence data; calculating the error phase trajectory and detecting periodic disturbance patterns through cross-mechanical cycle normalized correlation analysis; extracting historical feedforward compensation voltage vectors and calculating the net available voltage amplitude under the periodic disturbance pattern; calculating the upper limit of the current change rate based on the net available voltage amplitude and planning the optimal intermediate current trajectory; performing two-step deadbeat current prediction calculations to calculate the nominal voltage vector; synthesizing the voltage vector and performing constraint verification; outputting voltage commands and updating the angle index memory table.

The invention discloses an industry business and remote sensing technology correlation degree quantitative evaluation and grading method and device, and belongs to the field of remote sensing technology application and remote sensing information management, and the method comprises the steps: carrying out the sorting and gathering of industry business types, and extracting keywords corresponding to different business types; remote sensing technology carding and gathering are carried out, and keywords corresponding to different remote sensing technologies are extracted; literature retrieval is carried out in a paper database by means of the keywords, each literature is classified, and the literature number and the literature publishing time span are counted; calculating the integration level of the remote sensing technology in the industry business; calculating the support degree of the remote sensing technology to the industry business; the industry business and the remote sensing technology are used as nodes, a relation network is constructed, and the node weighting centrality of the network is calculated; calculating the normalized correlation degree of the industry business and the remote sensing technology; and grading based on the normalized correlation degree. The method can quantitatively analyze the use degree of the remote sensing technology in industry business application.

This application relates to a method for analyzing the coherent integration gain mechanism of synchronous and asynchronous GNSS signals. The method includes: for synchronous signal generation scenarios, generating a local copy that maximizes the total correlation energy; calculating the coherent integration output based on the local copy and the intermediate frequency signal; introducing a pseudo-random code to normalize the correlation function and simplifying with residual frequency difference; obtaining the output signal; and then calculating the output signal-to-noise ratio (SNR) by combining it with a preset noise power, thus deriving the conclusion that the output SNR in synchronous scenarios is linearly proportional to the coherent integration time. For asynchronous signal relay scenarios, generating independent local copies for the real signal and multiple relayed signals respectively; calculating the conjugate correlation integral of the local copy and the mixed input signal and simplifying the integration result, deriving the expression for the output SNR in asynchronous scenarios, and concluding that it is proportional to the input SNR and the coherent integration time. This method can provide theoretical support for the optimized design of the acquisition and tracking link in GNSS array receivers.

This invention relates to the field of digital filter technology and discloses a quantization-aware wide-linearity minimum error modulus adaptive filter. It utilizes quantization parameters to perform non-uniform low-bit quantization on the input signal and the desired signal to obtain the corresponding quantized values; a linearity factor is constructed based on the quantization parameters; a normalized correlation matrix between the input signal and the linearized error signal is constructed based on the non-circularity of the input signal, and a compensation matrix is ​​constructed in conjunction with the linearity factor; the quantized values ​​of the input signal at the current and historical times are obtained to construct an augmented input signal vector, and its product with the compensation matrix is ​​calculated to construct a corrected input vector; wide-linearity filtering is performed on the corrected input vector to obtain the output signal, and the error signal is calculated in conjunction with the quantized value of the desired signal; the weight vector at the next time step is updated using the corrected input vector and the error signal. This invention significantly reduces the cost and energy consumption of the analog-to-digital converter by introducing non-uniform low-bit quantization and a bias compensation mechanism, while maintaining a low steady-state error.

The present application belongs to the technical field of photovoltaic power generation operation evaluation, and discloses a photovoltaic power generation efficiency analysis and evaluation method. The method obtains multi-source operation data of a photovoltaic power generation station to be evaluated and carries out normalized correlation to obtain an evaluation basic record set; sequentially carries out evaluation object merging, evaluation window screening, dynamic irradiation calibration and power generation capacity correction to obtain a dynamic benchmark evaluation record set; then quantifies efficiency influence characteristic quantities of the dynamic benchmark evaluation record set to obtain an efficiency influence evaluation record set; and takes the dynamic benchmark power generation capacity as an evaluation benchmark to carry out loss attribution decomposition on a measured power generation deviation to obtain a multi-factor efficiency evaluation result. The present application can perform itemized characterization on limited power generation, peak clipping, wave posture, back gain, pollution shielding and residual deviation candidates.

The application discloses a local minimum spanning tree path planning method supporting global coordinate updating, and belongs to the field of image processing. The method comprises the following steps: grouping collected images according to an XY space coordinate system and an adjacency relation, calculating relative offset distances among the images and a normalized correlation index; confirming a starting group and a starting image of the starting group, constructing a minimum spanning tree by using a minimum spanning tree algorithm, and calculating global coordinates of the images in the starting group; in a current group and an adjacent group in which global coordinates have been solved, finding an image pair having a spatial adjacency relation with the images in the current group, determining a reference image and a starting image of the current group, calculating the global coordinates of the starting image of the current group, updating the global coordinates of the remaining adjacent images in the current group, and calculating the global coordinates of the remaining images in the current group along the minimum spanning tree; and images in the remaining groups are processed in the same way until the global coordinates of all the images in the groups are calculated, and a path planning graph is obtained. The application improves the image splicing precision and efficiency.

The application relates to the technical field of motor control, and discloses an optimal dynamic response deadbeat current prediction system for a permanent magnet synchronous motor, which executes the following steps: obtaining motor operation state data and historical sequence data; calculating error phase trajectories and detecting periodic disturbance modes through cross-mechanical cycle normalization correlation analysis; extracting historical feedforward compensation voltage vectors under the periodic disturbance modes and calculating net available voltage amplitudes; calculating the upper limit of a current change rate based on the net available voltage amplitudes and planning an optimal intermediate current trajectory; executing two-step deadbeat current prediction operation to calculate a nominal voltage vector; synthesizing the voltage vector and executing constraint verification; outputting a voltage instruction and updating an angle index memory table.

The invention discloses a local minimum spanning tree path planning method supporting global coordinate updating, which belongs to the field of image processing, and comprises the following steps: grouping acquired images according to an XY space coordinate system and an adjacency relation, and calculating a relative offset distance and a normalized correlation index between the images; determining a starting group and a starting group starting image, constructing a minimum spanning tree by adopting a minimum spanning tree algorithm, and calculating global coordinates of images in the starting group; searching an image pair having a spatial adjacency relation with the images in the current group in the current group and the adjacent group after global coordinate solving, determining a reference image and a current group initial image, calculating the global coordinate of the current group initial image, updating the global coordinates of the remaining adjacent images in the current group, and obtaining a current group image; calculating global coordinates of residual images in the current group along the minimum spanning tree; and similarly processing the images of the remaining groups until the global coordinates of the images in all the groups are calculated, and obtaining a path planning graph. According to the invention, the image splicing precision and efficiency are improved.

The application relates to an improved template matching-based target tracking algorithm implementation method, which solves the problems of time consumption, instability, surrounding similar target interference and the like of a traditional template matching algorithm by improving a template creation strategy, reading original image data to create a template, and the like; when searching for each frame, a scale factor is introduced to match with a current scale image and a predicted scale image, a region block with an equal size to the template is taken out from each pixel point in a search range as a center to carry out normalized correlation operation with the template, a target point position in the current scale and the predicted next scale image is obtained, a latest scale factor is obtained by judging a confidence degree, and the problem of tracking drift of the traditional template matching algorithm is solved; the application improves the applicability of the traditional template matching algorithm, considers tracking speed and precision, has small and fixed algorithm calculation amount, has low requirement on an embedded platform, and has a good application prospect.

The invention provides a meteorological knowledge question answering method and system, and the method comprises the following steps: a data preprocessing step, an index construction step, an initial retrieval step, a reordering step, a dynamic fusion weighting step and an answer generation step, the candidate content corresponding to each candidate index in the preliminary candidate index set obtained in the initial retrieval step is input into a pre-trained multi-modal reordering model, the correlation score of each candidate content relative to the query problem is obtained, and normalization processing and ordering are conducted on the scores; in the dynamic fusion weighting step, a text modal weight and an image modal weight of a modal layer are calculated based on a normalized reordering score, the weight of the modal layer obtained through fusion calculation, a preset index layer weight and a normalized correlation score are fused, and a final comprehensive score of each candidate content is calculated. And screening out a plurality of candidate contents with high comprehensive scores according to the scores. The meteorological knowledge question-answering method and system have good accuracy, specialty and usability.

This invention provides a method, apparatus, device, and medium for data link signal synchronization and rate identification, relating to the field of communications. The method includes: acquiring a complex baseband signal of a data link signal; generating first and second complex signal templates corresponding to first and second frame lengths, each containing a carrier with a synchronization tone frequency and a phase transition at the boundary of each frame; performing sliding correlation processing on the complex baseband signal and the first and second complex signal templates respectively, and normalizing the correlation results to obtain first and second normalized correlation curves; performing peak search on the first and second normalized correlation curves respectively, and performing cross-curve matching to determine burst synchronization points; comparing the peak scores of the two normalized correlation curves at the burst synchronization points to determine the burst rate pattern. This invention enables robust burst detection, automatic rate pattern identification, and frame synchronization of data link signals under low signal-to-noise ratio, frequency offset, and interference environments.

The application discloses an industry business and remote sensing technology correlation degree quantitative evaluation and grading method and device, belongs to the field of remote sensing technology application and remote sensing information management, and comprises the following steps: carrying out industry business type analysis and collection, refining keywords corresponding to different business types; carrying out remote sensing technology analysis and collection, refining keywords corresponding to different remote sensing technologies; carrying out literature retrieval in a paper database with the aid of the keywords, classifying each paper, and counting the number of papers and the time span of paper publication; calculating the integration degree of remote sensing technology in the industry business; calculating the support degree of remote sensing technology to the industry business; taking the industry business and the remote sensing technology as nodes, constructing a relationship network and calculating the node weighted degree centrality of the network; calculating the normalized correlation degree of the industry business and the remote sensing technology; and grading based on the normalized correlation degree. The application can quantitatively analyze the use degree of remote sensing technology in the industry business application.