46 results about "Orthogonal matrix" patented technology

The invention discloses a crack sub-pixel precision edge detection method based on an improved Canny operator. The crack sub-pixel precision edge detection method comprises the steps of obtaining a crack image corresponding to a structural body surface crack; the crack image is preprocessed; carrying out gradient calculation on the preprocessed crack image through an improved Sobel operator to obtain a gradient image containing a gradient magnitude and a gradient direction; performing non-maximum suppression on the gradient image, adaptively obtaining an optimal threshold by adopting an improved maximum between-class variance method, judging a crack edge according to the optimal threshold, and further obtaining a coarse edge pixel-level image; processing edge information in the coarse edge pixel-level image by using a Zernike orthogonal moment to obtain coordinates of sub-pixel edge points; and connecting all the sub-pixel edge points, and outputting a crack detection result image. On the basis, the crack edge detection precision is improved to a sub-pixel level.

The invention discloses a direction consistency constraint-based adaptive image classification method during testing. The method comprises the following steps of: 1, constructing an image classification training data set and preprocessing the image classification training data set; 2, constructing a classification model and completing pre-training; 3, decomposing the weight of each linear layer in the pre-training model to obtain a modulus length matrix and a unit direction matrix, and introducing an orthogonal matrix to construct an effective weight structure for updating in a test stage; and 4, in a test stage, calculating the difference between the model output features and the source domain features in terms of statistics, constructing a loss function with statistics alignment as a target, and on the premise of keeping the unit direction matrix unchanged, updating the modulus length matrix and the orthogonal matrix to realize adaptive adjustment of the image classification model during test. According to the method, the problem of performance degradation caused by input distribution change is effectively relieved, and the classification precision of an image classification model under a complex disturbance condition is remarkably improved.

The invention discloses a joint sorting QR decomposition method and related device for multi-antenna detection, and belongs to the technical field of multi-input multi-output signal detection, and the method comprises the steps: initializing an orthogonal matrix and an upper triangular matrix; acquiring a channel matrix H; extracting candidate columns from residual columns in the channel matrix H based on the sum of residual energy and self energy joint weighting, updating an orthogonal matrix and an upper triangular matrix according to the candidate columns until all columns in the channel matrix H are traversed, and obtaining a final orthogonal matrix and a final upper triangular matrix; and taking the final orthogonal matrix and the upper triangular matrix as a joint sorting QR decomposition result for multi-antenna detection, the method and the related device can shear out the nodes with the super radius as early as possible, reduce access nodes, and improve the speed of multi-antenna detection while ensuring the detection performance.

Certain examples of the present disclosure relate to an apparatus (10, 120) comprising: means (11, 15) for sending, to one or more User Equipment, UE (110), demodulation reference signal, DMRS, matrix information (401) indicative of a row-orthogonal DMRS matrix (P); means (11, 15) for sending, to a UE (UEi) of the one or more UE, DMRS submatrix information (402) indicative of a submatrix (Pi) of the row-orthogonal DMRS matrix that has been assigned to the UE; means (11, 15) for receiving, from the UE, said at least one DMRS determined by the UE based, at least in part, on the DMRS matrix information and the DMRS submatrix information.

This invention discloses a multi-harmonic source responsibility quantification method based on asynchronous measurement, relating to the field of power quality harmonic technology. The method includes measuring the harmonic voltage of the bus of interest and the harmonic current at the connection point between each harmonic source and the bus of interest to construct the observed signal. After centering and whitening, a covariance matrix is ​​constructed. For the covariance matrix, the optimal common orthogonal matrix is ​​determined, and the source signal matrix is ​​reconstructed. The harmonic transfer impedance corresponding to each harmonic source signal is calculated based on a fast-changing component model. Each harmonic source signal is multiplied by its corresponding harmonic transfer impedance to obtain the harmonic voltage of the corresponding harmonic source. The harmonic voltage is projected onto the harmonic voltage of the bus of interest to achieve multi-harmonic source responsibility quantification. This method does not rely on GPS, simplifying the operation steps of multi-harmonic source responsibility quantification and helping to improve quantization efficiency. Simultaneously, the sparsity of the hybrid matrix reduces the computational dimensionality, alleviating the computational burden and improving quantization accuracy.

This invention relates to the field of natural language processing technology and discloses a multilingual word vector weighted alignment method based on orthogonal Protodyakonov analysis. The method includes the following steps: S1: Randomly initialize an orthogonal matrix R, and randomly rotate the Chinese word vectors, i.e., X < -XR; substitute the weight matrix A, calculate the weighted orthogonal transformation matrix W according to the provided weighted Protodyakonov analysis, and obtain the weighted aligned Chinese word vector XW2. The Chinese word vectors are downloaded through a given word vector link to obtain Chinese and English word vectors X and Y. A given alignment dictionary L is used to weight sentiment words, with the goal of weighted alignment from X to Y. The method provided by this invention can perform weighted alignment according to the needs of downstream tasks, further improving the performance of downstream tasks, realizing a shared word vector space, and providing a mathematical proof of the weighted orthogonal Protodyakonov analysis.

The present disclosure relates to methods and devices (including apparatuses, such as UEs and / or base stations) for wireless communication. The apparatus can select one or more rows or one or more columns of a DFT matrix, the one or more rows being even rows in the DFT matrix and the one or more columns being even columns in the DFT matrix. The apparatus can also determine an orthogonal matrix based on the one or more rows or the one or more columns of the DFT matrix, the orthogonal matrix having a size of (MxN)x(MxN) with MxN rows and MxN columns. Additionally, the apparatus can determine a codebook based on the orthogonal matrix, the codebook including a plurality of codepoints. The apparatus can also transmit at least one signal including a first codepoint of the plurality of codepoints in the codebook in an uplink resource.

An operating method of a first device which communicates with a second device based on time division duplex (TDD), includes: receiving a first signal from the second device; estimating a channel between the first device and the second device based on the first signal; generating, by applying singular value decomposition (SVD) to the estimated channel, a first orthogonal matrix including one or more left singular vectors, a diagonal matrix including one or more singular values, and a second orthogonal matrix including one or more right singular vectors; selecting at least one right singular vector from the second orthogonal matrix in descending order according to the one or more singular values, a number of the selected at least one right singular vector corresponding to a number of ranks of the channel; and transmitting, to the second device, a precoded physical sidelink shared channel (PSSCH) precoded based on a precoding matrix including the selected at least one right singular vector.

A data multi-protection method relates to the technical field of information security, solves the problems that a traditional encrypted image is easy to be visually identified and pointedly cracked, and a traditional steganography method is insufficient in security and steganography capacity, and comprises the following steps: reading privacy data and a carrier image, and respectively converting the privacy data and the carrier image into two-dimensional matrixes; a carrier image hash value is obtained through an SHA-256 algorithm, a one-dimensional chaotic system is constructed to generate a chaotic sequence, and three sequences are obtained through a mod function limitation range; a final encrypted image is obtained through chaotic sequence scrambling of privacy data, orthogonal moment transformation of a carrier image, data embedding and reverse transformation reconstruction in sequence and through secondary scrambling and diffusion operation. According to the scheme, the algorithm complexity is increased, and the privacy data protection security is improved.

The present application relates to a double-ended DC power transmission fault location method, system, storage medium and computer, the method first uses the energy structure characteristics of current signal to construct high sensitivity starting criterion, accurately records the fault time. Secondly, based on the voltage and current data before and after the fault time, the first modal counter-traveling voltage wave is extracted, and the method of Laguerre orthogonal matrix fitting combined with Hilbert transform is used for accurate denoising, and the noise interference is effectively filtered out. Then, the Bergeron time domain equivalent model of the double-ended DC power transmission system containing frequency variable loss is constructed, the denoised counter-traveling voltage wave is taken as the excitation, and the time domain fault voltage signal is solved. Finally, based on the fault voltage signal, the weighted energy density spatial distribution function is constructed, and the two-stage iterative search strategy is adopted to accurately locate the fault point. The present application has strong anti-interference ability, high location accuracy, and is not affected by the transition resistance.

This invention belongs to the field of blind source separation. First, the observed graph signal is preprocessed to obtain a whitened graph signal, and a graph learning iterative model and graph adjacency matrix are initialized. A multi-objective function incorporating graph topology and temporal correlation is constructed, forming a multi-objective optimization problem. The multi-objective iterative model is then entered, and a fitness function is constructed to calculate the fitness of quantum PID individuals, determining the non-dominated solution set and the global optimal solution. The quantum rotation angle and quantum position are updated based on the global optimal solution. The iteration continues until convergence, outputting the non-dominated solution set and its corresponding orthogonal matrix set, generating multiple signal separation schemes. A set of separated graph signals is selected, and the graph adjacency matrix is ​​updated using the alternating direction multiplier method. The graph learning and multi-objective optimization process is iteratively executed until convergence, outputting the separated signals and the adjacency matrices of multiple graphs. This invention can improve the separation accuracy in multi-Gaussian source mixed scenarios and provides multiple separation schemes for selection.

The invention discloses a low-complexity signal detection method and device, and relates to the technical field of wireless communication. The method comprises the following steps: acquiring a received signal and a channel matrix; obtaining a constellation point set according to the received signal and a preset modulation mode parameter; layering the constellation point set based on a preset sphere center coordinate and an equal point layering number; performing QR decomposition on the channel matrix to obtain an upper triangular matrix, a first division orthogonal matrix and a second division orthogonal matrix; based on the upper triangular matrix, the first division orthogonal matrix and the second division orthogonal matrix, according to the layered constellation point set, using an SD detection algorithm to perform local search on each layer of constellation points to obtain a local optimal estimation signal set; and performing global optimal screening on the local optimal estimation signal set based on the layered region radius set to obtain a global optimal estimation signal. The invention provides an efficient and accurate low-complexity signal detection method based on an ML detection algorithm.

A method of determining N×m touch signals for a touch sensor including N×m touch transmission electrodes includes generating an orthogonal matrix including N orthogonal codes, determining a first phase shift matrix for N first frequency touch signals such that a sum signal of the N first frequency touch signals having a first frequency has equal power in N / m code symbols among N code symbols and is canceled out in remaining (N−N / m) code symbols among the N code symbols, determining the first frequency touch signals by applying the first phase shift matrix to the orthogonal codes, determining a k-th phase shift matrix for N k-th frequency touch signals having a k-th frequency by shifting the first phase shift matrix, and determining the k-th frequency touch signals by applying the k-th phase shift matrix to the orthogonal codes.

The invention discloses a geological disaster risk assessment system based on cloud computing, which relates to the technical field of geological information processing and comprises a data processing module, a feature extraction module, an intelligent decision module and a scheme decision module. The method comprises the following steps: firstly, acquiring geological disaster monitoring data and performing data block coding processing to obtain a historical disaster sequence matrix and a regional space feature matrix, then constructing a parameterized unitary orthogonal matrix, and performing orthogonal coding and reversible compression on a historical disaster sequence to obtain a first disaster matrix; performing disaster occurrence probability calculation on the first disaster matrix to obtain an exploration action, and optimizing the exploration action through a greedy strategy to generate an optimized monitoring sequence; structured analysis is carried out on an optimized monitoring sequence and a historical disaster sequence matrix through orthogonal inverse transformation, disaster monitoring point arrangement is obtained, self-adaptive improvement of exploration efficiency is achieved, and an intelligent exploration task which is continuously optimized and can be used for reference is formed.

The invention discloses a multi-harmonic source responsibility quantification method based on asynchronous measurement, and relates to the technical field of electric energy quality harmonics. The method comprises the following steps: measuring harmonic voltage of a concerned bus and harmonic current at a connection point of each harmonic source and the concerned bus to construct an observation signal, and constructing a covariance matrix after centralization and whitening: for the covariance matrix, determining an optimal common orthogonal matrix and reconstructing a source signal matrix; calculating harmonic transfer impedance corresponding to each harmonic source signal based on a fast-changing component model; multiplying each harmonic source signal by the corresponding harmonic transfer impedance to obtain a harmonic voltage of the corresponding harmonic source; and projecting the harmonic voltage to the harmonic voltage of the concerned bus to realize multi-harmonic source responsibility quantification. The method does not depend on a GPS, the operation steps of multi-harmonic source responsibility quantification are simplified, and the quantification efficiency can be improved; meanwhile, the calculation estimation dimension can be reduced through the sparsity of the hybrid matrix, the calculation burden is reduced, and the quantization precision is improved.

The invention discloses a clustering method based on a time sequence and a life cycle analysis method of a bearing. The clustering method in one embodiment comprises the following steps: respectively carrying out phase-space reconstruction on received operation data sequences of a plurality of devices and generating phase-space matrixes in one-to-one correspondence with the plurality of devices; decomposing each phase space matrix and generating an orthogonal matrix and a dynamic matrix; the orthogonal matrixes of all the operation data sequences are utilized to form a Stepepol manifold, the multiple devices are clustered according to the Stepepol manifold, and a first clustering result is generated; and based on the first clustering result, performing clustering in combination with the dynamic matrix of each operation data sequence, and generating a second clustering result of the plurality of devices. According to the embodiment provided by the invention, the phase-space matrixes are generated by performing phase-space reconstruction on the multiple pieces of equipment operation data based on the time sequence, and comprehensive clustering is performed by using the orthogonal matrixes and the dynamic matrixes obtained by decomposing the phase-space matrixes, so that the clustering accuracy is effectively improved.

The application discloses a rotating machinery state monitoring method based on performance degradation space fluctuation evaluation, and steps include: 1) collecting rotating machinery vibration data; 2) extracting multi-domain state features from the rotating machinery vibration data, thereby obtaining a multi-domain state feature matrix in the rotating machinery operation process; 3) optimizing the multi-domain state feature matrix by using an unconstrained orthogonal optimization method, thereby obtaining a multi-domain intrinsic state feature matrix Y in the rotating machinery operation process; 4) performing orthogonal matrix transformation on the multi-domain intrinsic state feature matrix Y, thereby constructing a rotating machinery performance degradation space; 5) calculating a rotating machinery state fluctuation rate based on the rotating machinery performance degradation space; and 6) analyzing the rotating machinery state fluctuation rate, thereby obtaining a rotating machinery equipment operation state. The application considers multi-domain intrinsic state features at adjacent time points, and both fault sensitivity and transient interference robustness are improved, and the application has good engineering application value.

The present application relates to a kind of radar anti-range deception jamming performance evaluation methods of multi-element combination selection optimization, comprising: step 1: according to the working parameter database of radar anti-jamming type, determine the multiple elements of radar anti-jamming performance evaluation and the value range of each element;Step 2: according to element and the value range of element, construct orthogonal matrix;Step 3: according to orthogonal matrix, radar anti-jamming test is carried out, and the influence degree of each element on radar anti-jamming performance is determined according to test result;Step 4: according to the influence degree of element on radar anti-jamming performance, the weight of element is determined, to realize the evaluation of radar anti-jamming performance according to the weight of element.The multi-element combination selection optimization radar anti-range deception jamming performance evaluation method of the present application, compared with prior art through expert experience to carry out subjective weight assignment, the evaluation of anti-jamming performance is more objective, so that anti-jamming performance evaluation result is closer to real situation.

The application discloses a data privacy protection method and device, equipment, medium and program product. The method comprises the following steps: obtaining a first data set obtained by adding differential privacy noise to an original data set collected by a smart meter; dividing the first data set into N groups; calculating the covariance matrix of each group; in the case of N>1, rotating the covariance matrix of each group to obtain an orthogonal matrix of each group; randomly exchanging the order of each matrix in the orthogonal matrix of each group to obtain a first matrix of each group; for each group, obtaining a third matrix of the group based on the first matrix and the second matrix of the group; and merging the third matrix of each group to obtain a target matrix, wherein the data in the target matrix is protected privacy protection data. In the process of transmitting the smart meter data collected by the smart grid to the server through the grid communication, the privacy and security of the transmitted data are ensured.

A vector retrieval method and apparatus, a medium, an electronic device and a program product. The method includes: acquiring a target vector to be retrieved and a target key; performing linear transformation on the target vector by using the target random number; performing a rotation operation on the target vector obtained after the linear transformation by using the target orthogonal matrix to obtain a first ciphertext vector; and sending the first ciphertext vector to a first server, so that the first server retrieves at least one second ciphertext vector that is similar to the first ciphertext vector from a knowledge vector base, ciphertext vectors in the knowledge vector base are generated based on the target key and a reference vector, and a generation manner of the ciphertext vectors is the same as a generation manner of the first ciphertext vector.

A physical layer protocol data unit (PPDU) transmission method is provided. The method includes generating a PPDU, where the PPDU includes an extremely high throughput-long training field (EHT-LTF). The EHT-LTF is obtained based on a P matrix and a predefined EHT-LTF sequence. The P matrix is an n×n orthogonal matrix, n is an integer greater than 8, and a first row of the P matrix includes at least one element whose value is 1 and at least one element whose value is −1. The method further includes sending the PPDU. This application may be applied to a wireless local area network (WLAN) system supporting a next-generation wireless fidelity (Wi-Fi) extremely high throughput (EHT) protocol of IEEE 802.11, for example, 802.11 protocols such as 802.11be.

This invention discloses a blind estimation method for frequency-hopping signal parameters based on atomic features. The method involves: first, windowing, compressed sampling, and atomic feature extraction of the frequency-hopping signal; then, roughly estimating the hopping time based on the distribution of atomic features within different windows; next, precisely estimating the hopping time, hopping period, and hopping speed using a block-diagonalized Fourier orthogonal matrix; and finally, estimating the frequency of each hop signal using an orthogonal matching pursuit algorithm, and obtaining the frequency-hopping pattern of the entire sample by concatenating each hop signal. This invention can adjust the search step size and compression ratio to change the computational complexity and estimation accuracy, adapting to different signal-to-noise ratio (SNR) environments. In high SNR environments, increasing the search step size and compression ratio effectively reduces computational complexity, while in low SNR environments, decreasing the search step size and compression ratio effectively improves estimation accuracy.

To provide an object identification device advantageous to the improvement of identification performance, miniaturization and cost reduction.SOLUTION: A plurality of light emitting elements configured to emit light having different center wavelengths in a predetermined direction, at least one light receiving element configured to generate a signal corresponding to intensity of light received from the predetermined direction, and a control unit configured to control a light emission timing of the plurality of light emitting elements and to extract a signal component having a wavelength corresponding to each of the plurality of light emitting elements from the signal, wherein an object existing in the predetermined direction is identified on the basis of a reflectance obtained from the signal component, the control unit includes a pulse modulation unit configured to execute ON / OFF of each of the plurality of light emitting elements simultaneously in parallel in a predetermined modulation pattern in synchronization with a predetermined frequency, and the modulation pattern is defined by an orthogonal matrix having an array of the plurality of light emitting elements as a row and an ON / OFF timing of each of the plurality of light emitting elements as a column.SELECTED DRAWING: Figure 1

Embodiments herein relate to a neural network compression technique in which a weight matrix within a neural network is transformed via matrix multiplication with an orthogonal matrix. The orthogonal matrix is derived from a calibration data set, which is generally selected to widely represent expected runtime input data, and the transformation causes the resulting modified weight matrix to have components ordered by relative importance. The modified weight matrix is incorporated into a compressed neural network with fewer weights. By removing one or more components of lower importance, the size of the neural network (and thus its storage and execution overhead) is reduced while still maintaining acceptable performance levels.

This invention discloses a multi-core computing method and apparatus for QR decomposition that integrates column-block TSQR and tile update. The method includes: for a large-scale matrix to be decomposed, horizontally dividing it into blocks based on the number of cores in the multi-core processor, and further dividing the large-scale matrix into multiple layers according to the tile update method; constructing a multi-stage pipeline with a binary tree structure, performing parallel triangular decomposition on the initial layers of the large-scale matrix through the multi-core processor to obtain the corresponding upper triangular matrix and orthogonal matrix; replacing the original layer block matrix with the upper triangular matrix, performing conjugate transpose on the orthogonal matrix to obtain the update matrix, and implementing parallel updates for the remaining layers through the multi-core processor; based on the reflection vector implicitly stored by the multi-core processor during the parallel triangular decomposition process, solving for the overall orthogonal matrix corresponding to the large-scale matrix, and simultaneously outputting the overall upper triangular matrix obtained after layer update. This invention can realize QR decomposition of large-scale matrices.

The invention discloses a method and a device for eliminating respiratory artifacts of uterine myoelectricity. The method comprises the following steps: S1, acquiring an abdominal multichannel signal and a respiratory rate RR to obtain a uterine myoelectricity original data sequence X; s2, subtracting the mean value from the original data sequence to obtain zero mean value data; s3, carrying out linear transformation on the zero mean value data; s4, solving zero-mean data after linear transformation to obtain an orthogonal matrix W by searching for a direction in which negentropy or kurtosis is approximately maximized; s5, constructing a two-dimensional comprehensive scoring function, and identifying a respiratory artifact vector VR; s6, calculating a projection component VRX of the respiratory artifact vector VR in the original hybrid matrix X, and removing the projection component from the original signal to obtain a signal matrix X'after preliminary removal of the respiratory artifacts; and S7, carrying out band-pass filtering on the signal matrix X'to obtain a pure uterine electromyographic signal with a high signal-to-noise ratio. The method can effectively eliminate the interference of the respiratory artifacts on the uterine myoelectricity signals, and improves the signal-to-noise ratio of the collected uterine myoelectricity.

The embodiment of the invention provides a matrix decomposition method and device based on a mercuric chloride chip, equipment and a storage medium. The method comprises the following steps: acquiring a to-be-decomposed original matrix; aiming at each column vector of the original matrix, performing projection processing on each column vector to obtain a middle orthogonal basis vector; performing iterative projection processing on the intermediate orthogonal basis vector to obtain a next intermediate orthogonal basis vector until the number of iterative projection times reaches a preset number of projection iterations, taking the next intermediate orthogonal basis vector obtained by the last iteration as an orthogonal basis vector of the corresponding column vector, and generating a corresponding coefficient vector according to the orthogonal basis vector; sequentially constructing an orthogonal matrix based on a plurality of orthogonal basis vectors corresponding to a plurality of column vectors contained in the original matrix, and constructing a coefficient matrix based on a plurality of corresponding coefficient vectors; and decomposing the original matrix based on the orthogonal matrix and the coefficient matrix to obtain a decomposition result corresponding to the original matrix. Therefore, the accuracy of matrix decomposition based on the mercuric chloride chip can be improved.

The application provides a kind of adaptive demodulation method of enhanced spatial modulation system, comprising: S1: receiving end obtains real-time channel matrix H and receiving signal y; using orthogonal matrix Q to the receiving signal y is carried out orthogonal transformation and obtains transformed receiving signal;S2: preset maximum reserved node number of each layer, initialize search layer;Generate the candidate symbol set of initial layer, and calculate the initial metric value corresponding to each candidate symbol;All initial metric values are screened, and the optimal initial metric value is reserved;S3: from the 2nd layer to layer, carry out iterative tree search layer by layer;S4: judge the layer number of current layer, and according to the judgment result, the candidate symbol and the corresponding cumulative metric value are reserved, and the reserved candidate symbol is stored in symbol vector;When the current layer is layer, symbol vector is used as the estimated value of transmitting vector x in enhanced spatial modulation system.

The present application belongs to the field of geotechnical engineering numerical analysis and ground treatment, and relates to a geopolymer composite foundation parameter optimization method based on finite element analysis. It comprises the following steps: step 1, initial mesh partitioning is performed on the calculation domain of the geopolymer mixing pile-soil composite foundation and recorded as a unified reference mesh, and the response field is mapped to the unified reference mesh to form a unified dimension response snapshot vector; step 2, singular value decomposition is performed on the snapshot matrix composed of all unified dimension response snapshot vectors to extract an intrinsic orthogonal matrix, and an order-reduced fast evaluation model is formed by interpolation mapping and the intrinsic orthogonal matrix; step 3, the order-reduced fast evaluation model is used to sample and evaluate the value range of the parameterized design variables, and the optimal design parameter interval of the key design parameters is output. The Borgonovo and Shapley joint sorting simultaneously captures the fair distribution of the distribution shape influence and the interaction effect, and provides a parameter optimization scheme for the geopolymer composite foundation which takes into account the accuracy and robustness.