106 results about "Orthogonal matrix" patented technology

The invention provides an intelligent risk identification and analysis method based on multi-modal heterogeneous data fusion, which relates to the technical field of risk management, and comprises the following steps of: acquiring multi-source data, constructing symbol-nerve double-space processing, generating semantic vectors, extracting features through orthogonal matrix decomposition and a bidirectional long-short-term memory network, and obtaining an intelligent risk identification and analysis result; according to the method, multi-modal information is fused by using an adaptive weight mechanism, and a risk propagation topology network is constructed by applying a graph embedding algorithm, so that accurate identification and early warning of risks are realized, and the risk prevention and control capability and prediction accuracy are effectively improved.

The invention discloses an MEMS and MHD combined gyroscope low-high frequency composite calibration method, which comprises the following steps: synchronously acquiring vibration response data of a combined gyroscope sensor, separating low-high frequency signals, calculating low-frequency static error parameters and high-frequency dynamic error parameters, constructing a static orthogonal matrix based on a mounting angle error, and calibrating the low-high frequency composite of the MEMS and MHD combined gyroscope. The method comprises the following steps: generating a normalized error transfer coefficient by utilizing a high-frequency dynamic error parameter cross response ratio and a rejection ratio, generating a dynamic error matrix according to the normalized error transfer coefficient, establishing an expression containing error output of a sensor by utilizing the dynamic error matrix, and inversing the dynamic error matrix to obtain a dynamic error transfer matrix, and the static orthogonal matrix and the dynamic error transfer matrix are combined to construct a composite error compensation model, error parameters after dynamic compensation are evaluated, a residual feedback signal is generated in combination with an error evaluation result, calibration error parameters are iteratively corrected until convergence, and the calibration parameters are output.

The invention discloses a signal transmission method and device based on orthogonal matrix precoding. The method comprises the steps that four chaotic sequences X, Y, Z and W are generated through a four-dimensional chaotic model according to a key initial value; performing bit interleaving on the original data by using X and W to obtain first data; performing serial-to-parallel conversion and QPSK mapping to obtain a mapping signal; scrambling the subcarriers and symbols of the mapping signals by using Y and Z to obtain encrypted data; carrying out IFFT (Inverse Fast Fourier Transform) on the encrypted data, adding a cyclic prefix, and carrying out parallel-serial conversion to obtain an encrypted data stream; performing binary conversion and serial-parallel conversion on the key initial value to obtain a square matrix K, and shaping the square matrix K by using a public key to obtain a key matrix; performing serial-to-parallel conversion, QPSK mapping, IFFT, cyclic prefix addition and parallel-to-serial conversion on the key matrix to obtain a key stream; and performing linear superposition on the encrypted data stream and the key stream through power distribution to obtain a power division multiplexing orthogonal frequency division multiplexing signal, and transmitting the power division multiplexing orthogonal frequency division multiplexing signal.

The invention relates to the technical field of artificial intelligence security, discloses a federated learning method and system based on decentralized orthogonal encryption of symmetric noise, and realizes efficient and secure communication and calculation in federated learning. Performing SVD decomposition on the initial model to generate a row representation matrix and a column representation matrix, and determining a row and column sampling index value through a Nystrom method and issuing the row and column sampling index value to a client; the client generates a local private orthogonal encryption matrix and a global shared orthogonal encryption matrix, and encrypts a local model matrix; dividing the private encryption matrix into N sub-shares through a threshold secret sharing mechanism, constructing a (t-1)-degree polynomial to realize secret distribution, and forming a distribution matrix; the central server carries out weight sorting instead of aggregation on the encryption matrixes uploaded by the client, and a sorted encryption matrix set is generated; and the client gradually removes an encryption matrix by utilizing transposition of an orthogonal matrix and secret sharing reconstruction through an iterative decryption process, and recovers a global aggregation result through a noise cancellation mechanism.

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 method and device for constructing a volatile organic compound emission list, and the method comprises the steps: obtaining observation data based on a preset observation point, and obtaining the concentration data of volatile organic compounds in a boundary layer based on the observation data; constructing a box model, and calculating the discharge flux in the boundary layer based on the box model and the concentration data; matrix decomposition is carried out on the concentration data and the emission flux based on an orthogonal matrix factor model, and a target factor contribution matrix and a target factor spectrum matrix are obtained; and determining an emission source and a contribution ratio thereof based on the target factor contribution matrix and the target factor spectrum matrix, and constructing a volatile organic compound emission list based on the emission flux, the emission source and the contribution ratio thereof. According to the method, the observation data is obtained based on the preset observation point, the concentration data of the VOCs in the boundary layer is obtained, the emission flux in the boundary layer is evaluated through the box model and the orthogonal matrix factor model, the reliability and accuracy of the evaluation result are ensured, and then the volatile organic compound emission list is accurately constructed.

The present application provides a coding method, a decoding method, and a communication apparatus. In the method, a check matrix used for coding first information comprises a plurality of submatrices, and each submatrix is a zero matrix or a non-zero matrix having both row and column weights of 1. Therefore, each submatrix is an orthogonal matrix, such that parallel decoding and low decoding complexity can be achieved, and the communication delay is reduced, thereby improving the communication efficiency.

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 method and device for obtaining an optimal solution of a high-dimensional Hardy theorem, and the method comprises the steps: a state matrix construction step: converting a two-mass quantum entangled state into a state matrix H; an orthogonal matrix construction step: constructing a group of real orthogonal matrixes based on the SO (d) rotation group, and selecting one of the matrixes as a current measurement matrix A1; a Hardy measurement value calculation step: determining other measurement matrixes A2, A3,..., Ak and B1, B2,..., Bk in combination with the state matrix H and the current measurement matrix A1; calculating a Hardy measurement value meeting a logic constraint condition based on the measurement matrix; a cycle judgment step: judging whether all the real orthogonal matrixes are traversed, if so, entering an output step, and otherwise, selecting a new real orthogonal matrix and returning to the Hardy measurement value calculation step; and an output step: selecting a maximum Hardy measurement value and a measurement matrix combination thereof as an optimal solution for output. The Hardy theorem optimal measurement strategy in the high-dimensional quantum system can be efficiently determined, and the method has good universality and expandability.

Methods, systems, and devices for solving quadratic optimization problems on orthogonal groups using quantum computing. In one aspect, a method includes receiving data representative of a quadratic optimization problem, where decision variables of the quadratic optimization problem take values in an orthogonal group or a special orthogonal group; encoding the quadratic optimization problem as a quantum Hamiltonian, the encoding including using a Crifford algebraic representation of the population to map orthogonal matrices or special orthogonal matrices in the population to corresponding quantum states in Hilbert space; determining an approximate eigenstate of the quantum Hamiltonian; calculating an expected value of a Fouli operator with respect to the approximate eigenstate, where the Fouli operator comprises an operator obtained by mapping a multiplication operation of a Crifford algebra into a Hilbert space; and rounding the expected value of the Fouli operator into the elements of the orthogonal group to obtain a solution to the quadratic optimization problem.

The invention relates to the technical field of optical fiber sensing, in particular to a rapid demodulation method based on improved space phase shift, which comprises the following steps: firstly, designing a space phase shift angle, then constructing a space phase shift matrix, and finally demodulating the amplitude or phase of a signal through a demodulation formula. According to the method, the intermediate frequency matrix is directly utilized to construct the orthogonal matrix, the orthogonal space phase shift angle is designed and introduced, the first space phase shift matrix and the second space phase shift matrix are accurately designed, the relationship among the space phase shift angle, the sampling frequency and the acousto-optic modulator frequency shift is fully utilized, the calculation efficiency of system demodulation is effectively improved, and the system demodulation accuracy is improved. And complex frequency mixing filtering operation and additional hardware equipment required by a traditional demodulation method are reduced, and the system demodulation cost is reduced.

The application discloses a kind of tight oil fracturing horizontal well differentiation energy storage methods, system and storage medium constrained by full-cycle stratum energy level evolution.The method comprises: constructing flow field prediction base based on local grid encryption and micro-osmotic equation coupling, embedding low-speed non-Darcy seepage control osmosis oil production velocity equation and dynamic zoning evolution algorithm of relative permeability curve;Based on streamline simulation module, carry out full-time domain flow field evolution tracking, accurately locate the decoupling breakpoint of injection-production space;Based on multidimensional orthogonal matrix, nonlinear collaborative optimization is carried out on single round extraction parameter, and the optimal process parameter combination of single round is locked by variance analysis;Cross energy level evolution scanning and establishing full life cycle differentiation energy storage chart.The application solves the problems of micro-mechanism distortion, multi-parameter collaborative optimization inefficiency and strategy and energy level evolution mismatch, and significantly improves the recovery efficiency of tight oil reservoir.

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.

The embodiment of the application discloses a sequence generation method and related equipment, wherein the sequence generation method can be realized by interaction between a network device and a terminal device. The network device determines pilot configuration parameters of the terminal device, and sends the pilot configuration parameters to the terminal device. The terminal device can determine, according to an orthogonal matrix indicated by the pilot configuration parameters, that part or all elements in each column of the orthogonal matrix constitute a pilot sequence of the terminal device. It can be seen that the pilot sequence generated by the method is selected from the orthogonal matrix, so that the number of the pilot sequence tends to be infinite, the demand of a large number of terminals in an mMTC scene is met, and the system capacity is improved. Meanwhile, through the design of the pilot, the complexity of processing at the receiving end is reduced.

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.

In one aspect, the method includes receiving data representing a quadratic optimization problem, where decision variables of the quadratic optimization problem take values ​​on an orthogonal group or a special orthogonal group; encoding the quadratic optimization problem as a quantum Hamiltonian, where the encoding includes mapping an orthogonal matrix or a special orthogonal matrix of the group to respective quantum states in Hilbert space using a Clifford algebra representation of the group; determining approximate eigenstates of the quantum Hamiltonian; and calculating expectation values ​​of Pauli operators for the approximate eigenstates, where the Pauli operators include operators obtained by mapping a multiplication operation of the Clifford algebra to Hilbert space; and rounding the expectation values ​​of the Pauli operators to elements of the orthogonal group to obtain a solution to the quadratic optimization problem.

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 invention discloses a color image dual encryption method based on orthogonal frequency domain scrambling and phase steganography, and belongs to the technical field of optical information encryption. According to the method, orthogonal frequency domain scrambling and phase steganography are fused, an orthogonal projection-phase reconstruction cross-domain collaborative encryption framework is constructed, and deep fusion of mathematical irreversibility and physical unclonability is realized. In a mathematical encryption layer, designing a high-dimensional orthogonal matrix to perform global linear transformation on RGB three-channel combined two-dimensional discrete cosine transform coefficients, and eliminating correlation between a frequency domain statistical law and the channels; in a physical encryption layer, orthogonal encryption data is coded into a phase image, secondary modulation is carried out through a non-interference coding aperture correlation holographic optical system, spatial domain plaintext information is destroyed by using physical unclonability of speckle noise, and a joint protection mechanism of a mathematical key and a physical key is formed. The method is suitable for scenes with extremely high requirements on encryption strength and anti-attack capability, such as secret communication and medical image security storage.

The MIMO equalizer circuit (300) includes: a controller (339); a calculation circuit (302) generates and outputs an autocorrelation matrix W (308) in response to receiving the covariance matrix RI (123) and the channel estimation matrix H (121). A matrix calculation circuit (316) that receives and combines the inverse autocorrelation matrix (315) and the channel estimation matrix H (121), and outputs an equalization gain P matrix (324); an inverse autocorrelation matrix (315), a received signal vector y (301), and a channel estimation matrix H (121) are received and combined, and a vector'f '(323) is output. A successive interference cancellation (SIC) detection circuit (325) converts the received P matrix (324) into a first orthogonal unitary matrix Q (328) and a first upper triangular matrix R (327), and converts the matrix Q (328), the matrix R (327), and the f vector (323) into an SIC estimated equalization symbol Z2 vector (330), which is output.

The invention discloses a point cloud encryption method and device based on a Gaussian mixture flow model, a medium and a product, and relates to the technical field of data processing, and the method comprises the steps: mapping an original point cloud to a hidden space obeying Gaussian mixture distribution based on a preset point cloud protection model, and obtaining an encrypted point cloud, the point cloud protection model being constructed based on the Gaussian mixture flow model; and rotating each point of the encrypted point cloud through a preset target orthogonal matrix to obtain a target point cloud. According to the method, the Gaussian mixture flow model is introduced into 3D point cloud data processing, the difficulty that a traditional flow model cannot be directly applied to the point cloud due to the irregularity, sparsity and disorder of the point cloud data is overcome, the target point cloud can be restored to the original point cloud under the condition that a user holds a decoder and a target orthogonal matrix, and the user experience is improved. And the encrypted point cloud can be normally used in a downstream application scene, so that the practicability of the encrypted point cloud is improved.

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.

The method comprises the following steps of: decomposing a measurement matrix of each strapdown triaxial magnetometer into a unit orthogonal matrix and a symmetric positive definite matrix by utilizing the characteristic that a magnetic field modulus is independent of the unit orthogonal matrix and adopting a polar decomposition technology, and obtaining an equivalent zero offset and the symmetric positive definite matrix of each strapdown triaxial magnetometer by adopting ellipsoid equation iteration linear least square fitting; a virtual coordinate system is introduced, a vector modulus value correction value of measurement data of each strapdown triaxial magnetometer is calculated, a correction value of a magnetic field horizontal modulus gradient is further obtained, and calibration of the strapdown triaxial cross magnetic array is completed. According to the method, the ellipsoid equation is solved with high precision by adopting the iterative linear least square method, the strapdown three-axis cross magnetic array does not need to be accurately rotated, high-precision calibration can be carried out under the condition of providing the geomagnetic field modulus, and the operation is simple and convenient; the iterative linear least square algorithm is simple, the calculation amount is small, and engineering implementation is easy.

The invention discloses a vector retrieval method and device, a medium, electronic equipment and a program product. The method comprises the steps that a first vector corresponding to an input request is acquired, a first transformation matrix is acquired, and the first transformation matrix is generated based on a first orthogonal matrix and a second orthogonal matrix; performing linear transformation on the first vector by using the first transformation matrix to obtain a first ciphertext vector; sending the first ciphertext vector to a first server; the ciphertext vector in the knowledge vector library is obtained by performing linear transformation on a second vector by using a second transformation matrix, and the second transformation matrix is generated based on the first orthogonal matrix, the second orthogonal matrix and the second vector. Thus, on the premise of supporting vector retrieval, the vec2text attack in a language model service scene can be resisted, and leakage of privacy data in the knowledge vector library is avoided. The second transformation matrix is dynamically generated according to the second vector itself, so that differences of plaintext and ciphertext inner products of different vector pairs in the knowledge vector library are different, and the effectiveness of known plaintext attacks is remarkably reduced.

This invention provides a noise reduction method for ground-penetrating radar (GPR) data based on grouped singular spectra. It employs zero-bias mode GPR and, based on singular spectrum analysis, decomposes the spectral matrix of GPR data into an orthogonal matrix and a singular value matrix. The singular values ​​are grouped using the k-means clustering method, and the singular values ​​of the spectral matrix are reweighted using a grouping weighting function, thereby reducing noise interference in the GPR data.

The invention discloses an indirect abnormal transaction identification method and device and a model construction method and device, and relates to the field of big data, and the identification method comprises the steps: extracting the multi-dimensional transaction key element features and the position sequence of each third-party transaction opponent from the current channel business transaction data; according to the key element features and the position sequence, obtaining a current channel business transaction multi-dimensional information vector of each layer; converting each layer of multi-dimensional information vector to a transaction hyperplane through a non-associated orthogonal matrix; inputting the current transaction hyperplane composition graph into an indirect abnormal transaction path identification model to obtain a plurality of indirect abnormal transaction paths corresponding to each piece of current channel business transaction data to form a current traversal track graph; and matching the current passing track atlas with a historical passing track atlas in the indirect abnormal transaction identification stereo coupling model to obtain an identification result of whether the current channel business transaction is an indirect abnormal transaction or not. According to the invention, the accuracy of indirect abnormal transaction identification can be improved.

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.

The present invention relates to the field of artificial intelligence security technology, and discloses a federated learning method and system for decentralized orthogonal encryption based on symmetric noise, which realizes efficient and secure communication and computing in federated learning; performs SVD decomposition on the initial model to generate a row representation matrix and a column representation matrix, determines the row and column sampling index values through the Nystrom method and distributes them to the clients; the clients generate local private orthogonal encryption matrices and global shared orthogonal encryption matrices to encrypt the local model matrices; divides the private encryption matrix into N sub-shares through the threshold secret sharing mechanism, constructs a t-1 degree polynomial to realize secret distribution, and forms a distribution matrix; the central server performs weight sorting rather than aggregation on the encrypted matrices uploaded by the clients to generate a set of sorted encrypted matrices; the clients gradually remove the encrypted matrices through the iterative decryption process, using the transpose of the orthogonal matrix and secret sharing reconstruction, and restore the global aggregation result through the noise cancellation mechanism.

The present invention discloses a method and system for reducing the order of a multi-coupled field model of turn-to-turn short circuit in a converter transformer. The method first constructs a full-order turn-to-turn short circuit geometric model of the converter transformer in the turn-to-turn short circuit state, solves the transient loss distribution function of the converter transformer through the magnetic flux density and current density distribution functions of the converter transformer, constructs a multi-coupled field model of turn-to-turn short circuit in the converter transformer, establishes an nth-order single-input single-output nonlinear model, and when solving the transient temperature field and transient magnetic field, expands the nth-order single-input single-output nonlinear model, calculates the low-order model through the standard column orthogonal matrix V0, multiplies the left side of both ends of the low-order model by #imgabs0# to obtain a secondary reduced-order model, and sums the weighted m secondary reduced-order models to obtain a reduced-order model; the present invention takes into account the nonlinear problem of the iron core and the change of the thermal conductivity of the material due to temperature, and reduces the order of this nonlinear model through the multi-point quadratic method, which speeds up the simulation efficiency and reduces the simulation time consumption.

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.