45 results about "QR decomposition" patented technology

The invention relates to the technical field of telephone communication, and discloses a robust recursive least square adaptive filter based on inverse QR decomposition and a storage medium, and the method comprises the steps: calculating an inner product of an adaptive weight vector at a moment and an input signal vector, and obtaining an output signal at the moment of the adaptive filter; calculating a difference value between the expected signal and the output signal at the moment, obtaining an estimation error signal, and constructing a nonlinear weighting function; recursively updating and acquiring an inverse correlation matrix of the moment input signal vector based on the moment input signal vector and transpose thereof, a nonlinear weighting function, the inverse correlation matrix of the input signal vector and the covariance of the estimated error signal, and constructing a block matrix containing the inverse correlation matrix of the moment input signal vector; inverse QR matrix decomposition and unitary rotation operation are sequentially carried out on the block matrix, an array before inverse QR decomposition and an array after inverse QR decomposition at the moment are obtained, a gain vector at the moment is constructed, and a self-adaptive weight vector at the moment is updated and obtained.

This invention discloses a method and device for reconstructing the deformation of mesh antenna nodes, belonging to the field of spaceborne mesh antennas. Based on the geometric position and topological connection relationship of the mesh antenna, a mapping model between node displacement and cable element strain is established. RBF radial basis interpolation is introduced, and the displacement information of a small number of control points is used to characterize the deformation field of the entire reflector surface, establishing an explicit relationship between cable element strain and control point deformation. Singular value decomposition is performed on this mapping matrix to extract the dominant strain characteristics; then, combined with column-pivot QR decomposition, the most linearly independent cable elements with the most significant response to the dominant strain are automatically identified as the placement positions for strain sensors. This invention achieves high-precision reconstruction of mesh antenna node displacements with a limited number of sensors, effectively reducing the number of sensors required while ensuring reconstruction accuracy, thus solving the problems of large sensor count and high system complexity in on-orbit deformation monitoring of spaceborne mesh antennas.

The application relates to a QR decomposition-based matrix-vector multiplication implementation method based on a vector processor, and the QR decomposition algorithm is a vsip_cqrd_f function in a VSIP library, the VSIP library is a vector, signal and image processing library launched by a GE intelligent platform, and is an open standard application programming interface specially provided for developers who need to use intensive signal and image processing. The technical scheme of the application mainly comprises the following steps: step one, judging whether input matrix C needs transposition conjugate processing and whether the matrix C is on the left or right in matrix multiplication, so as to enter different branch processing; step two, pre-processing the A matrix; step three, adopting different processing schemes according to the quantity size to realize matrix-vector multiplication operation. The application is designed and realized for the QR decomposition-based matrix-vector multiplication in the light of the advantages of the vector processor, such as large storage space, on-chip cache and efficient and fast data transmission, and can play a great advantage in complex matrix operation.

The application discloses a spherical decoding detection method and device, electronic equipment and a readable storage medium, and belongs to the technical field of wireless communication. The application obtains a Q matrix and an R matrix by performing orthogonal triangular QR decomposition on a channel response matrix, wherein each column in the Q matrix is arranged according to the size of channel energy; determines a target equalization signal according to the Q matrix and the R matrix; performs an ML path search process according to the target equalization signal to select N branches with minimum metrics as survivor paths; performs ML complement path search on the survivor paths to obtain ML complement paths; takes the survivor paths with minimum metrics as ML paths, and obtains the likelihood ratio information of each bit of each symbol at each layer according to the ML paths and the ML complement paths. The application can reduce the operation complexity of the spherical decoding algorithm while maintaining the decoding detection performance.

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.

The invention relates to a TSN (Time Sensitive Network) timestamp recovery method based on an FPGA (Field Programmable Gate Array), which belongs to the technical field of TSNs and comprises the following steps of: S1, collecting synchronous messages of different TSN nodes in parallel by multiple ports of the FPGA, and analyzing timestamp data by taking a message serial number as an anchor point; s2, constructing an incomplete timestamp matrix and a mask matrix by adopting a time sliding window mechanism, and automatically marking missing data; s3, a random index set is generated through LFSR, and matrix sparse sampling is achieved through a bitmap judgment unit; and S4, based on an FPGA accelerated CUR matrix decomposition algorithm, solving a pseudo-inverse matrix through parallel MGS-QR decomposition, and reconstructing a complete timestamp matrix through block parallel matrix chain multiplication. The FPGA parallel architecture, ping-pong cache and fixed-point number processing are adopted, microsecond-level low-delay recovery is achieved, hardware resource occupation is greatly reduced, robustness in a severe network environment is improved, and the method is suitable for a high-precision clock synchronization scene of an industrial TSN node.

This invention discloses an efficient QR matrix decomposition method based on FPGA for implementing systolic matrices, belonging to the field of software-defined radio signal transmission technology for airborne networks. It is based on the design of a multi-channel digital front-end implemented on an FPGA chip. The method includes: designing a general handshake coordination mechanism, designing a timing flow for systolic matrix multiplication, performing fast QR matrix decomposition single-loop operations by calculating the Householder mirror transformation matrix, designing a top-level loop pipeline for QR matrix decomposition, and finally verifying the hardware scheme of the fast QR decomposition algorithm. This invention converts resource consumption into timing consumption by designing the overall pipeline logic and loop operations, enabling fast processing and accurate decomposition of digital information in a multi-channel digital front-end on an FPGA, effectively saving on-chip resources. In addition, this invention has excellent scalability, supporting 64 to 128-bit high-precision fixed-point number formats, and the data matrix order can reach up to 128.

This application provides a method and system for ad push based on user browsing behavior, belonging to the field of data processing technology. First, this application simultaneously acquires the user's historical search terms and current page interaction behavior, including click weights and dwell time, and constructs an intent vector representing long-term preferences and a behavior vector reflecting current interests accordingly. Next, the two vectors are combined into an observation matrix, and a QR decomposition technique is used to extract an orthogonal basis vector representing the user's independent, core intent as a reference standard. Subsequently, the grey relational coefficient and correlation degree between this reference vector and the attribute vectors of each candidate ad are calculated to quantify the degree of matching between the two. Finally, the ads with the highest correlation are selected and accurately pushed to the user. This application achieves accurate mining of the user's core intent and matching and pushing highly relevant ads in complex page environments.

The present application relates to the field of digital image watermarking technology in information security, and provides a double color data image watermarking, image watermarking embedding, image watermarking extraction method and system. The double color data image watermarking method comprises an embedding process and an extraction process. In the embedding process, the color watermarking image W is encrypted by using HDNA, Mandelbrot graph and three-dimensional IPCM chaotic system to obtain an encrypted watermarking; the color carrier image is decomposed by QR decomposition, and then the encrypted watermarking is embedded into the color carrier image. In the extraction process, the encrypted watermarking information is extracted by QR decomposition, and then the original color watermarking information is extracted from the encrypted watermarking information by HDNA and Mandelbrot graph. The present application provides a safe, transparent and efficient double color image watermarking method, which has the advantages of high security, strong robustness, large copyright information capacity and fast operation speed, and has stronger application value.

The invention relates to the technical field of carbon emission calculation, and discloses an electric power carbon emission factor calculation method, system, equipment, medium and product based on QR matrix factorization. According to the method, a node power balance equation and a carbon emission conservation equation are determined by obtaining carbon emission information and tidal current power information of all generators in a power grid; the method comprises the following steps: constructing a carbon emission factor linear equation, solving the carbon emission factor linear equation based on QR matrix decomposition to obtain a carbon emission factor value of each node, so that efficient solving is realized by utilizing sparse matrix characteristics and QR decomposition, rapid response of multi-node carbon emission factor solving is realized, and the method does not depend on initial solution setting; the slow convergence or failure risk of an iteration method is avoided, the numerical stability is excellent, and the accuracy and reliability of carbon emission factor calculation are improved.

The present invention relates to a method for determining insulation resistance (R1, R2) and discharge capacitance (C1, C2) for ground (PE) of an ungrounded DC power supply system, wherein a linear difference equation is implemented as a function of a measurement voltage (UG(k)) and a grid voltage (UN(k)) with a measurement voltage (UM(k)), and a grid parameter (θi) formed from a shunt (RM), insulation resistance (R1, R2) to be determined, and discharge capacitance (C1, C2) to be determined. Using N linear differential equations, a measurement value equation system is implemented with a sample sequence ((UG(k), UN(k), UM(k))) and a grid parameter (θi) for measurement times from k = 1, 2 to N with a sampling period T. Another method step comprises a step (S6) of calculating the estimated grid parameter (θi) as an approximate solution to the measurement value equation system, wherein the sum of squared errors between the grid parameter (I) and the estimated grid parameter (θi) is minimized, a step (S7) of minimizing the sum of squared errors through QR decomposition of the measurement-value matrix (Ψ), wherein the QR decomposition is recursively calculated, and a step (S8) of calculating each insulation resistance (R1, R2) and each discharge capacitance (C1, C2) from the estimated grid parameter (I) and repeating the method step with the estimated grid parameter (I), each calculated to include samples available at the current measurement time.

The application provides a sorting QR decomposition method for a MIMO system, comprising: determining an initial matrix to be sorted according to a channel matrix of a MIMO system to be detected; determining column vectors to be sorted of the matrix and a column number thereof, denoted as a target number; if the target number is greater than a preset value, performing a first sorting strategy: in a first round of iteration, exchanging column orders of a column vector to be sorted with a smallest norm value and a first column vector to be sorted, and in each subsequent round of iteration, exchanging column orders of a column vector to be sorted with a second smallest norm value and a column vector to be sorted in a current round, to obtain a first target matrix; and a last column vector of the first target matrix corresponds to a highest layer traversal constellation point of an FSD algorithm. The above scheme can obtain an optimized target matrix. The application also provides an FSD-based signal detection method, which performs FSD signal detection by using the above optimized target matrix, so that the number of highest layer traversal constellation points is reduced, and the detection accuracy and reliability are still ensured.

This invention relates to the field of digital signal processing technology, and discloses a DSP multi-core parallel QR decomposition method and apparatus based on tile algorithm. The method includes: dividing the matrix to be decomposed into blocks in the horizontal direction according to the number of cores of the DSP processor and setting tile blocks; performing QR decomposition on the main diagonal tile blocks; and updating all tile blocks to the right of the main diagonal tile blocks in the horizontal direction; pairwise coupling of the main diagonal tile blocks with each tile block in the vertical direction of the same column; performing QR decomposition on the coupling matrix formed by each pair of couplings; and updating all coupling matrices to the right of the pair of coupling matrices in the horizontal direction; and cyclically executing the decomposition and horizontal update of the main diagonal tile blocks, the coupling decomposition of the tile blocks in the same column, and the update of the right coupling matrix until all main diagonal tile blocks in the matrix to be decomposed have been processed, resulting in an upper triangular matrix. This invention can fully utilize the parallel processing advantages of multi-core processors to achieve inter-core parallel data processing.

Embodiments of the present disclosure provide a visual inertia fused localization method and a device. The method comprises: acquiring target observation data corresponding to a target state vector; constructing a first residual model according to the target observation data; projecting the residual model according to a first-order partial derivative matrix, to obtain a second residual model, the second residual model comprising a product term of a second-order partial derivative square matrix and a system state matrix, and a covariance term corresponding to a first observation noise term; and eliminating a three-dimensional coordinate error vector of the second residual model, to obtain a target residual model, and performing EKF updating on the target state vector according to the target residual model. The embodiments do not involve left null space calculation and projection, and QR decomposition dimension reduction calculation, thereby reducing the amount of calculation, and improving positioning efficiency.

The application provides a multi-base station two-dimensional positioning method based on a pseudo-TDMA mechanism, which requests access by sending a Blink frame by a tag, a main base station allocates a communication time slot and issues an offset, and the tag is aligned to a specified time slot to realize pseudo-TDMA orderly communication; the tag sends a Poll frame in the time slot, and multiple base stations reply a Response frame in turn according to a preset gradient delay to avoid air signal collision; the system monitors time slot drift in real time and corrects through a Response frame feedback; multi-base station ranging data is collected to construct an over-determined equation, QR decomposition is used to solve the least square to obtain a two-dimensional coordinate of the tag, and abnormal base station data is removed and redundant positioning is supported. The application has the beneficial effects that the communication collision and strict network synchronization problems in a high-density scene are effectively overcome, the application has the advantages of low collision rate, high channel utilization rate, high positioning precision and strong fault tolerance, and is particularly suitable for large-scale personnel positioning in complex environments such as underground.

The present application belongs to the technical field of wireless signal positioning, and discloses a ground-based radiated source TDOA positioning method based on the constraint of the earth ellipsoid. First, the TDOA observation quantity about the ground-based radiated source is obtained by using multiple adjacent space observation platforms, and is converted into a distance difference observation quantity. Then, a scalar product matrix is constructed by using the distance difference observation quantity, and a pseudo-linear observation equation is constructed based on the same. Next, the influence of the distance difference observation error and the prior observation error of the observation platform position vector on the pseudo-linear observation equation is quantitatively analyzed by using a first-order error analysis method, and the singularity problem of the pseudo-linear observation error covariance matrix is avoided by using matrix QR decomposition, so that an optimal weighting matrix is obtained. Then, by using the earth ellipsoid constraint to which the ground-based radiated source is subjected and the algebraic characteristics of the auxiliary variable, a positioning optimization model containing double quadratic equality constraints is constructed. The present application utilizes the earth ellipsoid constraint to which the ground-based radiated source is subjected, and effectively improves the positioning precision.

The invention relates to a key technology in the field of computer image processing and data recovery, in particular to an asynchronous calculation method for a matrix singular value and a singular vector of the matrix singular value. The matrix singular value pure CPU asynchronous calculation method specifically comprises the following steps: uniformly partitioning an input matrix into a plurality of sub-matrixes according to rows, carrying out asynchronous parallel QR decomposition iterative calculation on each sub-matrix on a multi-core CPU platform, and extracting a column orthogonal basis and a row orthogonal basis of each sub-matrix; recombining the row orthogonal basis of each sub-matrix and then carrying out QR decomposition iteration again to generate an intermediate matrix of which the dimensionality is obviously reduced; performing approximate singular value decomposition on the intermediate matrix; and finally obtaining a plurality of first singular values and singular vectors of the original matrix through matrix multiplication recombination. According to the method, the parallel computing capacity of the multi-core CPU is fully utilized, GPU hardware support is not needed, and compared with a traditional SVD algorithm, the computing speed is obviously increased.

The embodiment of the invention provides a large-scale matrix QR decomposition single-core serial calculation method, device and equipment and a storage medium, block calculation is performed on a matrix according to the fast memory capacity to realize multi-stage matrix QR decomposition, and compared with a single-core serial QR decomposition method, the method has the advantages that the matrix is always accessed in a rectangular block mode when the matrix is accessed, so that the matrix access efficiency is improved. In the calculation step, the serial QR decomposition step is executed in the diagonal matrix blocks, and the Level-3 BLAS is used when the non-diagonal matrix blocks are updated, so that the calculation complexity and memory access ratio in a single core are improved, and the calculation efficiency of the single core is improved.

The application discloses a kind of geometric guidance and task self-adapting multithreaded spherical decoding method and related device, belong to wireless communication technical field, including: the channel matrix of system model is obtained, the channel matrix of system model is carried out QR decomposition, and the result of QR decomposition is obtained;Search tree is constructed based on the result of QR decomposition;The search radius and optimal solution of search tree are dynamically updated, and the geometric threshold value is determined;According to the search radius and optimal solution of updated search tree and the geometric threshold value determined, the search tree is searched by multithreading according to SE order, and the symbol vector of transmitting antenna in system model is obtained, and the geometric guidance and task self-adapting multithreaded spherical decoding is completed, the method and related device can improve search efficiency, shorten search time simultaneously, reduce the cost of search task scheduling and synchronization.

A method for multi-objective vector fitting includes the following steps: 1) processing a given dataset to construct a single-objective fitting dataset; 2) determining initial poles and using the initial poles and frequency sampling points to establish a fundamental matrix; 3) separating the real and imaginary parts of the fundamental matrix to construct a real fundamental matrix; 4) performing a simplified QR decomposition on the real fundamental matrix to obtain the first M columns of the complete Q matrix, denoted as Q. s Matrix, and for Q s The matrix is ​​stored; 5) Construct and solve the pole coefficient equation to obtain the pole coefficients; 6) Construct the pole characteristic equation using the pole coefficients and the initial poles to calculate the new poles; 7) Calculate the residues of each matrix element corresponding to the new poles to complete the vector fitting. This invention provides a method for multi-objective vector fitting that significantly reduces the computational complexity and improves computational efficiency.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit an indication of a dynamic precoding resource block group (PRG) size UE capability. The UE may receive, in accordance with the dynamic PRG size UE capability, a dynamic PRG size configuration. The UE may receive, in accordance with the dynamic PRG size configuration, an indication of a dynamic PRG size of a PRG that contains a plurality of resource elements (REs) associated with a common Q matrix derived from a QR decomposition. The UE may receive data using the dynamic PRG size. Numerous other aspects are described.

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.

The application relates to the technical field of telephone communication, and discloses a robust recursive least square adaptive filter based on inverse QR decomposition and a storage medium, which comprises the following steps: calculating the inner product of an adaptive weight vector at a moment and an input signal vector, and obtaining an output signal of the adaptive filter at the moment; calculating the difference between an expected signal at the moment and the output signal, obtaining an estimated error signal, and constructing a nonlinear weighting function; based on the input signal vector at the moment, a transpose of the input signal vector, the nonlinear weighting function, an inverse correlation matrix of the input signal vector, and a covariance of the estimated error signal, recursively updating the inverse correlation matrix of the input signal vector at the moment, and constructing a block matrix containing the inverse correlation matrix of the input signal vector at the moment; performing inverse QR matrix decomposition and unit rotation operation on the block matrix in sequence, obtaining an inverse QR decomposition front array and a rear array at the moment, constructing a gain vector at the moment, and updating the adaptive weight vector at the moment.

The invention discloses a digital signal compensation method and system for an optical module, and relates to the field of network transmission, and the method comprises the steps: dividing an input ideal driving signal into a static basis and a dynamic basis in an initialization stage, respectively constructing a static basis matrix and a dynamic basis matrix, and obtaining a static basis coefficient and a dynamic basis coefficient; performing QR decomposition orthogonalization on the dynamic basis, and removing the part overlapped with the static basis to obtain a sparse set; an output compensation signal is obtained; and updating the static basis coefficient. According to the invention, an input signal is divided into a static base and a dynamic base, so that accurate compensation of instantaneous nonlinear and dynamic nonlinear distortion is realized. The number of static bases and the number of dynamic bases are adjusted in a self-adaptive mode by combining hardware resources and channel performance parameters, performance targets and resource constraints are considered, and good universality is achieved. In the operation stage, static base self-adaptive updating is triggered through periodic error monitoring, the dynamic base learning step length is reduced and returned, and it is ensured that dynamic response is stable and signal distortion is controllable.

The invention discloses a geometric guidance and task self-adaption multi-thread sphere decoding method and a related device, and belongs to the technical field of wireless communication, and the method comprises the steps: obtaining a channel matrix of a system model, and carrying out the QR decomposition of the channel matrix of the system model, and obtaining a QR decomposition result; constructing a search tree based on a result of the QR decomposition; dynamically updating the search radius and the optimal solution of the search tree, and determining a geometric threshold value; according to the search radius and the optimal solution of the updated search tree and the determined geometric threshold value, searching the search tree through multiple threads according to an SE sequence to obtain a symbol vector of a transmitting antenna in a system model, and completing multi-thread sphere decoding of geometric guidance and task self-adaption. Meanwhile, the search time is shortened, and the search task scheduling and synchronization cost is reduced.

The invention provides a spindle deflection coupling transmission and regulation method based on minimum envelope multistage rotor inertia, and belongs to the technical field of rotor assembly. The invention aims to solve the problem that the engineering requirements cannot be met due to lack of consideration and analysis of a multi-stage rotor inertia main shaft in multi-stage rotor stacking assembly. Comprising the following steps: S1, calculating an inertia tensor matrix [1] under a single-stage rotor assembly coordinate system; s2, calculating an inertia tensor matrix of the assembled n-stage rotor in the rotary coordinate system; s3, performing QR decomposition on the inertia tensor matrix by adopting a Gram-Schmidt orthogonalization method to obtain a space equation of an inertia principal axis; s4, projecting the inertial principal axis at different assembly angles to an xroryr plane under the rotation coordinate system, solving the minimum envelope circle diameter of the inertial principal axis projection point and the rotation coordinate origin, and establishing an inertial principal axis deflection regulation and control model; and S5, adjusting the assembly phase of each stage of rotor to regulate and control the coaxiality of the inertia main shaft and realize optimal assembly.

A communication method includes a first device that determines channel state information based on a first frame that is used for channel measurement and that is sent by a second device, performs conjugate transpose and QR decomposition to obtain a matrix R and a matrix Q, and sends, to the second device, the matrix Q indicating attribute information of a target path.

The embodiment of the invention provides a low-complexity OTFS signal detection method based on QR decomposition. The method is applied to the technical field of wireless communication physical layer receiving and detection, and comprises the following steps: preprocessing an equivalent channel matrix of an orthogonal time-frequency-space system through QR decomposition and generating an initial symbol estimation value; performing soft estimation on the initial symbol estimation value to obtain a soft estimation result, and performing decision projection on the soft estimation result to obtain a hard decision result; iteratively updating the initial symbol estimation value until residual convergence, stopping iteration and outputting a final symbol estimation value, the iteration process comprising: calculating residual energy of each symbol; sorting all symbols according to the residual energy of each symbol, and selecting the first K symbols with the maximum residual energy to form an update set; according to the method, the soft estimation result and the hard decision result of the symbol in the update set are subjected to weighted fusion through the dynamic weight, an updated symbol estimation value is obtained, the calculation complexity is reduced, and the precision and the convergence efficiency are improved.

The invention provides a multi-objective optimization method for optimizing step length self-adaption, and the optimization method is based on a multi-objective process parameter optimization method for gradient estimation and optimizing step length segmentation self-adaption adjustment, and has the unique advantages that firstly, gradient estimation is finally realized through the Taylor expansion principle in combination with principal component analysis (PCA) and QR decomposition; secondly, a self-adaptive gradient aggregation mechanism based on dynamic weight distribution is provided, so that the problem of conflicts among multiple targets is effectively solved; and finally, introducing a segmentation error monitoring module into adaptive moment estimation so as to optimize updating of parameters, so that the search strategy can be intelligently and dynamically adjusted according to different optimization stages. According to the optimization method, a plurality of optimization objectives can be effectively processed at the same time, and the optimization objectives are jointly guided to a state area with better performance within limited iterations, so that the effectiveness of the optimization method in multi-objective process optimization application is proved.

The invention discloses an efficient random low-rank approximation method and system for a parameter dependent matrix. The efficient random low-rank approximation method comprises a parameter dependent matrix low-rank approximation method based on random SVD and a parameter dependent matrix random low-rank approximation method based on generalized Nystrm. The method comprises the following steps: acquiring a parameter dependence matrix and a simulated linear decomposition structure thereof; generating a fixed random dimension reduction matrix and carrying out offline preprocessing; a matrix sketch is calculated through row partitioning and House holder QR decomposition; pre-calculating an intermediate variable by adopting an index optimization technology; in the online stage, a low-rank approximation factor is rapidly calculated through parameter correlation linear combination; and error analysis and failure probability control based on the Frobenius norm are provided. According to the method, the parameter dependency matrix low-rank approximation problem in time sequence analysis, dynamic system simulation and Gaussian process regression can be solved, and the method has the advantages of being high in calculation efficiency, small in storage overhead, good in numerical stability and controllable in error.