74 results about "Triangular matrix" patented technology

The invention discloses an imitated radio frequency division multiplexing signal detection method based on low-complexity optimization expected propagation, and belongs to the signal detection technology of multi-carrier communication. According to the method, information is updated through iteration to approach an ML result, and the complexity is reduced from an exponential level to a cubic level; in order to reduce the complexity of the EP, sparse and quasi-banded channel structures in the DAFT domain are utilized. Through matrix block decomposition, upper and lower triangular decomposition and upper triangular matrix forward substitution, low-complexity matrix inversion is successfully realized, and the complexity of the EP algorithm is reduced to a linear level. In addition, the EP algorithm performance is further improved through a deep learning optimization moment matching strategy, so that the process becomes more adaptive through trainable positive and negative component parameters. In addition, DAFT domain iteration detection and decoding can be achieved based on the method, external information of a decoder is fed back to a detector, and the reliability of the whole system is remarkably improved. According to the invention, effective balance between performance improvement and calculation complexity is realized.

The invention relates to the technical field of array signal processing, in particular to a space-frequency power inversion anti-interference method fusing SMI-LDL decomposition. The problems that an existing space-time anti-interference technology is high in calculation complexity, and real-time processing is difficult to achieve in limited resources of a navigation receiver are mainly solved. The method comprises the following steps: firstly, converting a radio frequency signal received by an array into a digital intermediate frequency signal and carrying out sliding window partitioning processing; windowing the data block and performing FFT (Fast Fourier Transform) to obtain a frequency domain array; then calculating an auto-covariance matrix R of other array elements except the reference array element and a cross-covariance matrix r of the reference array element and other array elements; lDL decomposition is carried out on the auto-covariance matrix to obtain a lower triangular matrix L and a diagonal matrix D, and inversion is carried out on the lower triangular matrix L and the diagonal matrix D respectively, so that huge operand caused by direct inversion of the covariance matrix is avoided; and finally, calculating an optimal weighting vector according to a power inversion criterion, and performing spatial filtering on the frequency domain data.

The invention relates to the technical field of artificial intelligence, in particular to an aspect triple extraction method based on a multi-channel enhanced multi-head graph convolutional network, which comprises the following steps of: encoding an input text by using a pre-training model to obtain context representation; analyzing the text to extract language features, and constructing a multi-language feature map; probability distribution between context representations is obtained through a double-affine attention mechanism, and context semantic enhancement features are calculated through a multi-head self-attention mechanism; then, features are aggregated by using a multi-head graph convolutional network, and global semantic feature representation is obtained; combining the global semantic features with the multi-language feature map, judging word pair matching and calculating emotion polarity probability distribution; and finally, analyzing the aspect emotion triad by adopting a triangular matrix structure, and performing association verification through emotion polarity probability distribution to finally obtain the aspect emotion triad. According to the method, multi-source features and an attention mechanism are effectively fused, and the accuracy and efficiency of aspect emotion triple extraction are improved.

The application discloses a multiple wave prediction method and device, a computing device and a storage medium. The method comprises the following steps: acquiring frequency domain data of any shot point at any seismic trace; generating a seismic data matrix according to the frequency domain data, the seismic data matrix being an upper triangular matrix with a main diagonal line of 0, and any non-first column of the seismic data matrix containing frequency domain data of at least one seismic trace of the same shot point; constructing a multiple wave matrix, the multiple wave matrix being an upper triangular matrix with a main diagonal line of 0, and any non-first column of the multiple wave matrix containing a multiple wave model of at least one seismic trace of the same shot point; establishing a functional relationship between the multiple wave matrix and the seismic data matrix; and obtaining model frequency domain data corresponding to any multiple wave model in the multiple wave matrix according to the functional relationship. According to the scheme, the prediction efficiency of the multiple wave can be improved under the premise of ensuring the prediction accuracy of the multiple wave.

An LDPC-code-based communication method and communication apparatus. In the method, a device can perform encoding or decoding on the basis of an LDPC matrix, wherein the LDPC matrix is determined on the basis of an LDPC base matrix, the base matrix comprises an extended check matrix, the extended check matrix is a lower triangular matrix with diagonal elements all being 1, the extended check matrix comprises a plurality of lower triangular matrices, diagonal elements of each of the plurality of lower triangular matrices are located on the diagonal of the extended check matrix, the positions of the diagonal elements of the plurality of lower triangular matrices do not overlap, and the elements in the extended check matrix other than the diagonal elements of the extended check matrix and the diagonal elements of the plurality of lower triangular square matrices are all zero elements. The method can increase the column weight of a check region, reduce the occurrence probability of an error plane, and also support retransmissions at some specific columns, and thus the method is compatible with an IR-HARQ scheme of 5G LDPC codes.

This application relates to the field of plasma physics technology and provides an asymmetric inversion method and apparatus based on a matching mechanism for plasma diagnostics. The method acquires plasma magnetic flux data, observation lines, and measurement integral values. The magnetic flux data is preprocessed to obtain preprocessed magnetic flux data. Based on the preprocessed magnetic flux data, a closed magnetic surface uniquely matched to each observation line is determined. A lower triangular matrix is ​​constructed based on each observation line and the closed magnetic surface. An inversion equation is constructed based on this lower triangular matrix and the measurement integral values. Finally, the inversion equation is solved to determine the parameter distribution values ​​of the plasma. This method achieves three-dimensional spatial projection of the observation lines and magnetic flux, rapidly determining the position of the closed magnetic surface using geometric relationships, thus improving computational efficiency. Simultaneously, it accurately establishes a one-to-one correspondence between the closed magnetic surface and the observation lines, making the ill-posed problem in solving the matrix equations a unique solution, improving the success rate of solving using the stacking method, and significantly reducing computational errors.

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 application provides a pathological section recognition neural network model weight encryption method, including: acquiring a bit string as a pathological section recognition neural network model weight key; writing the bit string into a lower triangular matrix according to 8 bits as a number to obtain a first data matrix; performing digital conversion on the first 8 bits in the bit string to obtain first element data; reading a weight matrix of the pathological section recognition neural network model into a blank matrix to obtain a weight vector matrix; combining the first element data matrix and the weight vector matrix together to obtain a first data vector; obtaining an intermediate ciphertext vector by using a chaotic mapping algorithm according to the first data matrix and the first data vector; performing element data processing on the intermediate ciphertext vector to obtain a weight vector intermediate encryption matrix; and performing position disordering on the weight vector intermediate encryption matrix to obtain an encrypted weight vector matrix. The application can improve the safety coefficient of the neural network weight.

The application discloses a text reasoning method, product, equipment and storage medium, and relates to the technical field of computers, and comprises the following steps: through the orthogonal triangular decomposition mode and in combination with the judgment mechanism whether the pre-trained language model has been trained on the fine-tuning data set, if the pre-trained language model has been trained on the fine-tuning data set, the orthogonal triangular decomposition is performed on the to-be-fine-tuned parameter matrix, the triangular matrix obtained after the decomposition is fine-tuned and trained on the fine-tuning data set, and the fine-tuned language model is obtained; if the language model has not been trained on the fine-tuning data set, the orthogonal fine-tuning is performed on the language model starting from a preset unit matrix, the fine-tuned language model is obtained, and the text reasoning is performed by using the fine-tuned language model, through the above mode, the robustness of the language model to different data sets is improved, and the accuracy of the text reasoning result is improved, and meanwhile, the problem that the robustness of the traditional pre-trained language model parameter after fine-tuning is poor and the performance is reduced is solved.

To provide a selection device, an estimation system, etc. that can appropriately select a center frequency for which a trained model should be obtained before collecting data from a real environment.SOLUTION: The selection device includes: signal generation means for generating signal data simulating an arrival signal based on parameters including at least a center frequency and arrival angle information; correlation matrix calculation means for calculating a correlation matrix based on the signal data; inference means for generating an evaluation spectrum based on a lower triangular matrix extracted from the correlation matrix using a trained model; performance evaluation means for evaluating the performance of the trained model based on an estimated arrival angle estimated based on the evaluation spectrum and a correct arrival angle of the arrival angle information; and next frequency determination means for determining a center frequency to be evaluated next based on a result of the performance evaluation. An estimation system according to the present disclosure includes the selection device and an estimation device for estimating the arrival direction of an arriving wave.SELECTED DRAWING: Figure 1

The application provides a distributed security outsourcing computing processing method based on sparse matrix transformation, and relates to the technical field of computers, and the method comprises the following steps: acquiring a first matrix and a second matrix; randomly generating a key set comprising a binary permutation matrix, a sparse triangular matrix and a random vector; performing primary encryption on the first matrix and the second matrix based on the binary permutation matrix; performing secondary encryption on the primary encrypted matrix based on the sparse triangular matrix; distributing the secondary encrypted first secondary encrypted matrix to each edge end in an integrated manner, distributing the second secondary encrypted matrix to each edge end in an even manner after dividing the second secondary encrypted matrix into column vectors according to columns, and enabling the edge end to perform a subtask calculation operation by using the received matrix and return the result to the user end; receiving the calculation results of the edge ends, and aggregating the results; verifying the reliability of the aggregated results by using the random vector, and decrypting the final calculation result. The scheme can improve the security and timeliness of outsourcing computing.

The invention provides a terminal initialization method and device, electronic equipment and a storage medium. The terminal initialization method comprises the following steps: acquiring initialization parameters, inertial constraints and visual constraints of a terminal; constructing an information matrix according to the initialization parameters, inertial constraints and visual constraints; performing Schel compensation elimination on the information matrix, and eliminating the feature points from the information matrix to obtain an eliminated information matrix; performing Cholesky decomposition on the eliminated information matrix to obtain an upper triangular matrix and a lower triangular matrix; performing inversion on the image frame state quantity corresponding to the nearest preset moment in the upper triangular matrix to obtain a square root of a covariance, and further determining the covariance; and determining the initialization state of the terminal according to the covariance and the initialization parameter. According to the method disclosed by the invention, the covariance can be quickly solved, and the state quantity fluctuation amplitude is reduced.

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.

A communication method and a communication device based on LDPC codes, in the method, a device can perform encoding or decoding based on an LDPC check matrix, the LDPC check matrix is determined based on an LDPC basis matrix, the basis matrix comprises an extended check matrix, the extended check matrix is a lower triangular matrix with diagonal elements being 1, the extended check matrix comprises a plurality of lower triangular matrixes, and the lower triangular matrixes are arranged in the extended check matrix. The diagonal elements of each lower triangular matrix in the plurality of lower triangular matrixes are located on the diagonal of the expanded check matrix, the positions of the diagonal elements of the plurality of lower triangular matrixes are not overlapped, and the remaining elements in the expanded check matrix except the diagonal elements of the expanded matrix and the plurality of lower triangular matrixes are all 0 elements. According to the method, the column weight of the check area can be improved, the probability of error floor occurrence can be reduced, retransmission in some specific columns can be supported, and therefore the method can be compatible with an IR-HARQ scheme of LDPC codes of 5G.

The application discloses a method for calculating equivalent resistance based on a many-to-many mode, which comprises: filling a conductance matrix of a corresponding resistance network to obtain an extended matrix based on a node to be solved of an equivalent resistance, preordering the extended matrix to determine a permutation matrix P; performing LDL T decomposition on the extended matrix to calculate a lower triangular matrix L and a diagonal matrix D required for calculating the equivalent resistance and determining a non-zero element position in a sparse matrix F; calculating a matrix element of a target matrix Z according to the non-zero element position in the sparse matrix F and the lower triangular matrix L and the diagonal matrix D; and calculating the equivalent resistance according to the target matrix Z. For this purpose, the application does not need to solve all matrix elements, but only needs to calculate matrix elements consistent with the non-zero element position distribution of F, i.e. Z, so as to effectively reduce the calculation amount. Since Z is a sparse matrix and a general dense matrix, the total calculation amount is greatly reduced due to the fewer non-zero elements of Z.

The invention relates to a positioning method and device, electronic equipment and a computer storage medium. The method comprises the following steps: acquiring a variance-covariance matrix of a carrier phase observation value acquired by the positioning device; performing LD transformation on the matrix to obtain a lower triangular matrix and a diagonal matrix; and storing the effective elements in the lower triangular matrix and the effective elements in the diagonal matrix into the RAM, loading the effective elements in the lower triangular matrix and the diagonal matrix and the unit matrix from the RAM by adopting the DAM, and calculating according to the effective elements in the lower triangular matrix and the diagonal matrix and the unit matrix by adopting a decorrelation algorithm to obtain a positioning result. According to the method, only the effective elements in the lower triangular matrix and the diagonal matrix are stored, storage is reduced, reading and calculation are facilitated, meanwhile, the effective elements in the lower triangular matrix, the effective elements in the diagonal matrix and the unit matrix are stored in the RAM through the DAM, system control of a CPU is reduced, calculation power is increased, and efficiency is improved.

The embodiment of the invention discloses a matrix operation method and device, computer equipment and a storage medium, and belongs to the technical field of computers.The method comprises the steps that block processing is conducted on a transformation matrix to obtain a plurality of transformation blocks, and block processing is conducted on a triangular matrix to obtain a plurality of initial full-element blocks and a plurality of initial triangular blocks; obtaining a transposed full-element block corresponding to each initial full-element block, and obtaining a restored full-element block corresponding to each initial triangular block; according to a preset matrix block position index, determining restored full-element blocks and initial full-element blocks with block positions having an index row-column symmetric relationship, and transposing the full-element blocks into the same target processing group; and performing matrix operation on each transformation block and the processing block at the corresponding block position in the corresponding target processing group, and determining a target matrix operation result according to a matrix block operation result. According to the invention, the matrix operation efficiency, especially the matrix operation efficiency for the symmetric matrix, can be improved.

The application relates to the field of high-performance computing and computing power optimization, and relates to a method for accelerating triangular matrix multiplication based on an atlas 800 platform, which comprises the following steps: cutting a result matrix into multiple task blocks, and presetting an equal division strategy based on the multiple task blocks; generating a mask matrix on a vector calculation unit, and storing the mask matrix back to a global memory; reading the matrix and the mask matrix from the global memory, implementing triangular masking of the matrix by using the vector calculation unit, and obtaining a triangular matrix A after triangular masking; based on the triangular matrix A after triangular masking, calling a cube calculation unit to complete matrix multiplication operation of all the task blocks according to the preset equal division strategy, and obtaining a result matrix. The mix method combining the vector calculation unit and the cube calculation unit is used to complete the triangular matrix multiplication, the calculation efficiency of the triangular matrix multiplication on the NPU is improved, the computing power of the Huawei atlas 800 NPU can be fully utilized, the triangular matrix multiplication calculation is accelerated, and computing power support is provided for the fields of deep learning and scientific calculation.

A computer-implemented method for memory management in a computer system configured for generating a signature of a binary data message m using a key B of a predetermined lattice-based structure is proposed, which comprises: determining coefficients of a 2×2 signature generation matrix SG, wherein the non-diagonal coefficients of the signature generation matrix SG are complex polynomials with a non-zero imaginary part, and the diagonal coefficients of the signature generation matrix SG are real polynomials; and determining a LDL representation of the signature generation matrix SG according to which SG is represented by a matrix product L.D.L*, wherein L is a 2×2 lower triangular matrix with ones on the diagonal, D is a 2×2 diagonal matrix, and L* is the adjoint of L; wherein the storing in a memory buffer of the computer system of the coefficients of the signature generation matrix SG and the coefficients of the matrices of the LDL representation is managed based on that the signature generation matrix SG has real diagonal coefficients, and the memory buffer is used alternatively to store the coefficients of the signature generation matrix SG or the coefficients of the matrix D of the LDL representation.

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.

The application relates to a spacecraft precise orbit determination parallel processing method. The method comprises the following steps: opening a corresponding number of integral thread handles according to the number of spacecrafts; performing orbit integral calculation on the spacecrafts to obtain ephemeris data of the spacecrafts and save the ephemeris data; opening observation data processing thread handles with a preset number, dividing observation data of the spacecrafts into the preset number of thread blocks, and allocating an upper triangular matrix and a vector to each thread block; obtaining partial derivatives of to-be-solved parameters, differences between theoretical values and measured values of observation data according to the ephemeris data and the observation data in each thread block, and substituting the partial derivatives and the differences into Givens transformation to update the upper triangular matrix and the vector; performing Givens transformation on all the updated upper triangular matrices and vectors to obtain orbit confirmation results. The application can overcome the deficiency of the existing precise orbit determination system in the aspect of calculation efficiency when processing massive observation data.

The application discloses a running-in state identification method based on a friction signal threshold-free recursive analysis result, extracts nonlinear components of a friction signal time sequence output in a friction and wear process by collecting the friction signal time sequence; constructs a threshold-free recursive matrix by combining a sliding window and an avoidance embedding phase space reconstruction method and realizes visualization of the threshold-free recursive matrix in a two-dimensional plane; divides a lower triangular matrix of the threshold-free recursive matrix into several regions by a group of equidistant line segments parallel to a main diagonal line of the recursive matrix, extracts mean values of recursive elements in the regions, analyzes a change rate of element values of the threshold-free recursive matrix when the threshold-free recursive matrix transitions along the main diagonal line to edges and corners as a recursive measure, analyzes variation rules of the recursive measure along with a running-in and wear process, and further realizes running-in state online identification driven by the friction signal threshold-free recursive analysis result. The application optimizes a recursive characteristic representation and a measure extraction method of the friction signal time sequence, and realizes running-in state online identification from a perspective of dynamics-friction coupling.

The present application relates to a kind of optimal column ordering method and device of tide Jacobian matrix, wherein, method includes: the maximum non-zero element number of optimal pivot column in lower triangular matrix in Jacobian matrix decomposition process is calculated, and the non-zero element upper bound of optimal pivot column is obtained;With the same non-zero element structure of optimal pivot column, pivot row mode skip list and original row mode skip list are updated to empty set;The numerical value of each column number value corresponding to row mode counter in the non-zero element upper bound mode skip list of pivot row of the column number value pointed to by the column number value of optimal pivot column is updated, and the numerical value of pivot row mode counter and original row mode counter is obtained;The column metric value of each column number value in the non-zero element upper bound mode skip list of pivot row of the column number value pointed to by the column number value of optimal pivot column is updated and calculated.The present application can improve the response speed and effectiveness of power flow calculation.

The invention provides a parallel solving method of a chip dynamic power consumption model based on Cholesky decomposition, and the method specifically comprises the following steps: S1, receiving sparse symmetric positive definite matrixes, carrying out the matrix sorting, and constructing a chip power consumption model matrix; s2, rearranging sub-matrixes of the chip power consumption model matrix and constructing an elimination tree; s3, performing hierarchical cutting and sub-tree recursive splitting on the eliminated tree; s4, traversing the sub-tree set after recursive splitting, merging the sub-trees with the node number lower than a preset minimum threshold value, and generating a multi-diagonal-block matrix; s5, performing Cholesky decomposition on the multiple diagonal block matrixes in parallel to obtain a lower triangular matrix; s6, the diagonal blocks and the non-diagonal coupling blocks of the lower triangular matrix are recombined into an extended sub-matrix, an inverse matrix is solved step by step through a recursion method, and parallel solving of the diagonal block inverse matrix in the multi-diagonal-block matrix is achieved; s7, solving an inverse matrix of the multi-diagonal block matrix; and S8, carrying out parallel calculation on the Schur complement based on the inverse matrix of the multi-diagonal block matrix so as to realize the parallel solution of the chip power consumption model.

The application relates to a dynamic incremental calculation method of a power flow Jacobian matrix and a power imbalance, which redesigns a calculation flow of the Jacobian matrix, saves lower triangular admittance values of a target column to a circular queue, and dynamically updates power accumulation values to a diagonal line register, so that the time for searching an admittance matrix during calculation of a lower triangular matrix of the Jacobian is greatly shortened. The application realizes parallel pipeline dynamic incremental calculation of the Jacobian matrix and the power imbalance, and reduces the calculation time of a large-scale network Jacobian matrix and consumption of storage resources.

The invention provides an implementation method of a reconfigurable low-power-consumption triangular interleaver, and relates to the technical field of wireless communication, and the method comprises the steps: obtaining the number of rows and columns of an upper right-angle triangular matrix; constructing a column index counter, an address offset and a read address; writing the data stream according to a row sequence to obtain a write address of the data; the read addresses are progressively increased row by row, the initial values of the read addresses and the incremental quantity are equal to the row and column number of the matrix, and the value of the incremental quantity is progressively decreased along with the row number; and judging whether the data corresponding to the current address is valid during each reading, and skipping the address if the data corresponding to the current address is invalid. Through dynamic parameter calculation, the triangular interleaver with configurable parameters is realized, and the flexibility is high. Meanwhile, storage resource occupation is reduced, and power consumption is reduced.

The embodiments of the present disclosure relate to a method, apparatus and medium for inverting a triangular matrix. According to the method, the matrix of order 2 is inverted. n The inverse triangular matrix to be determined is stored in a shared memory; the triangular part of the inverse triangular matrix to be determined having non-zero elements is divided into a plurality of blocks of different orders, the plurality of blocks including a plurality of first to n+1th blocks, wherein each first block forms a first triangular matrix, and each mth block and two adjacent m-1th triangular matrices form an mth triangular matrix; and using the 2 included in the thread warp n The threads perform n+1 iterative inversion calculations in the order of the first triangular matrix, the second triangular matrix, and finally the n+1th triangular matrix to ultimately determine the inverse of the triangular matrix to be inverted. This can fully utilize the computing power of the thread warp and improve the computational performance of triangular matrix inversion.

The present application discloses a matrix inversion method and system for iterative calculation based on Cholesky decomposition, which relates to the field of DSP system optimization technology. The method includes obtaining a target source matrix; performing a first iterative process on the target source matrix based on Cholesky decomposition to generate an upper triangular matrix; performing a second iterative process on the upper triangular matrix to generate an inverse matrix of the upper triangular matrix; performing a conjugate transpose process on the inverse matrix of the upper triangular matrix to generate a lower triangular matrix; wherein the lower triangular matrix is ​​stored in the form of whole column storage; the storage mode of the inverse matrix of the upper triangular matrix is ​​converted into a sequential storage form; performing matrix multiplication process on the inverse matrix of the upper triangular matrix and the lower triangular matrix to generate the inverse matrix of the target source matrix. The present application replaces cumulative summation with iteration, adopts complex multiplication and addition optimization calculation, supports multi-parallel operation, parallelizes zero-filling operation, can adapt to general matrix multiplication module, and reduces calculation time and area overhead.

Embodiments of the present application disclose a data processing method and device, computer equipment and program product, and belong to the technical field of big data. In the embodiments of the present application, after obtaining a target coefficient matrix and a target constant matrix corresponding to a target triangular matrix equation set to be solved, the inverse matrix of each sub-triangular matrix included in the target coefficient matrix is determined through a matrix inversion algorithm. Subsequently, the solution of the target triangular matrix equation set can be directly determined through a matrix multiplication algorithm according to the inverse matrix of each sub-triangular matrix and the target constant matrix. The scheme is not only suitable for the scenario where the scale of the coefficient matrix is large, but also the entire solving process can be realized through matrix operations, so that the efficiency of solving the target triangular matrix equation set is improved, and the computing power of the processor is improved.

The invention relates to the field of clinical nursing, in particular to a diabetic complication risk detection system based on artificial intelligence, which comprises a data acquisition module, a data preprocessing module, a complication risk feature extraction module, a complication risk prediction module and an intelligent feedback module. A positive definite execution layer is introduced, the output of a time sequence is converted into a lower triangular matrix, a positive definite covariance matrix is generated through Cholesky decomposition, the correlation and uncertainty of input data are further quantified, meanwhile, a lawny eagle algorithm is designed, and by simulating attack and migration behaviors of the lawny eagle, the time sequence of the lawny eagle is calculated. And the search direction is dynamically adjusted by combining the actual parts and the virtual parts of the plurality of individuals, so that the global search capability and the local development capability are improved.