9 results about "Permutation matrix" patented technology

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.

Certain example embodiments may relate to a 5G and / or 6G communication system for supporting higher data transmission rates than 4G communication systems such as LTE. A method performed by a transmitter in a communication system, which method may include: determining the number of input bits; determining a base matrix on the basis of the number of input bits; determining a lifting size (Z) on the basis of at least one of the number of input bits or the base matrix; determining a parity check matrix on the basis of at least one of the base matrix or the lifting size (Z); and performing encoding on the basis of the parity check matrix and the input bits. The size of the parity check matrix is Z×(k+1) Z, the last column block of the parity check matrix corresponds to parity bits, a Z×kZ column block of the parity check matrix corresponds to information word bits, all of modulo-Z values of differences in cyclic shift values corresponding to circulant permutation matrices constituting a Z×Z circulant matrix are different, and all of the circulant matrices corresponding to the information word bits are composed of three or more circulant permutation matrices.

This invention relates to the field of mine safety monitoring technology, specifically disclosing a method for deploying mine fire monitoring sensors. The method includes: establishing a three-dimensional model; acquiring fire smoke propagation data through numerical simulation to construct an original spatiotemporal concentration matrix; extracting threshold response time feature vectors and maximum time-varying gradient feature vectors from the original spatiotemporal concentration matrix; performing nonlinear logarithmic mapping and centering on the original spatiotemporal concentration matrix, and constructing a spatial feature basis matrix through singular value decomposition; concatenating the spatial feature basis matrix, threshold response time feature vectors, and maximum time-varying gradient feature vectors, introducing feature weight penalty coefficients, and constructing an augmented feature matrix; performing orthogonal triangular decomposition with column pivot selection on the transpose of the augmented feature matrix, and determining the optimal monitoring point based on the row index of the permutation matrix, thereby achieving effective monitoring and early warning of the initial stage of a fire. This improves the ability to capture low-concentration signals in the initial stage of a fire and the accuracy of reconstructing the overall concentration field.

A discrete cosine transform processing device includes an adder, a register, multiple multiply-accumulate operation circuits, an accumulator, an operation control circuit and an output circuit. The adder processes first input data based on a first permutation matrix to generate second input data. The register stores an operation matrix. The operation control circuit configures the multiply-accumulate operation circuits and the accumulator based on a matrix multiplication operation corresponding to a unit dimension, such that the operation matrix and the second input data are multiplied and accumulated by the multiply-accumulate operation circuits and the accumulator to generate a first operation result. The output circuit processes the first operation result based on a second permutation matrix to generate a second operation result, wherein the first permutation matrix, the operation matrix, and the second permutation matrix are derived from decomposition of a discrete cosine transform matrix.

This invention proposes a reconfigurable metasurface beamforming design method based on CGAN and Gumbel-Sinkhorn. This method constructs a conditional generative adversarial network (GAN) as the inverse design network. The generator takes the target beam pattern as a conditional input to generate the corresponding encoding matrix. The Gumbel-Sinkhorn operator is introduced to discretize this continuous matrix, transforming it into an approximately doubly random permutation matrix. The encoding is sorted and selected by multiplying this permutation matrix with a predefined structure vector (SV), outputting a discrete 0 / 1 metasurface encoding array. A noisy forward prediction network is trained to predict the beam pattern corresponding to a given encoding array. In the training of the inverse design network, the discretized encoding matrix output by the generator is input into the noisy-trained forward prediction network. The mean square error between the predicted beam pattern and the target beam pattern is calculated as the target loss term to optimize the network parameters and accurately learn the complex mapping relationship from the beam pattern to the encoding array.

This invention relates to the field of medical informatics and medical data processing technology, and discloses a standardized storage method for airway stenosis treatment data. By converting a three-dimensional medical image of the airway into a topological graph, and sequentially constructing an adjacency matrix, a node attribute matrix, and an edge attribute matrix, the multidimensional structural features of each node are calculated, and a standardized permutation matrix is ​​generated through normalized sorting. Then, a unified standardized structural encoding vector is formed through rearrangement and vectorization concatenation. Standardized storage records are generated by combining patient identification and time, and fingerprint verification is performed. This solves the problems of incomplete preservation, difficulty in retrieval, and easy loss of context in traditional clinical data storage. This method restores the structure without secondary reconstruction through matrix and vectorization processing; unified sorting eliminates differences in node order among different cases; the high-dimensional encoding after vectorization saves storage space and is compatible with vector retrieval libraries; and fingerprint verification ensures data integrity and security.

This invention discloses a traffic flow prediction method based on graph serialization and bidirectional state space. First, a spatiotemporal graph of traffic flow is constructed. Topological features of nodes are extracted using a graph attention network, and a double-random permutation matrix reflecting the optimal traversal path is generated through a differentiable relaxation sorting operator, adaptively mapping the two-dimensional graph structure data to one-dimensional serialized features. Then, a bidirectional gated state space model is constructed, and the serialized features are recursively scanned from both the forward and reverse directions using discretized state space parameters, and a hybrid hidden state is obtained through fusion using gated units. Finally, the transpose of the permutation matrix is ​​used to perform an inverse transformation on the hybrid features to restore the spatial structure, and the future traffic flow is output through a prediction head. This invention effectively solves the problem that traditional state space models struggle to handle graph structure data, achieving end-to-end joint optimization of the graph traversal strategy and the prediction model, significantly improving the accuracy and efficiency of long-sequence traffic prediction.