107 results about "Permutation matrix" patented technology

According to one aspect, the present disclosure provides a decoder. The decoder may include a posterior probability storage module that stores a posterior probability message respectively corresponding to each of a plurality of cyclic permutation matrices. The decoder may include a node message storage module that stores a message transmitted to a variable node by a check node respectively corresponding to each of the plurality of cyclic permutation matrices. The decoder may include a message updating module that sequentially receives the posterior probability message and the message transmitted to the variable node by the check node respectively corresponding to each of the plurality of cyclic permutation matrices in a first order, and sequentially outputs the updated message transmitted to the variable node by the check node and an updated posterior probability message respectively corresponding to each of the plurality of cyclic permutation matrices in a second order.

Certain aspects of the present disclosure provide techniques for selecting a first orthogonal cover code (OCC) codeword from an OCC matrix for a transmission occurring during a first transmission time interval based on a first pseudo-random codeword allocator function, such as a first pseudo-random permutation matrix, corresponding to the first transmission time interval; and sending the transmission during the first transmission time interval using the first OCC codeword.

The invention relates to the technical field of information fusion, in particular to a robust filtering method for solving uncertainty of one-step random observation time delay, which comprises the following steps of: taking multiplicative noise, one-step random time delay, data packet loss, continuous loss observation and uncertain noise variance which are dependent on a system state and a state in an observation matrix into consideration; specifically, based on a maximum and minimum robust estimation principle, a CI fusion Kalman estimator (a predictor, a filter and a smoother) and two FCI fusion Kalman estimators are provided. According to the method, an augmentation method and a virtual noise method are combined, a robustness proving method based on permutation matrixes and a Lyapunov equation is introduced, it is proved that the proposed fusion estimator has robustness by defining different permutation matrixes, and in addition, through an application example of autoregressive moving average signal processing, the robustness of the fusion estimator is improved. It is verified that the robust local and fusion signal estimation problem can be solved through the state estimation method, and therefore solid practical application support is provided for the system modeling result.

The invention discloses a safe reasoning method and device of a model, electronic equipment and a storage medium, and relates to the technical field of model privacy reasoning. In the security reasoning method, a cloud platform cannot obtain a parameter set of a model based on each hidden parameter set; the cloud platform cannot obtain the original reasoning data based on the second hidden reasoning; and the user side performs recovery reconstruction processing based on the first permutation matrix, the first reasoning result and the second reasoning result to obtain a target reasoning result. A user side cannot obtain a parameter set of the model, so that the user side cannot obtain privacy of a model developer side. According to the method, the original reasoning data and the parameter set of the model do not need to be converted into the ciphertext by adopting a traditional protocol, and the parameter set of the model and the randomly generated permutation matrix are subjected to matrix multiplication processing, so that the calculation and communication overhead caused by ciphertext calculation is saved, the processing speed is higher, and the communication overhead is smaller.

The embodiment of the invention provides a privacy-protecting data providing and querying method and device.In the data providing method, in the preparation stage, a server receives first encrypted data from a client side, and the first encrypted data is obtained by conducting homomorphic encryption on an n * n-dimensional permutation matrix corresponding to a preset permutation rule. According to a first plaintext sequence formed by n pieces of plaintext data held by the server and the first encrypted data, a ciphertext sequence formed by n pieces of first ciphertext is obtained, the ciphertext sequence corresponds to a second plaintext sequence, and the second plaintext sequence is equal to a plaintext sequence obtained by replacing the first plaintext sequence based on a preset replacement rule. In the query stage, the target position of the target data to be queried is received from the client side, and the target position is the position obtained after the original position of the target data is subjected to replacement operation based on the preset replacement rule. And reading the target ciphertext of the target position from the ciphertext sequence, and sending the target ciphertext to the client.

The invention provides a privacy protection decision tree model reasoning method based on partial homomorphic encryption, and relates to the technical field of data privacy protection, and the method comprises the steps: obtaining to-be-predicted sample data, carrying out the preprocessing of each participant, and converting a ciphertext permutation matrix into a secret share matrix; performing bit decomposition on the to-be-predicted sample data to obtain a decomposition matrix, selecting an input sharing mode of the decomposition matrix according to the source of the to-be-predicted sample data, and then converting the input obtained decomposition matrix into a secret sharing share form; each participant performs comparative calculation by using the secret sharing share and the threshold share, evaluates Boolean functions of all leaf nodes to obtain indication result vectors, and randomly arranges the indication result vectors by using a secret share matrix to generate comparative result shares; and each participant constructs a vector pointing to a prediction output leaf node by using the comparison result share to obtain a prediction result, and outputs the prediction result to the sample data provider according to the to-be-predicted sample data source.

The invention provides a longitudinal federated lifting tree method for privacy protection, and relates to the technical field of longitudinal federated learning. The method comprises the following steps: combining a secretly shared binary matrix and gradient information to obtain a shared matrix and secretly sharing the shared matrix; each training terminal performs row permutation on the sharing matrix based on the permutation triad and secretly shares a permutation result; the linear gain scores of the candidate split are calculated cooperatively and shared secretly, and the indication vector of the split corresponding to the maximum linear gain score is calculated; according to the candidate split number, selecting corresponding columns and indication vectors from the matrix to calculate sub-node samples and a permutation matrix of sub-nodes; and recursively executing a calculation splitting step, completing splitting from the root node to the leaf node, calculating the weight of the leaf node, and storing the weight into a preset set. Updating the binary permutation matrix of the root node of the next decision model based on the leaf node weight, and continuing calculation until all decision tree models are generated; the problem that an existing longitudinal federated gradient boosting tree protocol is low in efficiency can be solved.

The invention belongs to the technical field of underwater acoustic array signal processing, and particularly relates to an acoustic vector circular array orientation estimation method based on cross covariance matrix construction, a program, equipment and a storage medium. The method comprises the following steps: introducing a preprocessing matrix to transform the output of an acoustic vector circular array, and constructing a cross covariance matrix of sound pressure and different vibration velocity components according to the transformed vector; combining and arranging the cross covariance matrixes of the sound pressure and the different vibration velocity components to obtain a combined arrangement matrix; performing singular value decomposition on the combined permutation matrix, and reconstructing a cross covariance matrix by using a unitary matrix formed by left singular vectors of the combined permutation matrix and a diagonal matrix formed by singular values; and implementing a spatial spectrum estimation method by using the cross covariance matrix, and taking the scanning angle corresponding to the maximum value in the spatial spectrum as an orientation estimation result of the detection target. The method is suitable for a column barrier condition, and can effectively improve the dual-target resolution and orientation estimation performance of the acoustic vector circular array under a low signal-to-noise ratio condition.

Various aspects of the present disclosure relate to receiving (1502) a polar codeword comprising a set of bits and generating (1504) a permuted vector based at least in part on the polar codeword and a permutation matrix. Aspects of the disclosure may relate to determining (1506) a plurality of polar subcodes based on the permuted vector, and identifying (1508), for each polar subcode of the plurality of polar subcodes, a set of kernels, where each kernel of the set of kernels is associated with a bit pattern of a set of one or more bit patterns. Aspects of the disclosure may relate to decoding (1510) the plurality of polar subcodes using a plurality of parallel polar code component decoders, where each parallel polar code component decoder includes one or more fast decode modules to decode a corresponding kernel of the set of kernels.

A method for constructing a permutation matrix or a check matrix, a processing device, a storage medium and a coding method. The method for constructing the permutation matrix comprises: obtaining a base matrix for the permutation matrix; and performing lifting on the base matrix to obtain the permutation matrix. The lifting on the base matrix to obtain the permutation matrix comprises: obtaining a modulus graph of the base matrix, obtaining each macro ring in the modulus graph, and for each macro ring in the modulus graph, determining the size of a short ring corresponding to the macro ring in a Tanner graph of a check matrix corresponding to the permutation matrix from an equivalent cycle value ECS of the macro ring, and determining whether at least one cycle value in the macro ring needs to be set according to the size of the short ring. The method can more efficiently obtain a required permutation matrix.

The invention discloses a high-performance decoding method for quantum low-density parity check codes, and belongs to the technical field of quantum computing. Comprising the following steps: solving a transformation matrix and a permutation matrix through a matrix decoupling strategy optimized by an off-line satisfiability modulus theory, and equivalently transforming an original check matrix into a diagonal block matrix and any sparse matrix; the method comprises the following steps: decomposing an error mode into a left error corresponding to a diagonal block matrix and a right error corresponding to any sparse matrix through an online hierarchical greedy decoding algorithm, guessing an error bit of the right error, and then calculating an error symptom corresponding to the left error based on any sparse matrix; then the error symptom is divided according to the diagonal block matrixes for parallel decoding, decoding results of all the block matrixes are combined to form a left error, and finally the left error and the right error are spliced to obtain a complete error mode. According to the method, accurate and real-time decoding of the qLDPC code can be realized, and the method is applied to the frontier fields of quantum communication, quantum calculation and the like.

The present invention relates to the field of cloud computing security technology, and specifically to a searchable encryption method for hiding search modes and access modes in an e-commerce platform, including obtaining a data source, an initialization phase, and ciphertext retrieval. First, data is obtained from a public data set; the initialization phase includes extracting the relationship between keywords and documents, constructing an index matrix and an auxiliary data structure, and generating relevant keys. The ciphertext query phase includes: the user generates a search trap for the query keyword and sends it to the server; the server retrieves the secondary mapping according to the search trap, obtains the search range, and retrieves the corresponding data block sequence; the user constructs a permutation matrix, and encrypts and uploads it to the server, and performs homomorphic calculations with the index matrix on the server side to change the position of the data in the index matrix. The present invention integrates secondary search and homomorphic encryption technology into the field of searchable encryption, ensuring user privacy while achieving efficient and secure search, and has important application value for user privacy protection and information retrieval.

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 aspects of the present disclosure provide techniques for selecting a first orthogonal cover code (OCC) codeword from an OCC matrix for a transmission occurring during a first transmission time interval based on a first pseudo-random codeword allocator function, such as a first pseudo-random permutation matrix, corresponding to the first transmission time interval; and sending the transmission during the first transmission time interval using the first OCC codeword.

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 the technical field of wireless communication, in particular to a low-complexity signal detection method of an MIMO-OTFS system, which comprises the following steps: setting a grouping symbol number according to a channel condition, and calculating a maximum iteration number; in each iteration: calculating a filtered received signal through the channel matrix and the received signal; constructing a matrix psi, processing a structure matrix psi S of the matrix psi by adopting an RCM algorithm to obtain a permutation matrix, and calculating a reordering matrix according to the permutation matrix; performing Cholesky decomposition on the reordering matrix to obtain a banded matrix; calculating the SINR of each symbol which is not detected at present; all symbols which are not detected at present are arranged in a descending order according to the SINR size, the first S symbols in the sorting result are taken to be detected one by one and output, and the channel matrix and the received signal are updated; judging whether the maximum iteration number is reached or not, and if not, continuing the next iteration; according to the method, the time complexity is reduced while the bit error rate performance is ensured through an iterative strategy of reliability symbol detection and interference elimination.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a UE may receive, from a network node, one or more reference signals associated with measurement of a signal quality associated with a transmission channel. The UE may transmit, to the network node, a channel state information report that includes precoder information indicative of a geometric mean decomposition precoder associated with the transmission channel and includes first information associated with one or more Givens rotation matrices and second information associated with one or more permutation matrices. Numerous other aspects are described.

The application relates to the field of natural language processing, and discloses a cross-language entity alignment method and system based on relationship semantic enhancement, which comprises the following steps: constructing entity initial embedding and relationship embedding representation of a cross-language knowledge graph; a key neighbor screening stage; screening key neighbor entities with structural matching and semantic matching based on an entity similarity matrix and a relationship similarity matrix and in combination with a preset semantic correlation threshold; neighbor-enhanced entity embedding updating; adopting a graph attention network to fuse semantic features of target entities and key neighbors thereof, and generating context-aware entity embedding; semantic consistency alignment propagation: first-order entity feature alignment and second-order relationship structure alignment are jointly optimized through a shared permutation matrix; dynamic seed expansion iteration: high-confidence unaligned entity pairs are dynamically identified according to Manhattan distances of entity embedding, entity pairs with distances lower than a threshold are added to a seed set, and the foregoing steps are iteratively executed until convergence.

A method, computer program product, and computer system for identifying, by a computing device, a plurality of information associated with a telemetry system. A permutation matrix may be constructed for use with the telemetry system. One or more parameters for use in the permutation matrix may be extracted based upon, at least in part, the plurality of information associated with the telemetry system. A plurality of iterations may be performed with the permutation matrix based upon, at least in part, the one or more parameters extracted for use in the permutation matrix. A final telemetry geometry may be provided for the telemetry system.

This specification provides a privacy-protecting data provision and query method and apparatus. In the data provision method, during the preparation phase, the server receives first encrypted data from the client. This first encrypted data is obtained by homomorphically encrypting an n*n-dimensional permutation matrix corresponding to a predetermined permutation rule. Based on a first plaintext sequence consisting of n plaintext data held by the server and the first encrypted data, a ciphertext sequence consisting of n first ciphertexts is obtained. This ciphertext sequence corresponds to a second plaintext sequence, which is equivalent to the plaintext sequence obtained by permuting the first plaintext sequence based on the predetermined permutation rule. During the query phase, the server receives the target location of the target data to be queried from the client. This target location is the position after performing a permutation operation on the original position of the target data based on the predetermined permutation rule. The target ciphertext of the target location is read from the ciphertext sequence and sent to the client.

The invention relates to the technical field of digital signature, in particular to a digital signature method based on QC-MDPC and pad filling, which comprises the following steps: acquiring an object to be digitally signed; qC-MDPC is adopted as private key coding, and a private key is designed by using a parity check matrix, a reversible permutation matrix, a disturbance matrix and a hash function; designing a public key by using the parity check matrix and the reversible permutation matrix; performing hash operation on the digital signature object to obtain a message digest; carrying out random length selection on the message digests, and multiplying the randomly selected message digests by the disturbance matrix to obtain a message sequence; performing pad filling on the message sequence until a BF decoding condition and a signature condition are met, completing digital signature construction, and sending a signature to a verifier; and verifying the signature by using the message sequence and the public key. The method has the advantages of being small in public key storage space, low in encryption and decryption complexity, high in safety and high in speed, and has important significance in the field of cryptography research of quantum attack resistance.

The present invention discloses a method for identifying vulnerable nodes of an active distribution network taking into account the influence of new energy sources. The method samples a pre-constructed DG random output model and a load random model, obtains random output data of new energy sources and loads, determines a random output matrix based on the random output data, arranges the random output matrix, and obtains an arrangement matrix that minimizes the correlation of each random variable sampling value; inputs the data in the arrangement matrix into a pre-constructed node vulnerability index evaluation system model to obtain a node comprehensive vulnerability index; and uses a three-parameter interval number sorting method based on a Boolean matrix combined with a node comprehensive vulnerability index to identify vulnerable nodes. Advantages: The present invention can accurately and quickly identify vulnerable nodes in a power grid while taking into account the access of new energy sources to the distribution network, and effectively evaluate the vulnerability of the distribution network, which is beneficial for power grid operators to fully and deeply grasp the safety status of the distribution network and eliminate or mitigate the risks caused by vulnerability.

The implementations of present disclosure provides a coder, based on the way of updating the message by way of using inter-block serial coding for a plurality of cyclic permutation matrices in a layer of a check matrix corresponding to a frame of code words, the coder includes: a posterior probability storage module configured to: store the posterior probability message respectively corresponding to each of the cyclic permutation matrices; a node message storage module configured to: store a message transmitted to a variable node by a check node respectively corresponding to each of the cyclic permutation matrices; and a message updating module configured to: sequentially receive the posterior probability message and the message transmitted to the variable node by the check node respectively corresponding to each of the cyclic permutation matrices in a first order, and sequentially output the updated message transmitted to the variable node by the check node and updated posterior probability message respectively corresponding to each of the cyclic permutation matrices in the second order; wherein the first order is the same as or different from the second order.

The present invention discloses a video image behavior prediction method, system, device and storage medium, relating to the field of artificial intelligence technology. The training method includes constructing undirected graph data for each frame of image according to the labeled nodes of each frame of image; arranging the order of the labeled nodes of the undirected graph data according to the permutation matrix to obtain observed image data; inputting the sequence of observed image data based on the video time sequence into the Kalman filter prediction sub-model to obtain a sequence of predicted image data, and correcting the sequence of predicted image data according to the sequence of observed image data; inputting the sequence of predicted image data into the Kalman smoothing sub-model to obtain a sequence of smoothed image data; updating the prediction parameters and correction parameters of the prediction sub-model according to the sequence of smoothed image data and the sequence of observed image data until the prediction parameters and correction parameters converge, so as to obtain a video behavior prediction model. The present invention can train an accurate video behavior prediction model when the video image data is incomplete or the labels are chaotic.

The invention discloses a human-computer interaction feature mining-based prediction method, which comprises the following steps of: inputting cue words and original data, extracting original features through GPT-4, constructing an input matrix X, mapping the input matrix X to a uniform embedding layer, completely exposing an association mode among all the original features by using a double-line attention mechanism, and extracting the original features by using the correlation mode. Local and global original features are efficiently sampled through a permutation matrix and a double-branch lightweight convolutional network, correlation mining of cross-modal and / or multi-source heterogeneous features of the original features is achieved, and finally feature fusion and feature extraction are conducted through a multi-layer perceptron connected through residual errors. Classification and fitting tasks of multi-modal and multi-source heterogeneous data can be well processed, and the prediction accuracy is improved.

A radiation source number estimation method suitable for an unmanned aerial vehicle array direction-finding system comprises the following steps: receiving observation signals through an antenna array, and calculating a covariance matrix of the observation signals; presetting the number of information sources, constructing a smoothing matrix containing a permutation matrix, and smoothing the covariance matrix based on the smoothing matrix to obtain a smoothed covariance matrix; performing information source number estimation on the smoothed covariance matrix based on an eigenvalue entropy calculation method to obtain an information source number estimation result; and arranging the information source number estimation results in an inverted order, and judging the monotonicity of the inverted sequence after the inverted order arrangement. According to the method, a new signal source number estimation scheme in array DOA estimation is provided, and due to the fact that the number of needed signal sampling points is very small, the method is suitable for signal source number estimation of an unmanned aerial vehicle array direction finding system under the conditions that received signals are small samples, aliasing color noise exists in observation signals and coherence exists in incident signals.

The invention provides a memristor-based fixed-point matrix FFT (Fast Fourier Transform) calculation method, which belongs to the technical field of signal processing and image processing, and comprises the following steps of: firstly, constructing a non-linear voltage controlled memristor model, simulating a state conversion behavior in logic operation through a dynamic regulation mechanism, and realizing the function of a basic logic gate; according to the method, an FFT algorithm based on matrix block optimization is designed, FFT calculation is decomposed into small-scale matrix operation units, calculation efficiency is optimized in combination with a Kronecker product and an arrangement matrix, FFT operation with higher point number is expanded in a recursion mode, meanwhile, a full adder and a multiplier are designed based on a memristor, efficient fixed-point number operation is achieved, and finally, the FFT calculation efficiency is improved. The method is applied to image FFT processing, and a processing result is obtained. The scheme of the invention has higher calculation efficiency and lower energy consumption while ensuring the calculation precision, can be widely applied to the fields of image processing, signal analysis, scientific calculation and the like, and has important practical value and application prospect.

The invention discloses an electronic voting casual shuffling method based on semi-trusted hardware, trusted execution environments of a first participant and a second participant are mutually verified through a remote authentication protocol, and after authentication is passed, the trusted execution environments of the first participant and the second participant negotiate to generate a shared random seed; constructing a permutation matrix based on the random seeds and the trusted execution environments of the two participants, generating a secret share of the permutation matrix, and sending the secret share to the corresponding participants according to a distribution rule of copy secret sharing; the voter generates a secret share of voting data by using the trusted execution environment of each participant, and sends the secret share to the corresponding participant according to a distribution rule of copy secret sharing; and the two participants respectively use the locally held voting data and the secret share of the permutation matrix to carry out casual shuffling calculation, and the secret share of the position permutation voting data is obtained and disclosed, so that any third party can obtain a voting result after casual shuffling through the secret share of the position permutation voting data.

Certain aspects of the present disclosure provide techniques for selecting a first orthogonal cover code (OCC) codeword from an OCC matrix for a transmission occurring during a first transmission time interval based on a first pseudo-random codeword allocator function, such as a first pseudo-random permutation matrix, corresponding to the first transmission time interval; and sending the transmission during the first transmission time interval using the first OCC codeword.

The present application discloses a method for calculating the equivalent resistance between nodes in a resistor network, which includes: determining the admittance matrix G of the resistor network; converting the admittance matrix into a non-singular matrix #imgabs0# based on the permutation matrix P; performing LDL on the non-singular matrix #imgabs1# T Decompose and obtain the lower triangular matrix L with diagonal 1 and its elimination tree, diagonal matrix D; determine the equivalent resistance R to be calculated in the resistor network ij Node i, node j, and the standard unit vector e corresponding to node i i , the standard unit vector e corresponding to node j j With the permutation matrix P and the lower triangular matrix L, establish the equation group to be solved LXi=P T e i , LX j =P T e j , X i 、X j is the solution of the system of equations to be solved; based on the elimination tree, determine the solution X of the system of equations to be solved i 、X j The non-zero position of ; based on the solution of the equation system X i 、X j The non-zero position of the equation to be solved is calculated i 、X j ; Based on the solution X of the system of equations to be solved i 、X j And the diagonal matrix D, calculate the equivalent resistance R between node i and node j ij .