91 results about "Square matrix" patented technology

The invention discloses an information security assessment method and system based on cloud computing, and relates to the technical field of information security, and the method comprises the steps: collecting multi-modal data, and carrying out the encryption through employing a node identifier, and generating a spatio-temporal data package; the method comprises the following steps: aggregating threat features by utilizing secure multi-party calculation through edge nodes, constructing a 58-dimensional square matrix, constructing a risk assessment model based on a quantum heuristic algorithm, positioning root cause threats by applying a Do-Calculus algorithm, dynamically adjusting and optimizing model weights by federal reinforcement learning, and outputting threat vectors to a cloud causal engine; the method comprises the following steps: constructing a space-time causal diagram by combining threat intelligence, positioning root cause threats by applying a Do-Calculus algorithm, generating a dynamic defense strategy, optimizing access control by KL divergence constraint, locally encrypting and storing a strategy execution log, and generating an evaluation audit log. According to the method, the problems of insufficient cloud computing multi-modal data relevance, defense lagging and verification fault are solved, and collaborative crossing of evaluation precision and response efficiency is realized.

Predictive uncertainty of a generative machine learning model may be estimated. The generative machine learning model may be a large language model or large multi-modal model. A datum may be input into the generative machine learning model. The generative machine learning model may generate outputs from the datum. Latent embeddings for the outputs may be extracted from the generative machine learning model. A covariance matrix with respect to the latent embeddings may be computed. The covariance matrix may be a two-dimensional matrix, such as a square matrix. The predictive uncertainty of the generative machine learning model may be estimated using the covariance matrix. For instance, the matrix entropy of the covariance matrix may be determined. The matrix entropy may be an approximated dimension of a latent semantic manifold spanned by the outputs of the generative machine learning model and may indicate the predictive uncertainty of the generative machine learning model.

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

A method with a number-theoretic transform (NTT) operation includes allocating an element of a matrix to a data lane such that elements in a first column of the matrix corresponding to a polynomial are allocated to the data lane of a first lane group among lane groups, wherein the matrix is a square matrix, and a number of elements comprised in the matrix is N, performing a first NTT operation on a data lane of a fourth root of the N for each of the lane groups, allocating a result of the first NTT operation to the data lane such that the matrix is transposed, based on adjustment of a reading order of a buffer that stores the result of the first NTT operation, and performing a second NTT operation on the data lane of the fourth root of the N for each of the lane groups.

The invention relates to the technical field of heat conversion flow distribution, in particular to a self-adaptive flow distribution method and device for a double-pipe heat exchanger, and the method comprises the following steps: S1, equipment assembly: installing a plurality of groups of flow pipes in the middle of a shell, and installing two groups of flow adjusting assemblies on one side of the input end of each of the plurality of groups of flow pipes; s2, arranging a plurality of groups of flow tubes in the shell in an annular matrix or a square matrix, establishing a plane-coordinate system by taking the center of the matrix as a coordinate origin, and numbering and marking each flow tube; s3, flow grade judgment; according to the scheme, the flow grade of the flow pipe is determined, the higher the flow grade is, the faster the flow speed is and the larger the flow is, then the flow channel area of the high-grade flow pipe is adjusted to decelerate and reduce the flow, the redundant quantity is distributed to the low-grade flow pipe, and it is guaranteed that the flow speed and the flow difference value of all the flow pipes are smaller than the set threshold value through comprehensive adjustment. Therefore, the effect of reasonable flow distribution is achieved, and the thermal conversion efficiency is improved.

The invention relates to the technical field of medical information security, and discloses a patient privacy data protection method used in an operating room. The method comprises the following steps: uniformly coding patient privacy into a binary system, zero-filling the binary system into a square matrix, and filling according to rows; a disturbance seed is generated through combination of operating room environment temperature and noise quantification, and chaotic mapping is driven to carry out two-dimensional replacement on a matrix; applying position-related mask XOR to the sub-blocks, and overturning odd columns or even rows according to global parameters; and then linearization is carried out according to rows and filling is eliminated, and a final ciphertext is output. Meanwhile, disturbance control parameters are constructed and bound, and then Hash check is calculated and structured packaging is carried out. Through global and local double-layer disturbance, field seed driving and reversible coding, the scheme enhances the resistance to statistical analysis, plaintext attack and replay attack on the premise of no fixed key, and gives consideration to real-time performance, security and traceability.

The invention provides a distribution line fault positioning precision self-correction method based on a digital twin model, and the method comprises the steps: independently constructing a virtual branch of a parallel admittance structure for each phase for each measurement point node of the digital twin model, and initializing the admittance vectors of all virtual branches; obtaining a three-phase current measured value of the distribution line, a three-phase voltage amplitude measured value and a power measured value of each measuring point node, and a corresponding power theoretical value in the digital twinborn model; obtaining a residual vector between the power measured value and the power theoretical value; assigning a division result of the residual vector and the voltage amplitude square matrix to an admittance vector; and acquiring the virtual power of each virtual branch according to the admittance vector, and correcting the admittance parameter of the distribution line in the digital twinborn model according to the current measured value. According to the method, the digital twin model can continuously and automatically track parameter changes of a physical system through a closed-loop correction mechanism, and the precision and reliability of fault positioning based on the model are ensured.

The invention provides an energy storage system black start method and system based on hierarchical control, and the method comprises the steps: carrying out the secondary frequency modulation and voltage regulation of a collected common voltage at a station control layer, so as to obtain a regulation variable, and transmitting a starting instruction, an off-grid mode enabling instruction and the regulation variable to a square matrix layer; a master matrix and a slave matrix are determined, the master matrix is controlled to perform black start, the master matrix is converted into an off-grid state after black start succeeds, and the black start of the master matrix comprises power loop control and voltage outer loop control performed by the master matrix and current inner loop control of an energy storage converter layer; controlling in-station alternating current bus voltage from grid connection of the square matrix to construction of the main square matrix, and converting into an off-grid state after grid connection is completed; and after receiving the off-network state information of the master square matrix and the off-network state information of the slave square matrix, the station control layer is switched into an off-network state, and the black start of the energy storage system is completed. According to the method, hierarchical control is carried out on the system, the advantages of serial recovery and parallel recovery are combined, and the stability of the system is ensured while the black start speed of the system is increased.

Matrix multiplication operations can be implemented, at least in part, on one or more tensor cores of a parallel processing unit. An efficiency of the matrix multiplication operations can be improved in cases where one of the input operands or the output operand of the matrix multiplication operation is a square matrix having a triangular data pattern. In such cases, the number of computations performed by the tensor cores of the parallel processing unit can be reduced by dropping computations and / or masking out elements of the square matrix input operand on one side of the main diagonal of the square matrix. In other cases where the output operand exhibits the triangular data pattern, computations can be dropped or masked out for the invalid side of the main diagonal of the square matrix. In an embodiment, a library implementing the matrix multiplication operations is provided.

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.

The invention belongs to the technical field of machine learning and data mining, and particularly relates to a large-scale high-dimensional image data set-oriented compressible subspace clustering method, which comprises the following steps of: firstly, designing a dictionary representation learning model based on a partitioning mechanism to select part of samples to construct a small-scale dictionary to replace the whole original data; a bipartite graph construction method is ingeniously introduced by utilizing the thought of joint clustering, the problem that the bipartite graph cannot be directly constructed due to the fact that a coefficient matrix is not a square matrix is solved, and the relevance between a dictionary sample and a new input data sample can be fully considered. Under the Laplacian matrix rank constraint of the combination graph, the method can directly learn to obtain an optimal structured bipartite graph, can directly obtain a final clustering result, and does not need any post-processing process. In addition, an efficient optimization algorithm based on alternate iteration is further designed in combination with an augmented Lagrangian multiplier method to solve the model.

The invention relates to the technical field of planar motors, in particular to a stator unit for a moving magnetic planar magnetic suspension motor and the motor. The stator unit comprises a plurality of basic units, the first coil unit, the second coil unit and the position sensor unit in each basic unit form an n * n square matrix, and n is an integer greater than 1; the first coil units and the position sensor units on any odd-numbered rows or odd-numbered columns of the n * n square matrix are alternately arranged; the position sensor units and the second coil units are alternately arranged on any even-numbered rows or even-numbered columns of the n * n square matrix, and the coil direction of the first coil units is perpendicular to the coil direction of the second coil units. The motor comprises the stator unit, and the stator unit and the motor break through the constraint of a traditional cable, replace a laser interferometer scheme of a traditional moving-magnet planar motor, and simultaneously support the pose measurement of a plurality of rotors in a single oversized working plane.

The application discloses a kind of information security evaluation method and system based on cloud computing, it is related to information security technical field, including, acquisition multi-modal data, adopt node identifier to generate space-time data package by encryption;Through edge node, threat characteristics are aggregated using secure multiparty computation, construct 58-dimensional square matrix, construct risk assessment model based on quantum heuristic algorithm, apply Do-Calculus algorithm to locate root cause threat, federal reinforcement learning dynamically optimizes model weight, output threat vector to cloud causal engine;Combine threat intelligence to construct space-time causal diagram, apply Do-Calculus algorithm to locate root cause threat, generate dynamic defense strategy, KL divergence constraint optimization access control, and store strategy execution log in local encryption, generate evaluation audit log.The method disclosed in the application solves the problem of insufficient correlation of cloud computing multi-modal data, defense lag and verification fault, and realizes the coordinated breakthrough of evaluation accuracy and response efficiency.

The invention discloses a power industrial control network simulation verification scene generation method based on LLM, and the method comprises the steps: collecting paired input data and label data based on a power industrial control network topology to generate a training data set, and converting the training data set into a model input vector through preprocessing and vector coding; constructing a generation model based on a large language model by using the vectorized training data set, and obtaining an output result of a directed graph matrix containing network topology and alarm information through the trained generation model; evaluating the alarm information generation capability and the matrix generation capability according to the output result to obtain an evaluation result; and converting a square matrix and a vertex array output by the generative model into a directed graph form according to an evaluation result, and constructing a virtual simulation scene in a graph node mapping mode. According to the invention, the problems of single and fixed network scene required by simulation verification of the electric power industrial control network, incapability of rapid adjustment and the like can be solved.

An image decoding method performed by means of a decoding device according to the present invention comprises the steps of: deriving quantized transform coefficients with respect to a target block from a bitstream; performing inverse quantization with respect to the quantized transform coefficients with respect to the target block and deriving transform coefficients; deriving residual samples with respect to the target block on the basis of reduced inverse transform with respect to the transform coefficients; and generating a reconstructed picture on the basis of the residual samples with respect to the target block and prediction samples with respect to the target block. The reduced inverse transform is performed on the basis of a reduced inverse transform matrix. The reduced inverse transform matrix is a non-square matrix of which the number of columns is smaller than the number of rows.

The invention discloses a material array arrangement method, which comprises the following steps of: recording the time when materials pass through a fixed point through a capacitive sensor on an incoming material conveying belt, and calculating the real-time position of subsequent movement of the materials in combination with the speed of the conveying belt; a clamping device on the Z axis of the XYZ three-axis mechanical arm is used for clamping the materials and lifting the materials away from the incoming material conveying belt when the real-time positions of the materials are calculated to be within the clamping range; the materials are clamped and lifted according to the number of the materials in the set column direction, after a column array is completed, the column materials are placed on a conveying belt at equal intervals through a three-axis mechanical arm to form a square matrix, the conveying belt moves the square matrix to the next array position, and a new square matrix is generated at the array discharging position; a material matrix arranged at the array feeding position is conveyed to the material taking position through a conveying belt, and linkage of conveying and material taking is accurately controlled by a PLC through signals of a photoelectric sensor. According to the invention, through parameterized management of clamping stations and cyclic counting of array rows and columns, ordered arrangement of material matrixes of different specifications is realized, and the device is suitable for various working scenes.

The invention discloses a die clamping mechanism of a die-casting machine, which comprises a fixed die plate, a movable die plate and a tail plate, the fixed die plate, the movable die plate and the tail plate are sequentially connected through a pull rod assembly, the fixed die plate is fixedly connected with the pull rod assembly, and the movable die plate and the tail plate are movably connected through a bent elbow assembly. The pull rod assembly comprises a first rod set around the first flow guide groove and a second rod set around the second flow guide groove, all rod pieces of the first rod set are arranged in a square matrix mode with the center of the first flow guide groove as the center, and all rod pieces of the second rod set are arranged in a square matrix mode with the center of the second flow guide groove as the center. The invention relates to the field of die-casting dies, and aims to reduce the size and weight of equipment by optimizing the layout of pull rods and introducing a double-injection function.

The present invention discloses a two-stage high-precision positioning method in an NLOS environment. The method comprises the following steps: step 1, in an NLOS scenario with a length of L and a width of W, base stations are evenly distributed on a square array with a distance of D; step 2, CIR data acquisition; step 3, TOA prediction; step 4, TOA positioning; step 5, setting the sample size to be represented by N sp ,(x i ,y i ) and #imgabs0# distribution represent the actual position and predicted position coordinates. The method of the present invention obtains CIR data through the channel information between the base station and the user and establishes a mapping relationship between CIR information and TOA through a TOA prediction network, thereby accurately predicting the time TOA when the base station reaches the user. A nonlinear mapping relationship is established between TOA and the user position through a deep learning method, thereby ensuring that the user position can be accurately predicted. The proposed deep learning method establishes a mapping function between CIR, TOA and user position by learning a large amount of channel information, which greatly improves the positioning accuracy in the NLOS environment and saves equipment costs.

The invention relates to the technical field of oil and gas exploration and development, and particularly discloses a robust mixed norm constraint high-dimensional seismic data reconstruction method and device, and the method comprises the steps: carrying out the Fourier transformation of five-dimensional data along a time axis, and obtaining the Fourier transformation data; unfolding 4D data of each frequency slice of the Fourier transform data along a mode-(m, n) to obtain a near-square matrix; a non-convex Frobenius / Nuclear mixed norm and L1 norm combined regularization constraint is applied to the near-square matrix, and a target functional of observation seismic data and reconstruction data is constructed; and alternately solving the target functional by adopting an ADMM algorithm, and carrying out inverse Fourier transform on a solving result along a frequency axis. According to the method, a high-dimensional tensor completion method under the robust Frobenius / Nuclear mixed norm constraint is introduced, accurate representation of nonlinear high-dimensional seismic data is achieved, the seismic data reconstruction and denoising precision is improved, and therefore regularized reconstruction and abnormal noise suppression of the seismic data with the low signal-to-noise ratio are achieved.

The invention relates to the technical field of navigation testing, and discloses an optimization method and system for adjusting an anti-interference gain of a navigation receiver, so as to avoid invalid frequent switching. The method comprises the following steps: calibrating an interference intensity threshold X and a weight matrix B of the switching gain of the navigation receiver, the weight matrix B being an M-order square matrix, and M being an integer greater than or equal to 3; segmenting the obtained group of M * M * N continuous sampling values of the external interference intensity according to a time sequence, and obtaining the median of each segment based on bubble sorting, N being the number of an odd number of sampling points greater than or equal to 5 in each segment; combining results obtained by subtracting the median of each segment from X into an M-order square matrix A according to a time sequence in an element arrangement mode from left to right and from top to bottom; performing non-filling convolution operation on the square matrix A and the square matrix B to obtain a scalar value C; judging whether the scalar value C is greater than a trigger threshold value or not, and if so, triggering a gain switching operation; otherwise, the gain switching operation is not triggered.

The present invention relates to the technical field of FMCW radar ranging, and specifically discloses a high-precision measurement method for the target distance of an FMCW radar that fuses the difference frequency signal and the integral signal. The steps include: obtaining the discrete difference frequency signal; performing frequency shift processing through FFT transformation; constructing a Toeplitz square matrix and performing eigenvalue decomposition for denoising to obtain the denoised and frequency-shifted discrete difference frequency signal; solving the first integral signal of the denoised and frequency-shifted difference frequency signal; constructing a generalized eigenvalue equation and performing generalized eigenvalue solution, and then obtaining the accurate distance of the measured target. The method of the present invention can obtain the theoretical solution of the difference frequency signal frequency while solving the fence effect and spectral leakage existing in the FFT transformation, so as to achieve the precise solution of the target distance; moreover, the present invention can directly use the frequency of the difference frequency signal to measure the target displacement, thus effectively solving the phase wrapping problem existing in the phase interference method.

Methods, systems, and devices for wireless communications using a singular value decomposition (SVD) combiner precoder are described. The described techniques may enable a network entity to determine which streams of a set of multiple data streams to combine in the SVD combiner precoder to increase a lowest signal-to-noise ratio of the set of multiple data streams, and which streams of the multiple streams to leave separate. The network entity may determine a precoding matrix using a square matrix α, which may allow the network entity to dynamically combine (e.g., or not combine) data streams. The network entity may transmit an indication to a UE indicating which streams the network entity will combine and which streams the network entity will not combine. The UE may accordingly demodulate the non-combined streams with a relatively less complex demodulator and may demodulate the combined streams with a relatively more complex demodulator.

Various examples are provided related to a block cipher adaptation of the Galois Extension Fields (GEF) combination technique. In one example, a GEF-based block encryption includes forming an output from a PRNG into a key matrix, where the key matrix is formatted as an invertible square matrix; applying a GEF operation to the key matrix to map elements to a closed subset in a higher-order GEF space; mapping plaintext to a plaintext matrix; applying a GEF operation to the plaintext matrix to map elements to the higher-order GEF space; combining the plaintext matrix and the key matrix to produce a vector of ciphertext in the higher-order GEF space; reducing the vector to a reduced vector of ciphertext using an inverse of the GEF operation; and during the reducing, applying a ceiling operation to bijectively map elements in the reduced vector to a closed subset. Another example includes GEF-based block decryption.

The present disclosure provides coding and decoding methods, a communication device, and a storage medium. The coding method, applied to a first transmission node, includes: determining a base matrix for low density parity check (LDPC) coding from a preset base matrix set; performing LDPC coding on original data according to the base matrix, so as to obtain coded data; transmitting the coded data to a second transmission node; wherein the base matrix includes two kinds of elements: an element indicating an all-zero square matrix, and an element indicating a cyclic shift of an identity matrix; the base matrix set includes at least two non-empty subsets of base matrices, and all base matrices in each subset of the at least two non-empty subsets of base matrices have a same coding rate.

The present invention discloses an anti-jamming method for multiple-input multiple-output synthetic aperture radar based on APC and OFDM. By comprehensively utilizing APC and OFDM technologies, the two are combined to form an APC and OFDM dual-modulation waveform; the channel array is designed as a 2×2 square matrix; a space-time two-dimensional signal reception model is constructed, and at the same time, a repeater interference is added, and the echo is sampled to obtain range-azimuth-array three-dimensional echo data; OFDM demodulation and pulse compression are performed; the beam pointing angle corresponding to each azimuth channel is calculated to form a steering vector matrix, and the weighted vector matrix is calculated using the steering vector matrix and multiplied by the three-dimensional echo data to complete APC waveform separation and single-channel repeater interference suppression; imaging is performed on the echo data after anti-jamming processing, and finally a range-azimuth real target SAR image is formed. The present invention effectively utilizes the information resources in the time domain, frequency domain and spatial domain between the airborne radar and the target, making the anti-jamming algorithm more convenient, concise, accurate and effective.

1. The name of the design product: sound (square matrix). 2. The use of the design product: the design product is used for sound equipment. 3. The design points of the design product: the combination of shape and pattern. 4. The picture or photo that best indicates the design points: combination state diagram.

The invention discloses a high-order matrix operation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a plurality of target matrixes to be operated, dividing each target matrix into a plurality of square matrixes, and distributing each square matrix to a corresponding chip; a ping-pong transmission algorithm is adopted through a plurality of chips, and on-chip matrix multiplication is completed on the distributed square matrix; respectively corresponding multiplication results are transmitted to a target chip in parallel by adopting a ping-pong transmission algorithm through the plurality of chips; and performing accumulation operation on the multiple multiplication operation results through the target chip to obtain a target operation result corresponding to the target matrix. According to the technical scheme of the embodiment of the invention, the multiplication efficiency of the high-order matrix and the utilization rate of hardware resources can be improved.

The application discloses a kind of converter electromagnetic transient simulation parallel optimization method, equipment and storage medium, belong to power system electromagnetic transient simulation technical field, by merging significantly reduces unnecessary intermediate variable, shortens simulation calculation process;And since C, D matrix and Un, k matrix multiplication operation with Itotal of A, B matrix and multiplication are carried out simultaneously, and the calculation process between row and row is independent, increase the parallel degree of electromagnetic transient simulation calculation;Since parameter matrix does not change with the change of switch state, it is calculated and stored in advance in simulation initialization stage, only needs to consume register reading operation time in the calculation of single simulation step;Coefficient matrix A, B, C, D are all square matrix of scale Nb*Nb, the formula for calculating Ub and Ib is the same in structure, to lay the algorithm foundation for saving logic resources while improving the calculation efficiency of simulation program using pipeline and other hardware development techniques.

According to the square matrix movement control method provided by the invention, a movement instruction for a target square matrix is received, and the movement instruction comprises a target position, a target formation specification and a target orientation vector corresponding to the target square matrix; generating a target coordinate set according to the target position, the target formation specification and the target orientation vector; acquiring the current state of the target square matrix; sorting the target coordinate set based on the current state and a preset movement type, and determining an allocation sequence of each target coordinate; matching each unit in the target square matrix with a target coordinate in the target coordinate set to generate a corresponding relationship between the units and the target coordinate; and controlling each unit to move towards the corresponding target coordinate according to the corresponding relationship. Accurate control over square matrix movement can be achieved, and the efficiency and accuracy of square matrix transformation are improved through reasonable coordinate distribution and a matching algorithm.

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.