51 results about "Matrix iteration" patented technology

The invention provides a method for constructing a quasi-cyclic low-density parity-check code (QC-LDPC code), which comprises the following steps: determining a parameter of an encoding matrix; constructing an exponential matrix M (H) of a QC-LDPC code parity check matrix; using a progressive edge growth (PEG) algorithm of the QC-LDPC code parity check matrix to initialize the exponential matrix M (H); endowing the exponential matrix each nonnegative element to form a cyclic shift value with the longest minimum ring and the least ring number; carrying out iteration replacement on the elements in the exponential matrix; and completing the iteration replacement process of the exponential matrix by an exponential matrix iteration assignment algorithm of the QC-LDPC code parity check matrix. The method for constructing the QC-LDPC code of the invention can guarantee the girth and the average minimum girth of the code maximized so as to obtain excellent error code correcting performance.

The invention provides an image encryption method based on chaotic mapping and bit-level replacement. The method comprises the following steps: converting a grayscale image into an image matrix; iterating 2D-LSCM mapping to generate a chaotic sequence and mapping the chaotic sequence into a matrix, and returning a position index to perform pixel position exchange on the image matrix after descending sorting of each row; sequentially exchanging the lowest three bits in every two pixel bits to obtain an information fusion sequence of the image; performing iteration on the Logistic mapping to generate a chaotic sequence, and performing operation on the information fusion sequence and the chaotic sequence to obtain a pixel replacement column of the image; and performing pixel diffusion on thepixel replacement sequence of the image by using a chaotic sequence and a ciphertext diffusion technology to obtain an encrypted image. The chaotic mapping and scrambled images are used for replacement operation, the differential attack resistance is enhanced through bit information fusion operation and an image pixel-based diffusion method, the secret key space is large enough, violent attack canbe better resisted, and good safety is achieved.

The invention discloses a load characteristics comprehensive classification method based on Markov Monte Carlo. The method includes the following steps: finding the voltage drop time point, carrying out load dynamic characteristics extraction and classification at the disturbance moment corresponding to the voltage drop time point; judging whether the change between the load classifications has a Markov property or not; dividing all data into uniform segments by time; establishing Markov chain's probability transfer matrix based on the maximum likelihood thought for each data segment; judging whether the numerical characteristics are changed or not: if no, go to step V; if yes, carrying out clustering on the load data in the time segment according to the numerical characteristics corresponding to the matrix, and obtaining the probability transfer matrix of the load data with changed numerical characteristics in each time segment ; carrying out Markov Monte Carlo simulation and describing the load change situation; processing the sequence reflecting the load classification conversion using the Hidden Markov Model (HMM). The method provided by the invention improves the Markov chain Monte Carlo simulation and effectively reduces the possibility of the matrix entering the stable state after iteration.

The invention relates to a multi-regional fully distributed active distribution network economic dispatching method and belongs to the field of electric power system operation and control technology, and the method comprises the steps: 1) establishing an active distribution network economic dispatching model for considering linearizing transmission losses and minimum light discarding cost; 2) realizing localization quasi-Newton matrix iteration initial value construction, localization quasi-Newton direction iterative computation and localization step size searching calculation for regions through neighbor boundary node communication; 3) judging whether global convergence is achieved through the neighbor communication after regional convergence. According to the invention, the method aims at operating characteristics of an active distribution network, point-to-point communication technology are fully utilized, on the basis of fully distributed quasi-Newton method, the method complete active distribution network economic dispatching multi-regional fully distributed superlinear convergence computation without a coordination center, the reliability is improved, privacy of the regions is protected, and plug-and-play is realized.

The invention discloses a target tracking method under DoS attack. The method comprises the following steps: establishing a state model and a measurement model of a system, and initializing a system state, sampling time and control parameters; modeling a signal received by the monitoring center under the DoS attack; defining a local state estimate (LSE) and a distributed fusion estimate (DFE); designing two optimization problems for the networked nonlinear estimation system, and respectively calculating to obtain a local estimation gain and an optimal weighting matrix; iterative updating is carried out to obtain the optimal estimation of the target position; the distributed fusion estimation algorithm is provided for a networked nonlinear system under DoS attack, and compared with an existing target tracking method, the distributed fusion estimation algorithm effectively improves the target tracking precision on the premise of ensuring the calculation complexity.

The invention provides a translation matrix model selection system based on OpenKiWi, a method for evaluating a plurality of translation results output by a plurality of translation engines based on an evaluation engine of an OpenKiWi core, and a translation terminal. The selection system comprises a to-be-translated source text input component, a GMM clustering engine, an evaluation engine basedon an OpenKiWi core and a selection output interface. The evaluation engine based on the OpenKiWi core performs sentence-level evaluation and word-level evaluation on a translation result, obtains a sentence-level evaluation matrix and a word-level evaluation matrix, combines the sentence-level evaluation matrix and the word-level evaluation matrix to obtain an N-order evaluation matrix PN, performs iterative computation on the N-order evaluation matrix PN, and outputs an optimal translation result based on an iterative computation result.

A method for computing feature kernels for optical model simulation is provided. In the method, a feature matrix mathematically describing a plurality of properties of an optical imaging system is identified. A sampling matrix comprising at least one vector serving as input to form a low-rank basis for the feature matrix is generated. The sampling matrix is iteratively multiplied by the feature matrix and a multiplication result is adaptively rescaled according to numerical stability until a convergence condition is met. The iteration results are used to form a reduced feature matrix. Decomposition values of the reduced feature matrix are computed and a plurality of feature kernels are extracted from the computed decomposition values.

The invention discloses a multi-view image clustering method based on clustering self-adaptive canonical correlation analysis, and the method mainly constructs a self-adaptive optimization model of multi-view canonical correlation analysis and clustering and solves the problem of clustering inadaptability of multi-view correlation learning in a clustering task, thereby improving the clustering performance of multi-view images. The method comprises the following steps: (1) initializing a class label indication matrix of an original high-dimensional sample; (2) iteratively solving a related projection matrix, a class centroid matrix and a class label indication matrix; (3) directly obtaining a clustering result based on the solved class label indication matrix. Compared with the prior art, the multi-view image clustering method provided by the invention is more effective and robust.

The invention discloses an information system security situation assessment method based on a fuzzy Petri network. The method comprises the following steps: constructing an information system securitysituation evaluation index system; establishing a fuzzy Petri network model; obtaining an expert evaluation result; calculating the credibility of a library; obtaining an initial state matrix; iteratively calculating a state matrix; and obtaining the security level of the qualitative information system. The information system security situation evaluation method based on the fuzzy Petri network has the beneficial effects that the method has a visualized graphic structure; uses a Pythagorean fuzzy set for describing the evaluation indexes so as to achieve a wider expressible range and better description capacity for the evaluation indexes compared with a traditional fuzzy set and an intuitionistic fuzzy set; and has reasonability, can avoid repeated triggering of the same transition by setting judgment on transition equivalent input, and thus guarantees that a security situation evaluation result is obtained in limited iteration times.

The invention provides a sparse underwater acoustic channel estimation method based on generalized approximate message passing sparse Bayesian learning, and belongs to the field of underwater acousticsignal processing. The invention relates to a channel estimation method combining generalized approximate message passing (GAMP) and sparse Bayesian learning (SBL). The method comprises the followingsteps: (1) inputting a frequency domain baseband receiving signal, a dictionary matrix, an iteration termination condition and a related parameter initial value; (2) calculating a channel impulse response by utilizing GAMP under the framework of the SBL; (3) updating a noise variance and a channel hyper-parameter; and (4) judging an iteration termination condition, and outputting a channel estimation result if the iteration termination condition is met. The method has the advantages that the underwater acoustic channel impulse response is calculated in an approximate message passing mode under the framework of the SBL, the calculation complexity of the SBL is reduced under the condition of basically no performance loss, and the operation time of the algorithm is shortened.

The invention provides an optical layer decomposition method based on a spatial transformation model, aiming to solve the technical problems of bad decomposition effect and low efficiency in a conventional non-supervision single mixed image decomposition method. The realization steps include reading in an original mixed image; fuzzing by means of a blind deconvolution algorithm; defining iterative variables and a transmission layer matrix iteration formula; creating a spatial transformation model and deriving the function expression of the transmission layer matrix and the reflection layer matrix; constructing target functions, adding constraint conditions by means of layer prior, performing regularization with L1 norms, and realizing the target function convex optimization; solving the optimal solution of convex target function by means of a Lagrangian multiplier method; calculating the transmission layer matrix and the reflection layer matrix by means of the function expression; and determining whether the iteration frequency is greater than the set threshold, if yes, the iteration is completed, otherwise, the convex target function is updated. The optical layer decomposition method improves the decomposition effect of the mixed image and improves the calculating efficiency.

The invention discloses an online measurement method for a generalized short-circuit ratio of a multi-infeed new energy grid-connected system. System nodes are divided into a feed-in port node, an intra-network node and an infinite power grid equivalent node, discrete time point data of current and voltage of the feed-in port node are acquired from the nodes, and then a current difference matrix and a voltage difference matrix are acquired; and a relation model between the current difference matrix and the voltage difference matrix is established through a rearranged Crocco order reduction admittance matrix, then a rearrangement matrix is solved according to a least square method matrix iterative solution, and the generalized short-circuit ratio is obtained by utilizing the rearrangement matrix. According to the generalized short-circuit ratio real-time measurement algorithm, real-time online measurement of the generalized short-circuit ratio can be achieved, and the calculation resulthas high resistance to measurement noise interference through the matrix iterative algorithm based on the least square method.

The invention discloses a double-wall cooling structure flow transmission system, relates to the technical field of double-wall cooling structure flow design, and solves the problems that in the prior art, designers need to have rich experience, human intervention is needed, an automatic optimization system separated from people cannot be constructed, and the like. The system comprises a flow automatic identification module, a flow priority matrix D calculation module and a flow transmission matrix iteration correction module. According to the method, the flow distributed to each air film hole by each impact hole can be calculated under the condition that the flow of the impact hole inlet and the flow of the air film hole outlet of the double-wall cooling structure are known. The flow path of the double-wall cooling structure is not restrained by the structure, but the fluid is automatically distributed under the condition that the inlet and outlet pressure is given, so that the flow distribution of the double-wall cooling structure cannot be calculated by a common fluid network method. The flow matrix clearly points out the directions of all fluids in the double-wall cooling structure, and the result can be used for effectively guiding the design of the cooling structure.