18 results about "Linear code" patented technology

The invention discloses a reciprocal calculation instruction sequence generation method oriented to a heterogeneous processor, and belongs to the field of compilation optimization and code generation. Aiming at the problems of instruction redundancy, weak precision control, poor hardware adaptation and high manual dependence of an existing method in a heterogeneous environment, characteristics of a reciprocal instruction and an operand are accurately identified by linearly scanning heterogeneous object codes (including vectorization, scalar and complex instruction sequences); in combination with hardware characteristics of RISC / SIMD / VLIW / DSP and the like, a multi-round iteration precision improvement and temporary register optimization allocation strategy is adopted, differential generation logic is formulated, and a high-precision low-redundancy instruction sequence is generated. The method comprises linear code scanning classification, reciprocal instruction and operand identification, cross-architecture generation logic rule formulation, instruction sequence generation and legality verification. Full-process automation is achieved, manual intervention is reduced, the execution efficiency and precision of reciprocal calculation of the heterogeneous processor are improved, and the method is suitable for embedded systems, high-performance calculation and other scenes.

The invention provides a multi-keyword private information retrieval method and system based on inverted indexes, and belongs to the field of information security and privacy computing. The method comprises the following steps that: a server splits an original database into a reverse index part of a keyword-index set and a key value pair part of an index-data value; mapping the index set into an integer by utilizing Godel coding; processing the data by adopting probability batch coding and binary random linear coding and publishing a hash function; the client maps a multi-keyword query into a bucket by using a hash function to generate a query vector, and the query vector is sent to the server after being subjected to fully homomorphic encryption; the server performs homomorphic calculation on a matching result in a ciphertext state and returns the result; and the client obtains a matching index set after decryption verification, and then initiates a second round of query to obtain final data. According to the method, symmetric privacy protection of multi-keyword non-primary key query in a single-server environment is realized, leakage of query content and database information is effectively prevented, and private information retrieval security is improved.

The invention discloses a method for constructing a first-order elastic five-spectrum value function based on disjoint linear codes, which is characterized by comprising the following steps of: obtaining a group of disjoint linear codes according to the relation among related knowledge, set parameters and the set parameters of a finite field so as to divide the whole space; on the basis of a group of disjoint linear codes, resetting the value range of parameters, and generating one linear code and one linear code according to the generation principle of the disjoint linear codes; setting two sets to define a support set of a function; constructing a first-order elastic five-spectrum value function by using a one selection mode through giving two definition methods of the function; a truth table and a Walsh spectrum are given according to the defined first-order elastic five-spectrum value function to be depicted and verified, and therefore a Boolean function is constructed to be used for encryption. According to the method, a direct construction method of the first-order elastic five-spectrum value function is researched on the basis of the disjoint linear codes, starting from an existing Boolean function is not needed, application conditions and construction complexity are reduced, and construction efficiency can be improved.

This invention discloses a data encoding system and method based on simplicated complex homogeneous linear codes. The system includes: a parameter initialization module for initializing the construction parameters of an n-ary multivariable function F; a function definition module for generating the multivariable function F based on the construction parameters; and a definition set extraction module for constructing a definition set D. F ; Linear code generation module, used to generate linear codes according to the definition set D F This invention employs an inner product mapping to construct a basic p-ary linear code corresponding to the defined set; a homogenization processing module is used to homogenize the multivariable function F to obtain an (n+1)-ary homogeneous function; and a homogenized code generation module is used to generate a homogenized definition set based on the homogenized function, and then generate a homogenized p-ary linear code based on this set. This invention solves the problems of existing p-ary linear code construction techniques being complex in structure, having uncontrollable parameters, or being difficult to analyze weight distribution, leading to difficulties in efficient deployment in engineering.

The application discloses an image semantic segmentation method applied to an electronic device comprising an image semantic segmentation model, wherein the image semantic segmentation model comprises a down-sampling module and a sparse multi-layer perception module; the image semantic segmentation method comprises the following steps: acquiring an original image, extracting a down-sampled feature map of the original image by using the down-sampling module; performing linear coding on the down-sampled feature map to obtain a linear coding feature map; performing feature extraction on the linear coding feature map by using the sparse multi-layer perception module to obtain an output feature; training the image semantic segmentation model by using the output feature, and performing an image semantic segmentation task by using the trained image semantic segmentation model; and the application can balance the speed and accuracy of image semantic segmentation, so that the image semantic segmentation operation has a faster speed and higher accuracy. The application also discloses an image semantic segmentation device, an electronic device and a storage medium, which have the above beneficial effects.

The embodiment of the invention relates to the field of artificial intelligence, and provides an epilepsy electroencephalogram signal detection method and device based on frequency attention and a pulse recurrent neural network and a storage medium, and the method comprises the steps: obtaining an epilepsy electroencephalogram signal to be detected; performing datum line following coding on the epilepsy electroencephalogram signal based on a grid search algorithm to obtain a coded epilepsy electroencephalogram signal; constructing a bidirectional pulse recurrent neural network model based on a preset adaptive pulse neuron model; the bidirectional pulse recurrent neural network model is used as a reference model, the reference model is adjusted based on a frequency attention mechanism and a pulse full-connection linear coding mechanism, and an improved model is constructed; and inputting the epilepsy electroencephalogram signal into the trained improved model to output a detection result associated with the epilepsy electroencephalogram signal. By adopting the method, the model calculation performance can be improved on the basis of reducing the energy consumption, and the detection effect on the epilepsy electroencephalogram signals is improved.

Provided is a transmitter that shapes uniformly distributed bits into non-uniformly distributed bits according to a parity check matrix of a linear code such that a product of the parity check matrix and the non-uniformly distributed bits is equal to the uniformly distributed bits. Similarly, a receiver is provided that restores uniformly distributed bits from non-uniformly distributed bits by multiplication of the non-uniformly distributed bits with a parity check matrix.

The application relates to a design method of a nonlinear corrector of a true random number generator. A kind of n input m output corrector function is constructed, and the technical scheme is: a group of bases of a finite field is selected, and an isomorphic mapping from to an [n-m, m, t] equidistant linear code is established. Component functions of the corrector are constructed so that each component function is cascaded by 2 m n-m element affine functions, the coefficients of the affine functions are one-to-one corresponding to 2 m vectors in the [n-m, m, t] equidistant linear code, and the constant term of each n-m element affine function cascaded by the i th component function is equal to the value of the i th input symbol. By using the design method, the algebraic degree of the obtained nonlinear corrector is m+1, the flexibility order is t-1, the correction order is currently optimal t, and the correction order is greater than the function flexibility order. The corrector obtained by the application has the ability to resist linear attack, correlation attack and algebraic attack, and has wide application prospects in cryptography and random simulation.

One or more methods, devices, and / or systems can provide techniques for linear encoding channel state information (CSI) compression for multi-transmission / reception point (mTRP). This can provide improvements to wireless communication systems, for example, by improving resilience against transmission errors and mismatches, joint or separate compression of channel matrices from different TRPs, and / or fallback to legacy CSI reporting operations in mTRP CSI compression.

The invention relates to a digital signature method based on coding, and belongs to the technical field of information security. A trusted center generates a public key and a private key and sends the public key and the private key to a signer, and then the signer signs a message. Except a legal signer, the generated signature is difficult to counterfeit by any other person, but any person can verify the validity of the signature. Besides, the problem of difficulty in decoding of random linear codes in a coding theory is combined with digital signature, quantum computing attacks can be effectively resisted, the robustness of a signature scheme in a noise channel is improved, and the storage and transmission overhead of signature results is reduced.

The invention relates to a method for optimizing a function (F), the function (F) being a linear code with which a control matrix is associated, the function (F) comprising parameters that are the elements of the control matrix, the parameters taking their values from a set (E) of discrete values, the method using another function (L), referred to as a loss function, the method, which is implemented by a data processing device (100), comprising: executing a gradient descent step on the loss function (L) in order to obtain a parameter value (V1, V2, V3), the obtained values optimizing the function (F).

The invention discloses a customs commodity classification method and system based on multiple features of a table, and relates to the technical field of customs commodity classification. Comprising the steps that tabular customs commodity declaration data are acquired, and the data comprise numerical features, category features and text features; piecewise linear coding PLE is adopted for numerical value features, integer mapping is adopted for category features to be combined with an embedded layer, and RoBERTa pre-training model is adopted for text features to be combined with a linear transformation layer to be processed; stacking the three types of feature embedding vectors into an embedding matrix, and inputting the embedding matrix into a model based on a Transform architecture to complete multi-feature deep fusion; generating an adversarial sample, constructing a positive and negative sample pair, and combining cross entropy loss and contrast loss to train a model; and inputting to-be-classified tabular customs commodity declaration data into the trained model, and outputting a coordination system code corresponding to the commodity. According to the invention, the time cost and labor cost of manual auditing can be reduced, the error rate of manual classification can be effectively reduced, and the fairness and rationality of tax collection are ensured.

The invention discloses a secret sharing method based on a linear code general access structure. The method comprises the following steps: a sender selects and publishes security parameters of a secret sharing scheme; the security parameters comprise a parameter r in a finite field range and a bivariate one-way function, and the secret s is in the finite field range; the distributor selects a linear code, a generation matrix and a check matrix based on the number of users; the distributor randomly selects a vector and multiplies the vector by a generated matrix to obtain a corresponding character code, and the secret is equal to the vector multiplied by the first column of the generated matrix; any user selects a corresponding sub-secret and the sub-secret is checked by the distributor, so that the sub-secrets meet the condition that every two sub-secrets are relatively prime and are larger than the selected finite field; the distributor executes a secret distribution algorithm to calculate and obtain a general solution X meeting the congruence equation set, and the X is disclosed; and the authorized user cooperates with the bivariate one-way function according to the general solution X to reconstruct and recover the secret. According to the method, multiple times of use of the sub-secret is realized, and malicious behaviors of dishonest users are effectively resisted.

Examples of the presently disclosed technology provide a methodology for detecting and correcting errors in a summing content-addressable memory (Σ-CAM) while the Σ-CAM is performing a computational task (i.e., “on-access” error correction). The methodology involves adding redundancy columns to a Σ-CAM used to store a task-driven matrix (i.e., a matrix having values comporting with a computational task). Examples can leverage an encoder to compute redundancy values for the redundancy columns such that the Σ-CAM stores a codeword of a linear code (C) in each row. Examples also modify the linear code (C) used to compute redundancy values. Namely, examples modify the linear code (C) so that it includes the all-one vector. With this modification, a system of the presently disclosed technology can detect and correct errors in an output vector from a Σ-CAM based on this modified / particularized linear code (C).

The invention provides a near-field dynamics neighborhood construction method and device. The neighborhood construction efficiency of particles can be improved. The method comprises the following steps: determining space coordinates of all particles in a preset simulation model; dividing a computational domain into a grid unit set according to the space coordinates; performing linearization processing on each grid unit in the grid unit set to obtain a unique linear code corresponding to each grid unit in the grid unit set; counting and recording the number of particles and the number of particles in each grid unit, and respectively establishing a corresponding relationship between the number of particles and the number of particles in each grid unit and the unique linear code; determining potential neighborhood particles of each first particle in all the particles according to the corresponding relation; and constructing a neighborhood particle set of each first particle according to the potential neighborhood particles of each first particle.

The utility model relates to the technical field of automatic code reading identification, in particular to a nonlinear bottom bin bar code reading device, which comprises a horizontal box body and computer equipment, the reflection code reading assembly comprises an integrated base fixedly connected to the inner bottom face of the horizontal box body, a visual code reader is fixedly installed on the upper end face of the integrated base, and an external IO control interface is fixedly installed on the outer wall of the horizontal box body; and the computer equipment, the external IO control interface, the visual code reader and the external power supply are electrically connected through wires. According to the utility model, the installation and operation of the low-space visual code reader can be effectively solved, and the integrated base can be matched with computer equipment to carry out conditional operation, so that the whole device has strong expansibility, and the non-linear code reading operation of the low space can be realized through the reflection cooperation of the reflector A and the reflector B; therefore, the method is suitable for multi-angle and multi-position code reading operation.

The invention belongs to the technical field of wireless communication, and particularly relates to an OFDM (Orthogonal Frequency Division Multiplexing) transmission method based on space-time linear coding index modulation. According to the method, space-time linear coding is carried out on activated index information, and the safety performance of the system is improved while the characteristics of index modulation and space-time linear codes are reserved. Since space-time linear coding is carried out by using the activation index information, after receiving information is linearly combined during detection, sending information can be directly demodulated without channel information, and meanwhile, full diversity gain is ensured.

The invention provides a multi-energy supply and demand balance method and system, and the method comprises the steps: carrying out the data preprocessing of collected electric energy data, thermal energy data, hydrogen energy data and environment parameters, so as to generate a standardized data matrix; sequentially carrying out grey correlation analysis and clustering division based on the standardized data matrix, and quantifying an energy complementary relationship and piecewise linear coding to screen out key contradictory features; constructing an electricity-heat-hydrogen dynamic equation based on the key contradictory features, and performing space-time parameter configuration based on the electricity-heat-hydrogen dynamic equation to generate a digital twin multi-energy coupling model; extracting model constraint parameters based on the digital twin multi-energy coupling model; and inputting the model constraint parameters into a deep reinforcement learning network, updating the reward function weight in combination with a real-time state, generating a dynamic scheduling strategy, and encoding the dynamic scheduling strategy into an equipment executable scheduling instruction. The method has the advantages of being accurate in optimal scheduling strategy, efficient in supply and demand balance, high in system self-adaptive capacity and capable of improving the energy utilization rate.