42 results about "Huffman coding" patented technology

The invention relates to the technical field of spacecraft satellite-ground communication, and provides a low-earth-orbit satellite communication time delay optimization method and system aiming at the defects that a traditional low-earth-orbit satellite communication satellite system and a satellite communication frame have high time delay and poor real-time communication function. The core of the invention comprises three parts: firstly, an efficient receiving and transmitting end coding and decoding technology: a transmitting end adopts a subblock coding technology of a Turbo code; and a receiving end uses an MAX-Log-MAP algorithm to carry out rapid iterative decoding on the word block code of the Turbo code. And secondly, compressing the user data: carrying out lossless compression on the user data and a satellite communication frame header by using Huffman coding, reducing the transmission data volume, improving the data processing speed, and thus reducing the processing time delay. And finally, simplifying the frame header design: optimizing the frame header of the communication frame so as to reduce the total length of each frame. The method is particularly suitable for communication satellites (the orbit height is less than or equal to 1500km) in a low earth orbit.

The invention discloses a hardware acceleration method and system for a ZSTD data compression algorithm based on an FPGA. Unified hardware implementation and collaborative optimization are carried out on three key links of LZ77 character matching, Huffman coding and finite state entropy coding in the ZSTD data compression algorithm. According to the system, a multi-channel parallel LZ77 character matching hardware architecture is adopted, and character matching is executed on continuous positions in a plurality of parallel windows at the same time. A modular design and a deep pipeline structure are adopted, and a buffer and pipeline mechanism is introduced among modules such as an LZ77 matching module, a Huffman coding module and a finite state entropy coding module. The 375MB / s compression throughput can be achieved under the 100MHz clock frequency, the compression speed is remarkably increased while the compression ratio is guaranteed, and the method is suitable for scenes with high requirements for compression performance of data centers, edge computing and embedded systems and has high practicability and popularization value.

The application discloses a cryptographic algorithm debugging data hierarchical grouping compression method for a reconfigurable cryptographic chip. In the debugging work of the reconfigurable cryptographic chip, the debugging data is divided into reconfigurable cryptographic algorithm configuration information and operation intermediate data. The debugging data is processed by hierarchical grouping, the debugging data of each level module is divided into one or more groups, then the debugging data is filled or spliced, and then the reconfigurable debugging data is compressed by using a Huffman coding mode. After the hierarchical grouping compression method of the debugging data is used, the transmission performance of the debugging data can be effectively improved while the storage resource of the debugging data is reduced.

The invention relates to the technical field of data compression, in particular to a real-time lossless compression method for linear scanning panoramic infrared image data. The method comprises the following steps: receiving current column original pixel data output by a linear column scanning infrared sensor; taking the original pixel data of the current column and the coded pixel data of the adjacent column in one frame as reference columns, and performing backward inter-column difference prediction to obtain predicted residual data of the current column; mapping the predicted residual data into a symbol value; carrying out entropy coding on the symbol value by using a static Huffman coding table which is pre-generated and solidified based on the statistical characteristics of the linear scanning infrared image, and outputting a compressed code stream; according to the scheme, the technical problem that high real-time performance and high compression ratio are difficult to consider when real-time lossless compression is carried out on linear scanning panoramic infrared image data in the prior art is solved.

This invention discloses a hardware acceleration method and accelerator for Transformer based on mixed-precision quantization and Huffman coding. The acceleration method includes: using a genetic algorithm to obtain several configuration schemes for mixed-precision quantization of Transformer network layers; performing mixed-precision quantization on each Transformer network layer based on each quantization configuration scheme to obtain a corresponding KL divergence; training a multilayer perceptron to obtain a quantization configuration prediction network using the quantization configuration scheme and the corresponding KL divergence as the output label and input feature, respectively; receiving a user-set target KL divergence value, using the quantization configuration prediction network to obtain the corresponding quantization configuration scheme, and performing mixed-precision quantization on each network layer based on the quantization scheme; and using Huffman coding to encode and compress all quantization weights before on-chip storage. This invention can reduce storage and computational overhead while maintaining model accuracy.

The invention discloses a heart sound signal acquisition and automatic classification method based on deep learning, and aims to solve the problems that wireless transmission time delay of heart sound signals is high, weak pathological features are difficult to extract and classification accuracy is low. The method comprises the following steps: acquiring signals of four auscultation areas by using a high-fidelity wireless digital stethoscope; high-speed and low-delay transmission of medical-level signals is realized by utilizing a star flash transmission module and combining predictive coding and Huffman coding compression mechanisms; in the preprocessing stage, self-adaptive wavelet denoising based on signal energy entropy is adopted, a multi-resolution fusion feature extraction strategy is provided, the problem of time-frequency resolution tradeoff is solved through narrow window and wide window dual-channel parallel processing, and transient positioning features and pathological frequency domain textures are captured at the same time; the classification model adopts a multi-scale parallel convolution structure and is matched with a recurrent neural network and an attention mechanism, so that the problem that transient and continuous heart sound features are difficult to consider at the same time in a single scale is solved. According to the method, the accuracy and robustness of heart sound classification are remarkably improved.

The invention discloses a compressed XML database type, system and method supporting efficient query, and relates to the technical field of XML databases, and the database type adopts a hierarchical compression storage architecture and a reverse search query architecture; in the storage stage, XML non-keyword information is coded through Huffman coding, recoverable ordered arrangement is carried out on the coded information through a tree structure, then transcoding is carried out, the information is stored in a disk in a binary form, and compared with a traditional XML database storage mode, at least 50% of storage space is saved. In the query stage, a reverse search mode is adopted, a corresponding Huffman code initial position is positioned through a keyword, then under the optimization effect of a reverse index, reverse search is performed to recover a complete XML structure, and the query complexity is reduced from traditional O (n) to O (1). According to the method, the storage efficiency and the query performance of the XML data are greatly improved, and the method is suitable for large-scale XML data management and application scenes.

This invention provides a method and apparatus for safety fusion source coding of the main longitudinal beam of a hydraulic flatbed trailer. Based on the characteristics of important safety parameter signals from the hydraulic sensors of the hydraulic flatbed trailer, a base-64 encoding method is used, and the code length is calculated. Then, Huffman coding is used, and the code length is calculated again. The base-64 encoding code length is compared with the Huffman encoding code length. If the base-64 encoding code length is less than or equal to the Huffman encoding code length, the base-64 encoding is output; otherwise, the Huffman encoding is output. This invention overcomes the deficiency of Huffman coding in terms of low coding rate for shorter data and employs a fusion source coding strategy. The two methods complement each other, achieving more stable wireless communication of important safety parameters of the main longitudinal beam of the hydraulic flatbed trailer.

Methods and computing devices configured to perform enhanced coding operations (e.g., compression, decompression, LZ-based compression techniques, etc.) are provided. A computing device processing system may be configured to: receive an input data stream; querying a search table with a sequence of bytes (or characters, symbols, etc.) in the received input data stream to receive one or more location vectors for each byte; querying a matching table using the received location vectors to identify a start and an end of a matching sequence; and performing a historical buffer check in response to determining that the match fails in the match table. A computing device processing system may determine copy and text commands for an input data stream based on heuristics and results of queries to a search table, match table, or historical buffer, and perform enhanced Huffman coding operations to encode the copy and text commands into a compressed bitstream.

The invention discloses a GPU memory optimization method and system, and the method comprises the steps: obtaining the real-time change characteristics of a task load through obtaining the dynamic data flow information of the task load and an intermediate data generation rule; according to the real-time change characteristics of the task load, an optimization algorithm based on gradient descent is adopted to determine the distribution proportion and the reserved space of a memory pool, and adjusted memory pool configuration is obtained; extracting available memory block information from the adjusted memory pool configuration, and compressing the intermediate data with low access frequency by adopting a Huffman coding algorithm to obtain a compressed intermediate data storage unit; and if the access frequency of the compressed intermediate data storage unit is lower than a preset threshold value, temporarily storing the compressed intermediate data storage unit to a low-speed storage area, and reallocating memory resources according to the task priority to obtain an optimized memory allocation scheme. According to the method, the memory utilization rate is remarkably improved, the access delay is reduced, and efficient memory resource management is realized.

This invention relates to the field of data processing technology, specifically to a blockchain-based method and apparatus for storing civil engineering test data. The method includes: acquiring civil engineering test data stored on the blockchain and real-time collected civil engineering test data, and preprocessing it to obtain analysis data; determining the importance, access frequency, and final repetition rate of character data based on the analysis data, and obtaining the encoding priority of the character data, adjusting the Huffman coding table; compressing all civil engineering test data according to the adjusted Huffman coding table, and re-storing it in the blockchain; and comprehensively adjusting the Huffman coding table based on the obtained encoding priority of each character data, compressing the data, and re-storing it in the blockchain. This method reduces the amount of data while maintaining access speed, thereby improving the reading speed for high-access data during subsequent data access.

Decoding a data stream which includes variable-length character-strings representing symbols which have been encoded in accordance with a variable-length prefix encoding scheme (such as Huffman encodi

This invention discloses a lossless data compression and encrypted transmission method based on federated middleware, belonging to the field of computer application technology. The method includes: performing run-length encoding on the data to be processed based on federated middleware to obtain first compressed data; processing the first compressed data using a compression algorithm based on a raw-middleware dual dictionary to obtain second compressed data. This compression algorithm uses both the raw dictionary and the middleware dual dictionary, adding only values ​​that appear at a set frequency to the dictionary; sequentially performing Huffman coding and DES processing on the second compressed data to obtain encrypted data and a key; performing RSA processing on the key to obtain an encrypted key; and transmitting the encrypted data and the encrypted key to the target end using an encrypted compression transmission plugin of an experiment-and-train-enabled architecture. This method achieves lossless data compression and encryption based on federated middleware, with fast algorithm speed and high security.

The invention provides a short message transmission method and device, which can be used in the technical field of satellite communication. Based on the method, message information of a first user terminal can be received, and the message information comprises a compressed short message and coding information; under the condition that a plurality of preset Huffman coding trees comprise a Huffman coding tree pointed by the coding information, decompressing the compressed short message by using the Huffman coding tree pointed by the coding information to obtain an original short message; each Huffman coding tree comprises a Huffman code of a character in a corresponding message communication scene, and the Huffman code is related to the occurrence frequency of the character; and sending the original short message to a second user terminal.

The application discloses a Huffman coding method, a coding device, a chip and a storage medium. The Huffman coding method comprises the following steps: obtaining a to-be-coded string and associated coding information, wherein the coding information comprises the length of the to-be-coded string, a corresponding alphabet and a limited code length to be coded; scanning the symbols of the string based on a preset scanning length, counting the occurrence frequency of each symbol in the scanned symbols, and generating a symbol frequency table corresponding to the to-be-coded string based on the preset scanning length; determining a reference frequency for frequency adjustment according to the preset scanning length and the limited code length, and optimizing the symbol frequency table based on the reference frequency; generating a Huffman codebook for the to-be-coded string according to the optimized symbol frequency table; and coding the to-be-coded string by using the Huffman codebook and outputting a corresponding coding result. The application can adapt to different scanning progress, construct a codebook meeting the limited code length, and effectively improve the Huffman coding speed.

The invention provides a data processing method and device, equipment and a storage medium. The method comprises the following steps: determining a plurality of data units in a first message sent by a Beidou terminal, determining numerical data of the data units corresponding to different data types according to the plurality of data units, and then performing Huffman coding on the plurality of data units according to the numerical data of the data units corresponding to the different data types to obtain target data. And finally, sending the target data corresponding to all the data types to the user terminal. According to the method provided by the invention, the processing of the message data is realized, the calculation amount of coding compression is reduced, and the time delay of data transmission is reduced.

The application discloses a kind of atlas relationship compression method and device based on context-aware Huffman coding, belong to atlas compression technical field.The method includes: traversing original data, the global appearance frequency of all relationship types is counted, and the conditional appearance frequency of each relationship type in each context instance;Global master Huffman coding table is constructed based on the global appearance frequency of all relationship types;Subordinate Huffman coding table is constructed based on the conditional appearance frequency of relationship type;According to the difference value of income and expenditure, subordinate Huffman coding table is screened;Stream coding process is executed, for each relationship triple to be compressed, whether the relationship triple is matched with corresponding context instance is judged in turn, and corresponding coding is carried out according to matching result;The binary bit stream generated by coding is packed with the metadata required for decompression.The application improves compression performance by converting global probability into conditional probability and using the structural information of atlas as prior condition.

A time-of-flight sensor, comprising a processing unit (100), the processing unit comprising an encoding unit (120) to generate compressed time-of-flight histogram data from one or more time-of-flight histograms based on an encoding dictionary stored in an encoding dictionary unit (130); and wherein the one or more time-of-flight histograms are related to a current imaging frame obtained from a time-of-flight pixel array. The encoding unit (120) initially receives filtered histogram data (111) from a readout unit (110). The encoding unit (120) receives this filtered histogram data (111), and forwards the data to the encoding dictionary unit (130) which stores the encoding dictionary and which contains the specific codes and rules (131) used to convert the filtered histogram data into encoded histogram data (124). The encoding dictionary unit (130) may also receive updates from an external source, ensuring that the dictionary (131) is always optimized for the most efficient encoding possible. Encoded data (122) represents the histogram data transformed into its Huffman-encoded form, while the encoded data lengths (123) provide information about the size of each piece of encoded data. The encoding unit (120) forwards the encoded data (122) along with the output data lengths (123) to a packaging unit (140). Lower loss compression of histogram data, employing neighbor bin and neighbor histogram filtering combined with data encoding, in ToF image sensors addresses the increased volume and complexity of ToF data due to advancements in pixel resolution and frame rate.

This invention discloses a GPU memory optimization method and system. By acquiring dynamic data flow information and intermediate data generation patterns of the task load, the real-time variation characteristics of the task load are obtained. Based on these characteristics, a gradient descent-based optimization algorithm is used to determine the memory pool allocation ratio and reserved space, resulting in an adjusted memory pool configuration. Available memory block information is extracted from the adjusted configuration, and a Huffman coding algorithm is used to compress low-access-frequency intermediate data, resulting in compressed intermediate data storage units. If the access frequency of the compressed intermediate data storage units is lower than a preset threshold, the compressed intermediate data storage units are temporarily stored in a low-speed storage area, and memory resources are reallocated according to task priority, resulting in an optimized memory allocation scheme. This invention significantly improves memory utilization, reduces access latency, and achieves efficient memory resource management.

The application relates to the field of data processing, in particular to a digital management platform for cultural and creative products, which comprises a data characteristic curve construction module for constructing a data characteristic curve for any type of data of the cultural and creative products; a similar segment acquisition module for dividing the data characteristic curve into similar segments with similar change trends; an optimal strategy evaluation module for taking the similar segments as primitives, arranging and combining all types of the primitives to obtain different combined strategies, and evaluating the combined strategies to screen out optimal strategies; and a data coding module for constructing a Huffman tree according to the optimal strategies, obtaining corresponding Huffman codes, completing data compression, and fully reflecting the differences in character appearance frequency through the Huffman codes obtained by the optimal strategies, so that the efficiency of data compression of the related data of the cultural and creative products by the Huffman codes is improved, and the safety of the data and the overall performance of the system are enhanced.

The invention discloses a snapshot optimization method and device based on an open source gap system, a medium and a product, and the method comprises the steps: caching a motion joint picture experts group (MJPEG) video stream collected by a camera in real time when the device enters a camera view finding mode; after an image snapshot instruction is received, extracting target MJPEG single-frame data from the cached video stream; applying for a target cache region in an equipment memory and constructing a standard JPEG file structure, wherein the structure comprises a plurality of to-be-filled data regions; according to the camera parameters, the Huffman coding table and the image direction parameters, an application program reservation mark 0 segment is constructed, a Huffman table segment and an application program reservation mark 1 segment are defined, a standard data structure is sequentially filled in to generate JPEG additional data, and a standard JPEG file is spliced and output. The system resource overhead is greatly reduced, and high-quality image output is ensured.

The invention discloses a specific field text file custom dictionary auxiliary Huffman compression method and system, and belongs to the technical field of data compression. The method comprises the following steps: receiving and verifying a phrase-short code mapping dictionary customized by a user, and ensuring that the length of a short code is smaller than that of an original phrase and ambiguity is not generated; sorting the dictionaries in a descending order according to the phrase length to form a replacement priority queue; performing phrase-to-short code replacement on the text according to a priority sequence by adopting a block processing strategy; carrying out character frequency statistics on the replaced text and constructing a Huffman tree; generating a code based on a Huffman tree, and converting the text into a bit stream; and generating a structured compressed file containing the metadata area, the dictionary information area and the compressed data area. The system comprises a dictionary management module, a text replacement module, a Huffman coding module and a file storage module. According to the method, field specific dictionary preprocessing and Huffman coding optimization are combined, a repetition mode of a specific field text is fully utilized, and the high compression rate of 70%-80% is achieved and is far higher than that of a general algorithm by 40%-60%.

The invention discloses a PLC equipment data optimization storage method, device and equipment and a medium, and relates to the technical field of data compression, quaternary Huffman coding adopted by the method optimizes the construction process of a coding tree through a virtual node processing mechanism, under the same data distribution condition, the average code length is lower than that of traditional binary Huffman coding, and the data transmission efficiency is improved. And the compression rate is obviously improved. For common sensor data, control parameters and the like in the PLC equipment, the storage space occupation can be greatly reduced by improving the compression efficiency. Meanwhile, the size of the window can be adjusted in real time according to the data change rate by adopting a dynamic sliding window mechanism, a larger window is used when the data distribution is stable, and a smaller window is used when the data change is frequent, so that the coding rule can reflect the change of the data distribution in time, and the coding adaptability and stability are improved.

The invention discloses an offshore wind turbine communication system based on quantum encryption, relates to the technical field of offshore wind turbine communication, and aims at solving the problems that an existing system is interfered by natural environment factors, and the traditional communication cost is high. The system is divided into three layers: an offshore booster station layer is connected with a 5G base station and an offshore wind turbine layer, receives production data and transmits the production data to an onshore monitor through a submarine optical cable; the 5G base station layer is connected with the two ends, a multi-objective optimization function and threshold constraint are established based on the quantum entanglement success rate, the path fidelity, the path distribution rate, the path resource cost and the path maximum connected component five dimensions, and fan optimal quantum routing is achieved; the offshore wind turbine layer constructs a quantum communication channel mechanism and a dense coding mechanism based on 5G, the quantum communication channel mechanism compresses a to-be-transmitted state through Huffman coding and constructs a channel through unitary transformation transmission comparison, and the dense coding mechanism transmits data through I, X, Y, Z, OC-NOT and H unitary transformation based on shared entanglement particles. The communication reliability and safety are improved, and the operation and maintenance cost is reduced.

Decoding a data stream which includes variable-length character-strings representing symbols which have been encoded in accordance with a variable-length prefix encoding scheme (such as Huffman encodi

The application discloses a privacy protection image retrieval method and system based on a ciphertext vision, belongs to the technical field of image retrieval, and aims to solve the technical problem that the existing privacy protection image retrieval method cannot simultaneously consider effective protection of image privacy content and high accuracy of image retrieval, and cannot meet current retrieval requirements. The method comprises the following steps: performing encryption processing on a to-be-queried image through a pre-defined reliable encryption algorithm to obtain an encrypted JPEG bit stream of the to-be-queried image; extracting DCT coefficients in the encrypted JPEG bit stream, and extracting corresponding image ciphertext features based on the DCT coefficients; wherein the image ciphertext features at least include a local length sequence feature and a global Huffman coding frequency feature; an unsupervised learning retrieval model based on a visual Transformer is constructed, and the unsupervised learning retrieval model is trained through a self-defined comprehensive loss function.

The application discloses a semantic compression method based on a generative large language model and Huffman coding, and comprises the following steps: S1, semantic extraction; S2, keyword coding based on Huffman coding; S3, keyword decoding based on Huffman coding; and S4, semantic recovery based on a generative language large model. The application takes keywords as carriers to extract the semantics of natural language, thereby optimizing unnecessary grammar and connectivity content without losing important semantic information, and reducing unnecessary bandwidth occupation.

This invention belongs to the field of data processing technology, specifically an optimal iterative data compression method based on Huffman coding. The method first statistically analyzes and sorts the frequencies of each symbol in the original data, performing Huffman coding at level 0 as the initial optimal result. Then, it enters an iterative replacement compression loop, sorting the current layer's data by frequency, replacing the first symbol with the second, and so on, generating a new data string and recording the replacement mask string. The new data string is then Huffman-coded again, and the total compressed length including the mask string is calculated. The result of each layer is compared with the current optimal length; if better, the optimal result is updated. This iteration continues until the number of symbol types is reduced to 1 or the total mask length exceeds the optimal length. Finally, compressed data is output, consisting of prefix coding, each layer's mask string, and the optimal layer's compressed coding string. This invention significantly improves the compression efficiency of Huffman coding by reducing symbol types through iterative pairing replacement and combining optimal layer selection.

Techniques are provided for compressing weights of models during training of the models. A model is trained for execution on a target device. As part of training, weights of the model are compressed utilizing palettes to represent weight values using bits. A coding procedure, such as Huffman coding, is used to remove or modify the bit representations of infrequently utilized palettes. The model may be iteratively trained to compress the weights of the model in order to reduce the amount of storage consumed by the model without unduly sacrificing quality of the model. Reducing the size of the model provides the ability to deploy the model on devices that would otherwise lack storage and compute resources for storing and running an uncompressed version of the model.

The present application relates to the technical field of data compression, and discloses a data saving method, system and storage medium for process program running records, which comprises the following steps: S1: extracting a running record text during process program running, reading the running record text, and determining fixed strings; S2: removing the fixed strings of the running record text by using a maximum matching algorithm, and retaining variable strings of the running record text; S3: constructing the variable strings and the fixed strings by using a Huffman tree to obtain Huffman coding; and S4: compressing the running record text by using the Huffman coding and saving it to a database. The present application realizes lossless compression technology, reduces the text volume of the running record, reduces the storage space occupation of the database, and relieves the data storage pressure. In addition, the present application adopts a split table storage strategy to separate the compressed coding data from the dictionary data, thereby avoiding single table data expansion and big data field operation bottlenecks.