174 results about "Differential coding" patented technology

The invention relates to the technical field of data monitoring, in particular to a complex equipment data monitoring method and system based on a knowledge graph and edge calculation. The method comprises the steps of multi-modal data acquisition and edge intelligent preprocessing; performing feature extraction on the preprocessed data; fusing multi-source heterogeneous data and constructing a dynamic knowledge graph; performing deep knowledge reasoning and layered fault early warning decision making; and performing self-optimization and knowledge closed-loop management based on early warning decision. According to the differential coding and self-adaptive compression algorithm of the edge layer, the data transmission quantity is reduced by 75%, the network bandwidth requirement is greatly reduced, and the system operation efficiency is improved.

The invention discloses an electronic lead seal automatic detection method applied to logistics tracking, and relates to the technical field of Internet of Things safety monitoring. The problems of packaging data loss, tampering risk increase and real-time monitoring failure caused by wireless communication signal interference, transmission delay and state updating lag of an existing electronic lead seal are solved. The method comprises the following steps: fusing multi-physical field sensing data through a space-time correlation sampling algorithm, and constructing an anti-interference characteristic matrix; evaluating communication quality based on the dynamic probability network model, and triggering a multi-path fragmentation concurrent transmission strategy to avoid signal attenuation; a hybrid reasoning model is deployed at an edge end to screen key event data, and the transmission efficiency is optimized in combination with differential coding and an IEEE 1588 clock synchronization mechanism; the cloud end adopts a space-time diagram fusion analysis model to carry out cross-modal abnormal association scoring, corrects misjudgment and updates an edge model; according to the invention, the communication reliability, the real-time transmission efficiency and the anomaly detection precision of the lead sealing state data in a complex environment are obviously improved.

The invention provides a frequency difference compressor based on precision perception, a gradient compression method, equipment and a medium, which are used for carrying out data compression and transmission between a server and a client so as to reduce communication overhead in personalized federated learning, and relates to the technical field of data compression. The frequency difference compressor comprises an information bottleneck rarefaction unit, a frequency domain compression unit, a dynamic quantization unit and a differential coding unit. Non-key gradient redundant components of the original gradient data are removed through an information bottleneck rarefaction unit to generate sparse gradient data; generating a metadata packet containing the first N high-energy frequency domain coefficients and the positions and the number of the first N high-energy frequency domain coefficients through a frequency domain compression unit; performing adaptive bit width mapping on the high-precision floating point gradient data into low-order integer representation through a dynamic quantization unit to generate dynamic quantization gradient data; and the differential gradient is transmitted to the client through the differential coding unit, so that data compression and transmission are completed. The method solves the problems that the communication overhead is large and gradient information cannot be reserved as far as possible in gradient transmission.

The invention discloses a cross-platform virtual-real fusion scene construction method and system based on AI space calculation, and relates to the technical field of artificial intelligence and space calculation, and the method comprises the steps: carrying out the multi-scale feature fusion based on a received cross-modal conversion instruction set, and generating an initial image sequence; carrying out implicit field coding on a target object by combining a three-dimensional reconstruction algorithm to obtain an initial parameterized model; performing space-time alignment on the multi-view video stream, loading a digital scene asset package in combination with physical sensing data and a preset spatial index structure, and establishing a bidirectional data channel between a virtual scene and a physical sensor; performing rendering and illumination parameter adjustment on the initial parameterized model to obtain an optimized parameter model; performing differential coding processing on the optimization parameter model to obtain a target virtual-real scene fusion model; and distributing the target virtual-real scene fusion model to a preset terminal. The invention provides a virtual-real fusion construction method for end-to-end collaborative optimization, which is suitable for cross-platform live broadcast or dynamic interaction scenes.

The invention provides a downlink data transmission method, device and system for laser fiber power supply application, and the method comprises the steps: carrying out the differential coding of downlink data to be transmitted through a transmitting end, and obtaining a data bit sequence; mapping the data bit sequence into a modulation symbol sequence by adopting a single-carrier phase modulation mode; performing digital-to-analog conversion on the modulation symbol sequence to obtain an analog signal; and outputting downlink energy and downlink data through an energy optical fiber according to the analog signal. According to the invention, the signal frequency spectrum is moved to be far away from the direct current frequency through differential coding and single carrier phase modulation, so that the interference of direct current laser energy on signal detection is minimized, the signal-to-noise ratio is improved, the inter-symbol interference is reduced, and a receiving end is ensured to have enough signal-to-noise ratio to reliably detect data.

The invention provides an unstructured data compression method and device, equipment and a storage medium, and the method comprises the steps: carrying out the feature extraction and clustering processing of a to-be-compressed unstructured data set, and obtaining a data segment clustering group; performing semantic region segmentation processing on each data fragment in the data fragment clustering group to obtain a semantic important region and a semantic non-important region; performing differential coding processing on the semantic non-important regions in the same clustering group to obtain differential coding data; and performing high-quality compression processing on the semantic important regions in the same clustering group, and performing merging processing on the compressed important semantic data and the difference coding data to obtain an unstructured data compression result. According to the method, semantic region segmentation and differential compression processing are performed on the unstructured data, so that the data compression efficiency can be effectively improved on the premise of ensuring the quality of important information, and an efficient solution is provided for storage and transmission of large-scale unstructured data.

The invention relates to an intelligent water affair remote monitoring and control system based on the Internet of Things, in particular to the field of intelligent water affair remote monitoring and control, and the system comprises the steps: firstly, pre-training a long and short-term memory network model through a cloud, and generating a lightweight edge prediction model to reduce calculation and transmission loads; the data transmission module effectively reduces the occupation of transmission bandwidth based on a dynamic quantization threshold value of a residual error and a differential coding technology, meanwhile, the high precision of the data is kept, the verification feedback module monitors the accuracy of the transmission data in real time through confidence coefficient detection, and triggers model re-calibration when the confidence coefficient is reduced, so that the long-term stability of the system is ensured, and the reliability of the system is improved. The sampling optimization module dynamically adjusts the sampling frequency according to the confidence coefficient and the residual fluctuation characteristics, balance is achieved between bandwidth occupation and reconstruction precision by using the Lyapunov optimization theory, the real-time performance and accuracy of water affair monitoring are improved, and meanwhile bandwidth consumption and energy consumption are effectively reduced.

The invention discloses a method for aggregating ocean buoy data, which comprises the following steps of: establishing a space-time correlation model according to the spatial distribution density of buoy clusters and the dynamic characteristics of an ocean environment, and adaptively dividing buoy groups with a data compression cooperative relationship; performing a data-related compression operation within the buoy group; constructing a transmission priority dynamic sorting engine, and calculating a dynamic weight coefficient; performing hierarchical packaging processing on the differential coding data, distributing enhanced forward error correction coding resources for high-priority data, and reserving redundant transmission time slots; the method comprises the following steps: receiving a hierarchical data packet through a low-orbit satellite and executing on-satellite preprocessing, reconstructing an original data stream by using a distributed decoder, and meanwhile, fusing multi-dimensional space-time related data to generate an aggregated data product; and finally, the aggregated data product is transmitted to a ground data center through a satellite downlink. According to the invention, uplink data volume is reduced, disaster monitoring timeliness is improved, ground station processing load is reduced, and system environment adaptability is enhanced.

The invention relates to an edge weak network-oriented wireless ad hoc network link quality discovery method, which comprises the following steps of: acquiring signal intensity of neighbor nodes through a sliding window, calculating fluctuation amplitude of the signal intensity, and judging a link stable state based on a preset threshold value; dynamically adjusting the duration of the HELLOINTERVAL timer according to the stable state of the link, and broadcasting the Hello request message at the frequency corresponding to the adjusted duration of the timer; after the neighbor node receives the Hello request, multi-dimensional service quality information is calculated, and the multi-dimensional service quality information subjected to differential coding compression is returned to the request node through a Hello response message; and after the request node receives the Hello response message, extracting and updating the link quality data in the local neighbor information table, and dynamically updating the link quality data based on the received Hello response message. The resource waste in the edge weak network is effectively reduced, the network efficiency is improved, the link quality information is ensured to be accurate and reliable, and the network robustness is enhanced.

The invention discloses a heterogeneous network converged communication control method and system for a vehicle-mounted terminal, and relates to the related technical field of communication control, and the method comprises the steps: determining a plurality of original signal fragments transmitted to a receiving end by a plurality of heterogeneous networks based on the vehicle-mounted terminal; a vehicle-mounted terminal is provided with an intermediate fusion node, and the intermediate fusion node is provided with an interference detection module and a differential processing module; carrying out adaptive signal differential coding processing according to a synchronous receiving constraint condition of a receiving end and the plurality of link interference detection signals, and outputting a plurality of differential signal fragments; and respectively sending to a receiving end for signal restoration. The technical problem that in the prior art, when a vehicle-mounted heterogeneous network sends the same or fragmented signals at the same time, due to dynamic variation of network link interference and transmission delay difference of all paths, signals at a receiving end are out of step and quality is deteriorated is solved. The technical effects that the receiving end efficiently and synchronously restores the signal, and the anti-interference performance of signal transmission and the reliability of heterogeneous network converged communication are improved are achieved.

The invention relates to a data bit width dynamic compression and decompression method for an edge computing system while drilling, and belongs to the technical field of data compression and storage. The method comprises the following steps: traversing a data set to be compressed, and taking any value smaller than the maximum value in the data set to be compressed as a reference value; calculating a difference value between each piece of data in the to-be-compressed data set and the reference value to obtain a plurality of pieces of differential data, and determining a target storage bit width according to a storage bit width corresponding to a maximum value in the differential data; and by taking the target storage bit width as a reference, encoding each piece of differential data to obtain a plurality of pieces of encoded data, and arranging the plurality of pieces of encoded data into a data stream according to an output sequence. According to the invention, the technical problem of low compression efficiency or key information loss easily caused by a compression method based on fixed reference differential coding in the prior art under the condition of coexistence of data local stability and local abrupt change is solved.

The invention discloses a fire alarm and access control linkage method and system. The method comprises the steps of signal receiving and verification, target access control determination, intelligent control release execution, anti-interference processing and cross-brand adaptation. The system comprises a multi-channel signal transmission module, a double-loop verification module, a central control unit, an intelligent control release execution module, a secondary release trigger module, an anti-interference processing module and a protocol adaptive conversion module, the problem of signal interruption caused by dependence of a traditional single channel is solved; the intelligent unlocking execution module ensures thoroughness in unlocking through graded current monitoring and a secondary release mechanism; the anti-interference processing module adopts differential coding and frequency hopping communication to resist electromagnetic interference; the protocol adaptive conversion module realizes seamless integration of multi-brand equipment, reduces the cost and maintenance difficulty, and improves the reliability and practicability of the system.

The invention provides a brain-like chip heterogeneous calculation and dynamic model updating method, which comprises the following steps: constructing a neuron pulse coding and video feature parallel calculation model, carrying out heterogeneous integration on a brain-like chip supporting an SNN pulse neural network and a multi-core processor, and constructing a spatial-temporal feature dual-channel processing unit; developing a task load balancing algorithm based on synaptic weight dynamic allocation, including constructing a resource state matrix, designing a task allocator based on reinforcement learning, and performing decision optimization in a dynamic environment; a direct memory access channel is established between a brain-like chip and a video codec, a dedicated instruction set is expanded, and motion vector data of a video encoder is read through instruction level collaboration; carrying out binary differential coding on the key layer by adopting hierarchical parameter importance sorting, and compressing the update quantity of the key layer by combining a compression algorithm; and migrating a full-amount model to a lightweight model through dynamic knowledge distillation, and dynamically generating an adaptive model in combination with an attention migration loss function.

The invention discloses a centralized phased array beam control method and system based on an FPGA, and relates to the technical field of phased array beam control, and the method comprises the steps: carrying out the real-time iterative operation through an incremental adaptive correction kernel in a centralized control FPGA, and obtaining an amplitude-phase correction increment and a corresponding target effective frame number; performing increment differential coding on the amplitude-phase correction increment and the corresponding target effective frame number in a centralized control FPGA (Field Programmable Gate Array) to generate an increment differential beam control message; sending the increment difference beam control message to an array element FPGA (Field Programmable Gate Array) at the front end of an array, executing frame-level atom switching according to a target effective frame number, and fusing the amplitude-phase correction increment and a locally stored old beam control weight in the switching process to obtain a final array element beam control weight; generating a real-time beam control directional diagram based on the final array element beam control weight; the stability and convergence precision of beam control are improved, and the bandwidth requirement of a control link is reduced.

The invention discloses a music database retrieval method and system based on feature extraction, and relates to the technical field of data analysis, and the method comprises the steps: carrying out the preprocessing of an audio signal of a query track input by a user, dividing the audio into equal-length frame sequences, and generating three-channel spectrogram tensors, including a Mel spectrogram, a logarithmic amplitude spectrogram and a CQT spectrogram; extracting multi-modal features of the equal-length frame sequence, dividing melody motivation segments according to pitch change and stability of the audio signal, performing differential coding, generating a melody differential sequence, and modeling the melody differential sequence into a melody topological graph; and calculating the structural similarity between the melody topological graph and a database melody graph, screening a similar melody candidate set P, mapping a melody curve into a topological manifold through a topological data analysis method, extracting persistent homology features, and converting the persistent homology features into a persistent bar graph. According to the method, the retrieval precision and the matching credibility of the complex melody in the music database are remarkably improved.

The invention provides a special high-throughput satellite communication terminal for electric power, and relates to the technical field of electric power communication, and the special high-throughput satellite communication terminal comprises a baseband processing module which is used for carrying out differential encryption processing on different types of electric power data; the high-throughput satellite radio frequency module is used for suppressing sidelobe interference while realizing automatic satellite beam tracking through a beam forming algorithm during satellite communication, and calculating the optimal transmitting power through a self-adaptive power regulation algorithm; the communication transmission module is used for presetting a data priority based on a priority mapping table during data transmission and preempting satellite beam resources according to the data priority; the electric power Internet of Things protocol adaptation layer is used for realizing conversion between an electric power dedicated protocol and a satellite IP protocol, differential coding compression of electric power data and interrupted transmission in a link; and the beam optimization module is used for dynamically optimizing the beam pointing angle based on the satellite orbit parameters and the terminal geographic position. According to the scheme, the coverage degree of electric power communication in remote areas can be improved, and the safety and reliability of data transmission are improved.

The invention provides an on-site video return coding method and system, and the method comprises the steps: collecting a video stream of an on-site scene, judging whether a current video frame in the video stream responds to a scene switching video frame or not, and marking the current video frame as a key frame when the current video frame responds to the scene switching video frame; after the current video frame is identified as a key frame, visual saliency analysis is performed on the key frame, and an entropy weight matrix representing regional information importance distribution in the key frame is constructed according to a visual saliency analysis result and texture information entropies of different blocks in the key frame; adjusting code rate allocation weights of different blocks in the key frame according to the entropy weight matrix and a code rate regulation and control strategy of the key frame to obtain adaptive coding configuration adaptive to content characteristics of the key frame; and performing optimization coding on the key frame through adaptive coding configuration to obtain a target code stream in response to a field video return demand. By adopting the scheme of the invention, the dynamic differential coding of the key video frame in a complex scene can be realized.

The invention discloses a pathogenic microorganism detection system based on nanopore sequencing and intelligent interpretation. The system comprises six modules including a biomolecule electric signal acquisition module and a pathogen characteristic sequence extraction module. Ion current change signals are collected through a nanopore chip array, a pathogen characteristic sequence is extracted through differential coding, a hypergraph topological structure self-adaption building module is used for building a pathogen relation model, a multi-dimensional heterogeneous pathogen parameter fusion analysis module integrates morphological parameters, metabonomics parameters and other multi-dimensional parameters, and the multi-dimensional heterogeneous pathogen parameter fusion analysis module is used for analyzing the multi-dimensional parameters. The optimized hypergraph neural network reasoning module realizes pathogen category prediction, and finally, the nanopore sequencing result intelligent interpretation output module generates a detection report containing pathogen categories, subtypes and risk levels. The system is combined with nanopore sequencing and an intelligent algorithm, pathogenic microorganism detection can be efficiently and accurately completed, the accuracy, reliability and efficiency of detection are greatly improved, and the requirement for rapid and accurate detection of pathogens in practical application is met.

The invention discloses a Bluetooth low-bit-rate audio encoding and decoding method and a related device, and the method comprises the steps: obtaining a Bluetooth real-time bandwidth, carrying out the dynamic wavelet processing of an input audio signal based on the Bluetooth real-time bandwidth, and decomposing to obtain a plurality of initial sub-band signals; quantizing the initial sub-band signal, and performing layered compression on the quantized initial sub-band signal through FSQ to obtain a compressed sub-band signal; performing differential coding processing on the compressed sub-band signal to obtain coded data; inputting the coded data into a lightweight Transform model to obtain a residual error correction item, and adding a forward error correction code to the coded data to obtain an audio data packet; packaging the residual error correction item and the audio data packet into a bit stream, and transmitting the bit stream to a decoding end through Bluetooth; and at a decoding end, performing decoding processing according to the bit stream, and recovering to obtain the target audio signal. The invention provides a high-efficiency, low-delay and low-power-consumption solution for Bluetooth audio transmission.

The invention provides a power plant high-frequency data transmission method based on a lossless compression algorithm. The power plant high-frequency data transmission method comprises the following steps of performing quality preprocessing on original high-frequency data; implementing hierarchical acquisition and periodic packaging according to data real-time requirements; performing differential coding for the data type: performing run-length coding on the switching value, and performing differential coding on the analog quantity; carrying out unified lossless compression on the coded data by using a Zstand-ard algorithm; the compressed data is encrypted and transmitted to an industrial internet platform, challenges confronted by a speed regulation system are handled through the steps, automatic optimization and dynamic adjustment of a data compression algorithm are achieved so as to adapt to the requirements of different application scenes, and the stability and efficiency of power production are improved.

The invention provides a difference and dictionary mixed compression method and device for time series data of the Internet of Vehicles, and relates to the field of data processing of the Internet of Vehicles. The method comprises the following steps: acquiring original data corresponding to a target vehicle in the Internet of Vehicles; performing first-order differential coding on the original data to obtain a first-order differential sequence; obtaining a corresponding differential disturbance factor in the first-order differential sequence through a preset model, and calculating the redundancy corresponding to the first-order differential sequence based on the differential disturbance factor; when it is confirmed that the redundancy is greater than a preset redundancy threshold value, performing second-order differential coding on the first-order differential sequence based on a differential disturbance factor to obtain a second-order differential sequence; replacing a target character string in the second-order difference sequence by using a dictionary index through a dynamic dictionary; and carrying out compression packaging on the second-order difference sequence and the dictionary index, and uploading the second-order difference sequence and the dictionary index to an Internet of Vehicles cloud. The problem that the subsequent compression efficiency is greatly reduced due to the fact that an existing method cannot adapt to the time sequence structure difference of the Internet of Vehicles data in different abnormal scenes is solved.

The invention relates to the technical field of optical storage and charging data storage, in particular to an electric energy data storage method for an optical storage and charging system, which comprises the following steps of: acquiring electric energy data of the optical storage and charging system according to a time sequence, setting a mean value window, acquiring a photovoltaic power generation power difference factor according to a photovoltaic power generation power data difference condition in each window, obtaining an optimal window length according to a photovoltaic power generation power difference factor, obtaining a data weight adjustment parameter according to a difference degree between data in the optimal window and a mean value, obtaining a data weight influence factor according to a data difference with adjacent time sequences in the optimal window, adjusting the weight of data in a reference block according to the data weight, calculating the reference block according to the weight, and obtaining a reference block; and compressing the data according to the reference block. According to the invention, the differential coding compression effect is improved.

The invention discloses a graph convolutional network accelerator and equipment based on dynamic compression and sparse reordering, the graph convolutional network accelerator comprises a combination engine, an aggregation engine, a controller and a storage unit, the aggregation engine comprises an ECSR decoder, a scheduler and a plurality of multi-core SIMD processors which are connected in sequence, the ECSR decoder is used for extracting side information from an adjacency matrix represented by a sparse compression format ECSR, the adjacency matrix represented by the sparse compression format ECSR comprises a row pointer array and a column index array, the row pointer array comprises row numbers containing non-zero elements in the adjacency matrix, the column index array stores column position indexes of all rows containing the non-zero elements, and the column position indexes of all the rows containing the non-zero elements are stored in the column index array. The column position index is generated by adopting differential coding and variable byte coding. The method aims at improving the effective data throughput rate and the memory access efficiency of graph convolutional network acceleration, improving the calculation performance during feature updating and accelerating the reasoning process of the graph convolutional network.

The invention relates to the field of video monitoring, and discloses an intelligent coding storage optimization method and system for video monitoring, and the method comprises the following steps: a) carrying out the multi-scale convolutional neural network analysis of a video frame, and extracting the multi-level features of the video frame; b) dynamically adjusting video coding parameters based on the multi-scale features; c) identifying a dynamic target in the video frame by using a target detection algorithm, and allocating relatively high coding quality to a dynamic target area; d) adaptively adjusting the brightness and the contrast ratio of the video frame according to the environment sensor data, and optimizing the video quality; and e) carrying out differential coding on the video data based on space-time redundancy compression.According to the method, intelligent coding parameter adjustment, environmental perception enhancement and data redundancy elimination mechanisms are introduced, so that the compression efficiency is improved, the environmental adaptability is enhanced and the storage and transmission cost is reduced on the premise of ensuring the video quality.

The invention discloses a method and device for transferring single-mode model data to an intelligent electric energy meter and a medium, and the method comprises the steps: S1, constructing a multi-scale feature extraction network at a device terminal, and generating a training set at a cloud end to train the multi-scale feature extraction network; s2, implementing layered distillation compression based on attention weight distribution of each layer of the model, and compensating loss precision through progressive retraining; s3, updating a model differential coding protocol, and constructing an environment perception inference engine on terminal equipment through priority channel allocation; s4, the terminal equipment records environment-false alarm associated data to construct a feedback factor matrix, and uploads verification feedback through reverse channel coding; and S5, the cloud training set generates an environmental parameter generator, the feedback factor matrix is injected into the environmental parameter generator, a model evolution evaluator is constructed based on reinforcement learning, and training and iteration are performed on a specified period. According to the invention, high-precision continuous optimization of the power anomaly detection model at the resource-constrained terminal can be realized.

The invention discloses a smart city-oriented multi-modal data transmission optimization method. The method comprises the following steps of collecting and preprocessing multi-modal original data generated in a city; performing joint feature extraction by using an improved CorrNet network and outputting an importance label; collecting operation data and carrying out regular analysis on the urban network to generate network state information; the multi-modal features, the importance labels and the network state information are associated and analyzed, and a coding control instruction is generated; performing differential compression and coding processing on the multi-modal data to generate a to-be-transmitted data queue; path calculation and resource allocation analysis are carried out, and a scheduling control instruction is generated and implemented through a tabu search method; and generating and uploading a transmission performance evaluation result based on the feedback index and the network state information. According to the method, multi-modal feature extraction, differential coding and intelligent scheduling technologies are fused, efficient and reliable transmission of urban data is realized, and the method has the advantages of high accuracy, controllable time delay and high resource utilization rate.

The invention discloses a local dynamic updating method based on a 3D tiles three-dimensional pipe network. The method comprises the following steps: detecting change data in a 3D scene; generating incremental data according to the detected change data; the incremental data is serialized into a 3D Tiles format; and optimizing the incremental data in the 3D Tiles format through a differential coding and data compression method. Through local updating, the performance is improved, the bandwidth requirement is reduced, the loading speed is increased, the user experience is improved, and the like. By reducing the transmission and loading of redundant data, local updates can more efficiently manage large-scale 3D scenes, especially in real-time or dynamically changing scenes, provide a smoother experience.

The invention relates to a dam safety state intelligent prediction method and system based on regression modeling, and the method comprises the steps: carrying out the self-adaptive wavelet packet decomposition of structural data collected by a sensor, so as to extract a time sequence feature, and carrying out the differential coding of an environment variable, so as to generate a covariable feature; the method comprises the following steps: mapping a text event into vector features through a knowledge graph, inputting the features into a mixed primary function library formed by a physical primary function and a data primary function, and constructing a sparse regression model through a dynamic gating mechanism; a physical constraint term based on a stiffness matrix and an external load matching error is introduced into the model, a causal graph is dynamically updated through an incremental PC algorithm, and a causal regularization term is added into a loss function to improve the adaptability of the model. The method is suitable for dam structure health monitoring, intelligent early warning, long-term trend analysis and other application scenes, and has good real-time performance, interpretability and small sample generalization ability.

The invention provides an edge side industrial data lightweight preprocessing caching method, and belongs to the technical field of industrial data. According to the method, the data acquisition quality is improved through Gray code anti-interference coding, dynamic sampling is realized through adaptive sampling rate adjustment and weak abnormal feature weight vectors, a fault position is accurately positioned through wavelet decomposition and a high-frequency fault feature sparse matrix, a semantic perception compression encoder is matched with a dispersion evaluation matrix to carry out differential coding, and the accuracy and the reliability of the algorithm are improved. According to the overall systematic technical scheme, the transmission path is optimized through a network transmission graph model, and all links from signal acquisition, self-adaptive processing, intelligent compression, dynamic cache management to network optimization are optimized. The technical problems that the cache occupancy rate is too high and the data transmission delay is large due to the fact that the multi-source signals of the industrial equipment are difficult to pre-process efficiently on the edge side are solved.

A method and apparatus for loop filtering are provided, which reduce the computational complexity of loop filtering, accelerate the computational speed, and improve the encoding and decoding performance by optimizing the encoding method in the encoding and decoding loop filtering process. A method for loop filtering includes: determining multiple sets of filter coefficients for loop filtering; and encoding the multiple sets of filter coefficients using a non-differential encoding method. Another method for loop filtering includes: determining correction index parameters for loop filtering; and encoding the correction index parameters using a non-exponential Golomb encoding method. A method for loop filtering is also provided, including: determining loop filtering correction parameters for the luminance component and loop filtering correction parameters for the chrominance component of an image frame; wherein the loop filtering correction parameters for the luminance component and the loop filtering correction parameters for the chrominance component are parameters selected from the same parameter list.