71 results about "Differential coding" patented technology

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 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 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 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 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 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.

The invention belongs to the technical field of digital image transmission, and particularly relates to a digital image transmission system based on ultra-low time delay, which comprises the following steps: firstly, acquiring digital image data in a scene in real time by using a high-frame-rate and low-noise image sensor, and transmitting the acquired original image data; then, carrying out preprocessing operation on the collected original image data; then, a deep neural network model is utilized to adaptively adjust coding parameters and a coding mode according to the content characteristics of the image and the real-time transmission bandwidth condition; on the basis, the adaptive lightweight coding module is arranged, a complex inter-frame prediction algorithm in a traditional coding standard is abandoned, a block-level differential coding mode is adopted, and coding parameters and modes are adaptively adjusted according to image content characteristics and real-time transmission bandwidth; the method has the advantages that the coding delay is effectively reduced, and the high-real-time scene coding requirement is met.

The invention discloses a cross-document type retrieval method and system based on differentiated nested coding. The method comprises the following six steps: document preprocessing, document type identification, differential coding, index construction and optimization, online retrieval and result fusion. The method comprises the steps of firstly, performing standardized preprocessing on a document, and extracting structured information; secondly, a BERT classifier is used for analyzing document features, and document types are recognized; then, selecting a corresponding encoder to generate an original encoding vector according to the document type; thirdly, constructing a differentiated nested coding index, and optimizing the differentiated nested coding index; in the online retrieval stage, user query is preprocessed, related document types are predicted, and approximate nearest neighbor retrieval is executed. And finally, sorting the retrieval results through a stepped weight fusion strategy, and returning a Top-100 retrieval result. According to the method, efficient retrieval of different types of documents is realized through differential coding and index optimization, and the method has remarkable practical value and application prospect.

The application belongs to the technical field of data processing, and particularly relates to a processing process parameter monitoring method and system for glass plate processing, which comprises the following steps: performing adaptive differential coding on data sequences of a glass plate processing production line; obtaining the correlation of any two data sequences according to the similarity of the coding sequences of the different data sequences and the similarity in the adaptive differential coding process; obtaining the data quality of each data sequence based on the volatility of the coding sequences of the data sequences and the correlation of the different data sequences; and establishing a real-time monitoring model of the glass plate processing production line according to the data quality of the data sequences, the coding sequences of the data sequences and the correlation of any two data sequences. The application improves the accuracy and efficiency of real-time data monitoring of the glass plate processing production line.

Disclosed in the present application are a firmware update method for an embedded device, an embedded device, a development end device, and a firmware update system for an embedded device. The embedded device acquires patch data from a source device and decompress the patch data to obtain original differential coding data; acquires data blocks in the original differential coding data in batches, and respectively perform corresponding operations on the data blocks according to a state identifier configured to indicate the currently performed operation, until differential decoding of the original differential coding data is accomplished.

The invention relates to a remote desktop transmission method and system based on focus prediction and hierarchical optimization, and the method comprises the steps: S100, a client captures a user interaction event, calculates a prediction focus region PoR and an active context region ACR through a focus prediction model, and transmits the coordinate information and context labels of the PoR and the ACR to a server through an independent metadata channel; s200, after receiving the information, the server sends a layered rendering instruction to a graphics processor; s300, the server executes differential coding; s400, the server executes adaptive transmission; and S500, the client outputs and displays the complete desktop frame. The main purpose of the invention is to convert the graphic processing of a remote desktop from a traditional passive mode of taking a frame as the center to an active prediction and optimization mode of taking a user focus and content as the center.

Methods, systems, and devices for wireless communication are described. A user equipment (UE) can receive an indication of one or more encoding operations for encoding a compressed data set, the one or more encoding operations including a differential encoding operation or an entropy encoding operation or both. In some examples, using a neural network, the UE can first encode the data set based on an additional encoding operation to generate a compressed data set, and then quantize the compressed data set encoded based on the additional encoding operation. Subsequently, after the data set has been initially encoded and then quantized, the UE can further encode and compress the data set using the indication of the one or more encoding operations. The UE can then transmit the data set to a second device based on the one or more encoding operations.

This application relates to the field of computer technology and discloses a cross-domain digital twin synchronization method and system integrating a digital asset model library. It aims to solve the problems of bandwidth waste and state inconsistency caused by the lack of semantic awareness, coarse synchronization granularity, and missing dependency propagation in existing technologies. The method includes: performing structured parsing of the central library and local twin models based on a unified semantic meta-model framework to generate a standardized directed graph; using a graph attention network to detect node-level semantic changes; combining a static dependency graph with a dynamic execution context to prune the minimum necessary synchronization subgraph; and generating incremental packets through differential encoding and performing semantic fingerprint consistency verification. This application achieves fine-grained, high-efficiency, and semantically consistent cross-domain synchronization, significantly reducing bandwidth consumption and ensuring runtime logical correctness.

This invention introduces an energy-efficient communication protocol for Ambient IoT, integrating Slotted ALOHA with RF energy harvesting to enable reliable interaction between ultra-low-power, battery-less devices and 5G / 6G base stations or relay UEs. Devices first harvest energy from a Carrier Wave (CW) signal, followed by a structured five-message exchange (Msg0–Msg4) handling synchronization, random access, data transmission, and acknowledgments. Time-frequency resources are dynamically allocated based on device energy levels and random IDs, reducing collisions and improving throughput. Control signals use differential encoding for robustness. Each message is framed with a preamble and postamble, allowing the device to detect the start and end of the signal. Padding is inserted before the preamble to ensure alignment with NR OFDM symbol boundaries. A Slotted ALOHA-based retransmission strategy enhances channel reuse. Eliminating dedicated RFID readers, this approach supports long-range, interference-managed communication, offering a scalable, low-latency, and cost-effective solution for massive machine-type communication (mMTC) in next-generation Ambient IoT networks.

The invention relates to the technical field of digital people, and discloses a digital people display and interaction system based on multiple clients, which comprises a server system and heterogeneous client terminals, the heterogeneous client terminal collects hardware state data during operation to generate a terminal capability score, captures user input, converts the user input into virtual focus data and sends the virtual focus data to the server; the server system comprises a resource arrangement module and a gradient differential coding module; the resource arrangement module calculates the computing power budget of the current connection according to the terminal capability score; and the gradient difference coding module divides an original video frame into different image quality weight areas according to the virtual focus data, and generates a compressed video stream with non-uniform quality distribution in combination with calculation power budget. Through an end-cloud cooperation mechanism, adaptive resource scheduling and differential coding based on the terminal capability and the interaction intention are realized, and the interaction experience on heterogeneous equipment is ensured while the bandwidth and the computing power load are reduced.

The invention provides a video frame coding method and device, equipment and a medium, and relates to the field of artificial intelligence cloud computing, in particular to image processing and video coding scenes. The specific implementation scheme is as follows: performing sensitive area identification on a video frame to obtain a target area; according to a basic coding strategy, the overall basic code rate of the video frame, and the area ratio, visual sensitivity and texture complexity of the target area, code rate allocation is carried out on the target area, and a code rate allocation result of the target area is obtained; based on the code rate distribution result, performing quantization parameter adjustment on a target area and a non-target area in the video frame to obtain differential coding parameters; and adopting a video encoder to encode the video frame according to the differential encoding parameters. According to the technical scheme, the video picture quality can be improved.

A part of a data stream includes a plurality of data units respectively associated with a plurality of images and together presenting different images of the plurality of images. The data stream part further includes differential encoding data differentially encoding an artificial neural decoding network relatively to a reference artificial neural decoding network. A method for decoding this data stream part includes the following steps: determining the artificial neural decoding network by decoding the differential coding data; and decoding at least one data unit of the plurality of data units by the determined artificial neural decoding network. Another decoding method, decoding devices, a computer program and associated data streams are also described.

The invention discloses a distributed optical fiber vertical seismic DAS-VSP data capacity optimization method. According to the method, firstly, the slope difference between adjacent data points in a data point set is calculated, judgment is carried out according to a preset threshold value, redundant data points which have weak influence on the overall seismic signal trend form can be accurately recognized and deleted, and therefore the scale of the data set is remarkably reduced at the source, and first-layer compression is achieved. And then, carrying out differential coding processing on the optimized data point set after redundancy is removed, and only storing or transmitting a difference value between adjacent key data points to replace an original large value, so that the value representation range of the data is further reduced, and efficient compression of a second layer is realized. Finally, the initial data point and the differential set are packaged into a compact data frame, so that the total data amount is greatly reduced, and the resource occupation of the storage space and the network bandwidth is remarkably reduced.

This invention discloses a method and system for optimizing data interaction between intelligent terminals based on link state awareness, relating to the field of wireless communication data transmission technology. The method includes: constructing a directed acyclic graph topology; performing cooperative topology state discovery to generate a real-time link state communication topology; performing hierarchical packetization for transmission quality constraints; performing random linear network coding to obtain multiple linearly independent coded packets; performing distributed congestion-aware scheduling decisions to obtain multiple primary transmission links; performing differential coding and obfuscation transformation to obtain multiple obfuscated coded packets; and concurrently transmitting multiple obfuscated coded packets to a second terminal for Gaussian elimination decoding and reception. This invention solves the technical problems of weak topology adaptability, unreasonable congestion scheduling, and insufficient security protection in existing technologies, achieving efficient and secure data interaction between terminals and improving the real-time performance and transmission security of local area network data transmission.

The invention provides a three-dimensional reconstruction method and device, a medium and electronic equipment. The method comprises the following steps: firstly, acquiring an original two-dimensional image containing a to-be-reconstructed main body, then identifying the original two-dimensional image to determine a pixel position corresponding to the to-be-reconstructed main body contained in the original two-dimensional image, and further performing differential coding processing on the original two-dimensional image based on the pixel position to obtain a coded image, a pixel region corresponding to a to-be-reconstructed main body is coded by adopting a first coding parameter with higher coding quality, and other pixel regions are coded by adopting a second coding parameter with lower coding quality, so that the image quality of the to-be-reconstructed main body is preferentially ensured on the premise of controlling the occupation of computing resources and network transmission bandwidth of an acquisition end, and the image quality of the to-be-reconstructed main body is improved. And finally, the encoded image is sent to a server, and the server completes three-dimensional reconstruction of the to-be-reconstructed main body according to the encoded image, so that the overall efficiency and precision of three-dimensional reconstruction are effectively improved.

The invention relates to the technical field of educational informatization, and discloses a smart classroom interactive behavior real-time supervision method fused with attention recognition, and the method comprises the steps: collecting classroom video streams, carrying out the time domain differential coding through an integral issuing neuron model, and generating teacher and student end pulse streams; constructing a self-adaptive confidence mask based on the visual pulse stream of the student side, performing gating repair and interpolation on the original video signal, and reconstructing a clean physiological blood volume pulse wave signal; extracting a student physiological feature vector, and calculating a dynamic lag order parameter according to the teacher end pulse stream; and performing time-varying Granger causality test on the teacher end pulse stream and the student physiological feature vector by using the parameters, and outputting an interactive behavior judgment result. By quantifying the causal association between the teaching stimulation and the physiological response of the student, the problems that the false attention state is difficult to distinguish and the non-contact physiological signal is susceptible to action interference in the prior art are solved, and the accuracy and robustness of classroom supervision are improved.

This application relates to the field of PLC programming technology, and in particular to a fast symbol retrieval method for ultra-large multi-station PLC projects. The method involves data parsing, symbol metadata standardization, and fragment preprocessing of the PLC project file to obtain standardized SymbolMeta fragment data. Based on the standardized SymbolMeta fragment data, a three-level hierarchical index architecture is constructed, consisting of station-level hash routing, task-level compressed prefix Trie trees, and symbol-level differential encoded inverted lists. According to user query conditions, station-level fast pruning, task-level Trie tree matching, and symbol-level differential decoding aggregation are performed sequentially within the three-level hierarchical index architecture to generate structured retrieval results. Incremental updates are performed on the three-level hierarchical index architecture based on the PLC project's modification instructions. This solves the problems of high latency, weak fuzzy matching capability, high resource consumption, and delayed updates in retrieval of symbols exceeding 100,000, achieving millisecond-level accurate positioning.

A system and method for compressing temporal stacks of synthetic aperture radar (SAR) images while preserving interferometric properties. The system receives multiple SAR images acquired over time, aligns them through coregistration, and maintains phase continuity across the temporal sequence. A three-dimensional discrete cosine transform processes both spatial and temporal dimensions, creating hybrid subbands organized by frequency content and temporal change characteristics. The system employs a change-aware encoder that selectively uses differential encoding for small changes between frames and full encoding at adaptive keyframe intervals. A temporal coherence network with separate pathways for amplitude and phase information ensures consistency across the image stack. The compressed output preserves interferometric coherence properties essential for applications such as ground deformation monitoring and change detection. The system achieves compression ratios from 10:1 to 50:1 for static content while maintaining higher quality for rapidly changing features.

The application relates to the technical field of weighing sensor signal processing, and discloses a CAN-based shaft pin type weighing sensor weighing method.The method comprises the following steps: acquiring structural parameters and performing double-bridge redundant sensor positioning and symmetrical arrangement; collecting strain signals and converting the strain signals into CAN compatible data packets; performing differential coding and anti-interference transmission processing on the data packets; performing dynamic filtering and purification on the signals; compensating and verifying the signals by fusing temperature data; and finally calculating the load according to a calibration model and generating storage records.The application effectively improves the signal anti-interference capability and measurement precision, and realizes high reliability and high stability dynamic weighing.

The invention discloses a multistage correlation preamble detection method and system based on ZC sequence differential coding, related equipment and a medium, and relates to the technical field of wireless communication. The method comprises the following steps: generating a complex ZC sequence, and obtaining a binary real number lead code sequence through differential coding and symbol judgment; performing down-sampling and filtering on the received oversampling signal, and then calculating baseband signal energy through a sliding window; dividing a local lead code and a receiving signal segment into M sub-segments for correlation operation, and accumulating absolute values to obtain a synthetic correlation value; and combining sliding window energy to normalize a synthetic correlation value, and finally detecting a normalized sequence peak value to determine the initial position of a lead code. According to the invention, the low signal-to-noise ratio adaptability and the anti-frequency offset and anti-multipath capabilities are greatly improved, the calculation complexity is reduced, the resource-limited equipment is adapted, the precise detection of the lead code is realized, and the reliable establishment of a communication link under a complex channel is ensured.

A video decoding method is configured to reconstruct a current block that is encoded using an intra prediction. The method includes decoding, from a bitstream, direction information indicating a direction of differential coding applied to a residual block of the current block, generating the residual block from residual signals by reconstructing and using the information on the residual signals from the bitstream and using the direction information, inversely quantizing the modified residual block, generating a prediction block for the current block through intra prediction, and reconstructing the current block by adding the prediction block and the inverse quantized residual block.

The application discloses a kind of efficient solution of rural full life cycle carbon management, to solve the problems such as rural carbon source dispersion, monitoring is difficult, accounting precision is low and system adaptability is poor, suitable for the whole process carbon management of administrative village level, first of all, this method is deployed in key carbon source point Embedded device, capture carbon activity signal and build event sequence library containing event type, intensity and time stamp;Then, the event priority weight is calculated by assignment algorithm, and the event queue with priority label is generated, to distinguish between immediate and delayed processing events;Again, different priority events are compressed differently based on compression protocol, combined with differential encoding and adjusted compression rate according to network conditions, to generate compressed data packets;Then, the accounting simulator is issued to the edge device by the cloud;The application realizes accurate monitoring of rural carbon source, efficient transmission and accurate accounting, improves the timeliness and adaptability of carbon management, and provides scientific support for carbon emission reduction strategy.

The application belongs to the field of artificial intelligence, and particularly relates to a lightweight pedestrian dynamic feature extraction and recognition method and system based on video motion vectors. By constructing a motion decoupling and differential coding framework, the efficient pedestrian target capture and real-time low-delay recognition problem in complex motion scenarios is effectively solved. Specifically, the DiVE framework utilizes the spatiotemporal characteristics of motion vectors to accurately extract pedestrian dynamic features in dynamic environments, and reduces the computational and transmission bandwidth requirements through differential coding technology, thereby optimizing the processing performance of edge devices. This method not only improves the accuracy of pedestrian recognition, but also significantly reduces the power consumption and delay of the system, and has a wide application prospect, especially in intelligent video surveillance, autonomous driving and smart city fields.