121 results about "Source encoding" patented technology

A method and system for training a target neural network using a foundation model having a source neural network that has been pre-trained to operate on a source modality. Inputting source data to the foundation model. The source neural network of the foundation model having at least one source encoder having a source weights which has been pre-trained to compute source features which are computable within the source data of the source modality. Inputting target data to a target neural network operating on a target modality. The target neural network including at least one target encoder having target weights for computing target features within the target data of the target modality. Training the target weight by pairing the target data with the source data and freezing the source weights of the source neural network for a pre-determined epoch.

The invention discloses a frequency domain ground penetrating radar transmitting source coding and receiving signal synthesis method and system. The method comprises the following steps: constructing a frequency domain coding continuous wave ground penetrating radar transmitting signal by extracting amplitude and phase information of multiple frequency points of a time domain ultra-wideband transmitting pulse; adopting a fast forward modeling method based on impulse response to realize forward modeling of a coding source emission signal of the typical geoelectric model; in-phase components and orthogonal components of all frequency points are extracted, frequency responses are synthesized into responses of quasi-time-domain transmitted pulses through an inverse Fourier transform method, the high resolution equal to that of time-domain ultra-wideband transmitted signals is obtained, and higher anti-noise performance is achieved. According to the invention, the amplitude phase coding continuous wave transmitting signal is adopted, so that the frequency spectrum shaping of the quasi-time domain pulse of the transmitting frequency spectrum is realized, the resolving power of the synthetic signal is improved, and a theoretical basis is laid for signal synthesis of frequency domain ground penetrating radar hardware design.

The invention provides a power distribution equipment abnormity identification and life prediction method based on an improved EGNN network, and the method comprises the steps: taking a characteristic value of power distribution equipment and an electrical connection structure relation as an input source, carrying out the coding of multi-modal data, carrying out the geometric preprocessing, and constructing a geometric invariant representation system; feature fusion is carried out by adopting an E (n)-EGNN architecture, and geometric invariance and physical rule consistency are ensured by combining a cross-modal projection matrix, a physical constraint item and a dynamic topology updating mechanism; abnormal detection adopts a dual-path mechanism to reduce false alarms; the service life prediction is realized by integrating a grey fuzzy evaluation model and Bootstrap resampling: obtaining the service life state probability of the target power distribution equipment by using grey correlation analysis and a whitening weight function, generating a dynamic confidence interval based on Bootstrap resampling, obtaining a visual service life scoring interval, and realizing accurate prediction of the service life of the power distribution equipment. And the confidence coefficient and the engineering applicability of the prediction result are obviously improved.

The invention relates to the technical field of computers, and discloses an information source coding matrix data processing method based on a modified conjugate gradient algorithm. According to the method, sparsity constraint and a fixed-point quantization mechanism are fused in iterative optimization, and a sparse fixed-point coding matrix meeting hardware deployment requirements is directly generated through gradient shielding, correction conjugate parameter calculation and Armijo criterion line search and synchronous execution of hard threshold sparseness and fixed-point quantization after each update. According to the method, the sparsity constraint and the fixed-point quantization mechanism are embedded in the iteration process of the modified conjugate gradient algorithm, so that end-to-end alignment of coding matrix optimization and hardware deployment requirements is realized.

Systems, methods, apparatuses, and computer program products for semantic communication involving joint source and channel coding (JSCC) over current communication networks. One method may include receiving, by a first network entity, from a second network entity, a multi-level bit error rate (BER) interface configuration comprising at least one BER based upon the request for a communication session; generating, by the first network entity, an application source encoder and decoder configured to encode and decode, respectively, a plurality of levels corresponding to the at least one BER; and training, by the first network entity, the application source encoder and decoder according to the BER.

The invention relates to the technical field of waste paper detection, in particular to an AI-based waste paper whole-process detection method and system, which comprises the following steps: collecting image side line extension angle statistics color matching identification, coding direction sequence comparison identification offset, positioning an infrared adjustment frequency generation instruction, and correlating serial number contrast data to generate a linked list. And extracting a difference value to judge that the overrun output is abnormal. According to the method, in image processing, abnormal paper parcels are compositely recognized through sideline interruption, break angle errors and color strip density, a multi-dimensional judgment mechanism is constructed in combination with source codes, in path tracking, a direction sequence is adopted to recognize an offset trend, infrared monitoring frequency is dynamically adjusted, and a high-risk area is focused; in the detection link, quality and moisture data are connected in series through paper package numbers, a time sequence contrast linked list is constructed, and potential deviations are screened by fusing difference floating and trend cross validation, so that anomaly identification precision, monitoring response rapidness and data tracking closed loop are realized.

The invention discloses a pre-training model and multi-source coding feature fusion-based water pollutant molecular property prediction method and system, and relates to the technical field of environmental science and artificial intelligence crossing. Comprising the steps of collecting pollutant data; the collected pollutant data is preprocessed; taking SMILES as a molecular input basis, and extracting molecular features; according to the molecular features, feature vectors are obtained from an encoder and then input to a vector interaction module for feature fusion; and embedding the comprehensive molecules obtained after feature fusion into an expert mixed structure module to obtain comprehensive representation of an expert mechanism, inputting the comprehensive representation of the expert mechanism into a preset prediction head, and completing prediction of molecular properties through the prediction head. According to the method, the molecular language model features, the molecular graph neural network features and the molecular descriptor features are integrated, and feature fusion is carried out by utilizing an attention mechanism and residual connection, so that high-precision prediction of the molecular properties of pollutants is realized.

The invention discloses a water conservancy project construction progress and resource allocation intelligent optimization system, and relates to the technical field of water conservancy projects, and the system comprises a resource identification generation module which employs a Hash algorithm to generate unique identification codes for each batch of construction resources used in a water conservancy project construction process, calculating according to the resource attribute information, the construction task code and the batch identification associated data to obtain a non-repeatable digital resource code; when the same batch of resource information is detected, grouping identification is carried out according to a time sequence, a unified coding system covering the whole process of purchasing, transportation, entering, warehousing and construction is formed, and space coordinate basic data corresponding to each resource is generated; according to the intelligent optimization system for the construction progress and resource allocation of the water conservancy project, accurate control of the construction progress of the water conservancy project, intelligent optimization of resource allocation and comprehensive visualization of operation of a construction site can be realized, and the management efficiency, the resource utilization rate and the overall construction quality of the construction of the water conservancy project are greatly improved.

A HARQ method implemented in relation to channel coding may be suboptimal in that the HARQ method does not leverage features of the source coding. For example, it makes no difference to the HARQ method whether source coding is even performed, let alone whether some portions of the compressed bits output from the source encoder have higher levels of priority, e.g. higher levels of importance to the success of the source decoding. In some embodiments, a HARQ method for source coding is provided. The HARQ method for source coding may be performed with or without channel coding. A first set of source encoded bits may be sent in a first transmission (e.g. an initial transmission), and a second set of source encoded bits may be sent in a second transmission (e.g. a retransmission) based on feedback. The feedback may be an indication of source decoding outcome.

The invention discloses a DNA image transmission method and device based on deep joint source channel coding, and relates to the field of image coding, and the method comprises the steps: S1, constructing an image coding model, a channel simulation and sequence preprocessing module and an image decoding model; s2, acquiring a training data set; s3, training and optimizing the image coding model and the image decoding model; s4, acquiring an image to be transmitted; s5, encoding the image encoding model; s6, a channel simulation and sequence preprocessing module performs channel simulation and sequence preprocessing to obtain a numerical matrix; s7, the image decoding model decodes and reconstructs the image; according to the method, through an end-to-end integrated design, image compression, base mapping, DNA channel simulation and biological constraint optimization are integrated into the same neural network framework, deep collaboration of source coding and channel coding is realized, a high-fidelity image can still be recovered in a noise environment, and the method is suitable for large-scale popularization and application. Therefore, the overall efficiency and reliability of the DNA image storage process are greatly improved.

The invention relates to the technical field of material management, in particular to a cross-coding system material code automatic mapping and conversion method, which provides basic data support for dynamic mapping by acquiring historical material codes and mapping codes thereof as a training verification set and extracting structural feature vectors and code element value ranges of coding systems. A material code is subjected to sliding segmentation by utilizing a segmentation window technology, and a source coding system is determined by combining structural similarity and a code element value range, so that dynamic analysis and inverse coding processing of a complex coding structure are realized; and quality evaluation and parameter correction are carried out based on the similarity between the converted code and the mapping code, and limitation of static transcoding is avoided. According to the automatic mapping and conversion method for the material codes of the cross-coding system, the adaptive capacity and the dynamic adjustment capacity of transcoding are remarkably improved, and an effective scheme is provided for conversion and mapping of the codes in the large-scale material coding system.

Method for model-based prediction in critically sampled filterbanks, audio signal processing device and computer-readable storage medium SOLUTION: A method in an audio source coding system determines a first subband signal of an audio signal using an analysis filterbank (612) comprising a plurality of analysis filters providing a plurality of subband signals in a plurality of subbands, determines model parameters (613) of a signal model, and determines prediction coefficients to be applied to previous samples (614) of a first decoded subband signal derived from the first subband signal based on the signal model, based on the model parameters and based on the analysis filterbank. The time slot of the previous sample is before the time slot of the first sample 615. The method also determines an estimate of the first sample by applying the prediction coefficient to a previous sample.SELECTED DRAWING: Figure 6b

The invention belongs to the technical field of information processing, and discloses a cross-modal information source encoding and decoding method based on semantic association, and the method specifically comprises the following steps: obtaining information source signals of a plurality of modals, inputting the information source signals into an encoding end, determining a main modal according to the service quality index parameters of each modal, and enabling the other modals to be secondary modals; according to the type of the main modal signal, adopting a corresponding preset coding strategy to perform feature retention type coding processing on the main modal signal source signal so as to retain semantic features necessary for cross-modal decoding; semantic prior information between the primary mode and each secondary mode is constructed and used for describing a semantic label of a primary mode information source signal and a semantic consistency relation between the primary mode and the secondary modes; dividing the sub-modal signal source signal into a semantic correlation signal part and a semantic irrelevant signal part based on semantic prior information; the problems of low multi-modal coding efficiency and insufficient cross-modal semantic redundancy utilization in the prior art are effectively solved.

The invention relates to the technical field of natural language processing, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a text style conversion control method, device and equipment and a medium. Performing text word segmentation on the source text and the target style description text to obtain a corresponding source text sequence and a corresponding target style sequence; performing style feature extraction on the source text sequence and the target style sequence to obtain corresponding source text style features and target style features; determining a target style feature conversion parameter according to the source text style feature and the target style feature; performing text coding on the source text sequence to obtain a source coded text sequence; and performing style conversion on the source coding text sequence according to the target style feature conversion parameter to obtain a target style text. The text style conversion efficiency and style control granularity can be improved.

An acoustic remote control device and method for a bionic robotic fish, relate to underwater acoustic telemetry remote control. The device is composed of an acoustic emission module, an acoustic receiving module and a remote control terminal. The data of the remote control terminal is output to the acoustic emission module through wireless communication, the data of the acoustic emission module is output to the acoustic receiving module through acoustic communication, and the acoustic receiving module outputs control instructions to the bionic robotic fish through an RS232 serial port. The acoustic emission module is used to receive instructions from the remote control terminal through a wireless transceiver, complete channel coding, modulation and underwater acoustic signal transmission of the remote control instructions. The bandwidth of the underwater acoustic emission transducer is divided into two sub-bands B1 and B2. User instruction data is grouped by Hamming coding, information bits are sent through the B1 sub-band, and check bits are sent through the B2 sub-band. The remote control terminal receives user instructions through a remote control panel, source encodes the user instructions, and sends the encoded data to the acoustic emission module through a wireless transceiver.

The invention discloses an information transmission method and device, communication equipment and a readable storage medium, and belongs to the technical field of communication, and the information transmission method comprises the steps that first communication equipment processes to-be-transmitted first information into second information according to a first processing mode; sending second information to a second communication device; the first processing mode comprises any one of the following steps: performing channel coding on the first information to obtain third information, and mapping the third information which is not modulated into second information based on a first mapping relation; mapping the first information which is not subjected to source coding, channel coding and modulation into second information based on a second mapping relation; mapping the first information which is not subjected to source coding into third information based on a third mapping relation, and then performing channel coding and modulation on the third information to obtain second information; and mapping the first information which is not subjected to source coding and channel coding into third information based on a fourth mapping relationship, and modulating the third information to obtain second information.

A low-power communication method and apparatus for a wireless audio device, an SoC chip, and a storage medium. The low-power communication method for a wireless audio device comprises: sampling acoustic features of heterogeneous audio data from multiple target audio devices, calculating speech spectra corresponding to device characteristics, extracting multi-device acoustic features, and performing multi-frequency sub-band speech enhancement, heterogeneous segmentation and grouping of the multiple target audio devices, check value calculation, and differentiated encoding on each extracted acoustic feature sequence to obtain a multi-source encoded speech segment; dividing the multi-source encoded speech segment into transmission units, and performing cooperative signal modulation, cooperative resource allocation, and data stream transmission on each transmission unit to obtain a transmitted speech data stream; and acquiring the transmitted speech data stream transmitted with low power, and performing audio recovery on the transmitted speech data stream to obtain a target audio data stream transmitted by the multiple target audio devices, thereby reducing the communication power consumption of the multiple target audio devices and ensuring the audio transmission quality.

This invention relates to the field of computer technology and discloses a method for processing source coding matrix data based on a modified conjugate gradient algorithm. This method integrates sparsity constraints and fixed-point quantization mechanisms in iterative optimization. Through gradient masking, modified conjugate parameter calculation, and Armijo criterion line search, and by synchronously performing hard-threshold sparsification and fixed-point quantization after each update, it directly generates a sparse fixed-point coding matrix that meets hardware deployment requirements. This invention achieves end-to-end alignment between coding matrix optimization and hardware deployment requirements by embedding sparsity constraints and fixed-point quantization mechanisms within the iterative process of the modified conjugate gradient algorithm.

A communication method and apparatus are disclosed. In this method, first data from the application layer of a fifth device is received, and second data is transmitted. The second data is data obtained by jointly source-coding and channel-coding the third data. The third data is determined based on the first data, and the entropy rate of the third data is less than that of the first data. Joint source-coding and channel-coding may include, for example, semantic feature extraction and channel-coded data. For instance, the third data is data obtained by processing the first data, and this processing may include one of the following: decryption, entropy decoding, sequential decryption and entropy decoding, or sequential entropy decoding and decryption. This reduces the entropy rate of the data, thus enabling joint source-coding and channel-coding of the third data.

The application provides a passive coding device positioning and tracking method and device, and relates to the technical field of computers, and comprises the following steps: acquiring original data of radio frequency signals reflected by all passive coding devices arranged in a monitoring area; performing feature separation according to the original data of the radio frequency signals to obtain a signal baseband feature set; performing propagation path derivation according to the baseband feature set to obtain channel impulse responses describing environmental reflection characteristics; performing device position probability field construction according to the channel impulse responses to obtain a position probability distribution of the device in the monitoring area; performing motion trajectory function fitting according to the position probability distribution to obtain a space-time trajectory function of the device; and performing trajectory optimization under physical constraints according to the space-time trajectory function to obtain a positioning and tracking result. The application realizes high-precision and stable and continuous positioning and tracking of passive coding devices in a complex electromagnetic environment.

This invention discloses a source-channel joint encoding and decoding method based on a cross-modal communication system, relating to the field of cross-modal image signal reconstruction technology. The method includes: First, designing a cross-modal source encoder, inputting tactile signals and image signals with category labels into the encoder to mine deep-level fusion feature information between modalities. Second, designing a channel encoder and channel decoder, directly mapping the extracted fusion features into a bitstream for channel transmission, improving the system's adaptability to channel changes. Finally, designing a corresponding source decoder at the receiving end to complete high-quality image signal reconstruction from deep-level feature information. The source-channel joint encoding and decoding method provided by this invention reduces power consumption in the network, uses a fitness function to measure the load balance between the cloud network and the server (host), transforming the load balancing problem into an optimization problem, thus making it suitable for resource optimization. Using the particle swarm optimization results as the initial population for the genetic algorithm, this invention achieves better results in terms of execution cost, load balancing, and completion time.

Computer-implemented methods for determining and displaying correspondence between source data and target data. Aspects include receiving source tokens associated with source data and target tokens associated with target data, generating source encodings for each source token of the set of source tokens, and generating target encodings for each target token of the set of target tokens. Aspects include receiving an indication of a selected source token associated with the source data. Aspects further include determining an identified target token from the set of target tokens corresponding to the selected source token by calculating distances between the selected source token and each of the target tokens in the high-dimensional latent space using the source encodings and the target encodings. Aspects include displaying a correspondence between a portion of the source data corresponding to the selected source token and a portion of the target data associated with the identified target token.

This invention provides a wideband coded metasurface based on diffuse reflection effect, comprising: periodically arranged coded units printed on the surface of a dielectric substrate; each coded unit includes a periodically arranged first coded subunit and a second coded subunit; the first coded subunit includes right-angled triangular patches connected in pairs via varactor diodes; the second coded subunit includes right-angled triangular patches connected in pairs via rectangular microstrip patches; the designed coded metasurface has two operating states: a passive coded metasurface when not powered, and an active coded metasurface when powered. This invention features ultra-wideband diffuse reflection characteristics, achieving significant RCS reduction in the 25GHz–50GHz millimeter-wave range, while easily switching between passive and active operating states, and is easy to fabricate and conformally conform to.

Some wireless communication systems utilize channel feedback to improve communication reliability or quality. For example, a network entity may transmit a channel state information reference signal (CSI-RS) to a user equipment (UE). The UE may determine channel state information (CSI) feedback based on the CSI-RS and send the CSI feedback (e.g., a CSI report) to the network entity. The network entity may utilize the CSI feedback to perform power control, resource allocation, or scheduling. Some examples of the techniques described herein may enable joint source encoding for multiple configured CSI-RS resources within a CSI report. Some of the techniques described herein may allow for expanded CSI reporting, which may enable greater visibility and control of communications based on channel conditions, which may enhance link quality and performance. For example, joint source encoding of parameters may compress the information, allowing more parameters to be communicated with enhanced efficiency.

The invention provides a passive coding equipment positioning and tracking method and device, and relates to the technical field of computers, and the method comprises the steps: obtaining radio frequency signal original data reflected by all passive coding equipment disposed in a monitoring area; carrying out feature separation according to the original data of the radio frequency signal to obtain a signal baseband feature set; performing propagation path derivation according to the baseband feature set to obtain a channel impulse response describing environmental reflection characteristics; constructing an equipment position probability field according to the channel impulse response to obtain the position probability distribution of the equipment in the monitoring area; performing motion trail function fitting according to the position probability distribution to obtain a space-time trail function of the equipment; and trajectory optimization under physical constraint is carried out according to the space-time trajectory function, and a positioning tracking result is obtained. According to the invention, high-precision, stable and continuous positioning tracking of the passive coding equipment in a complex electromagnetic environment is realized.

Object detection encoder training using a base model is provided. A method and system for training a target neural network using a base model having a source neural network that has been pre-trained to operate on a source modality. And inputting the source data into the basic model. A source neural network of the base model has at least one source encoder having source weights that have been pre-trained to compute source features that can be computed within source data of a source modality. And inputting the target data into a target neural network operating on the target modality. The target neural network includes at least one target encoder having a target weight for calculating a target feature within the target data of the target modality. The target weight is trained by pairing the target data with the source data and freezing the source weight of the source neural network for a predetermined period of time.

Methods and servers for performing vertical federated learning (VFL) over a communications network are disclosed. Some methods include encoder and data selection, encoder customization, and VFL configuration. Encoder and data selection includes receiving a VFL request and parsing it to determine data requirements and encoder requirements, selecting a first encoder and a second encoder based on the encoder requirements, and selecting data sources for the first encoder and the second encoder based on the data requirements. Encoder customization includes selecting a first encoder and a second encoder and customizing the first encoder by muting portions of the first encoder. VFL configuration includes receiving labeled data information and an indication of a loss function, configuring an evaluator using the labeled data information and the indication of the loss function, configuring the encoder output to a combined classifier, and configuring a privacy router.

A quantum source coding method includes: initializing a quantum register having a plurality of nodes: loading a unary-coded message into the quantum register; loading an address state into an address register of each message node of the quantum register; sorting the message nodes based on a data register such that the message nodes form a message-sorted sequence; and applying, for each message node at an end of the message-sorted sequence, a CNOT gate to the address state of each of the register's message nodes and output nodes. The method also includes: unsorting the message nodes; sorting the nodes based on the address register such that the nodes form a fully-sorted sequence; applying, for each pair of adjacent nodes in the fully-sorted sequence having the same address state, a CNOT gate to the data registers of each pair; and unsorting the nodes to return the fully-sorted sequence to the initial sequence.

The invention discloses a multi-user source channel adaptive semantic coding method based on deep learning, and the method comprises the following steps: S1, constructing a multi-user semantic communication system based on a deep neural network: at a transmitting end, processing a to-be-transmitted signal through a deep source encoder and a digital channel encoder, and transmitting the to-be-transmitted signal through a digital channel encoder; carrying out superposition numbering and signal transmission; at a receiving end, the received signal is processed by a digital channel decoder and then is processed by a data user decoder and a semantic user decoder to obtain information source data and semantic information; s2, performing end-to-end distortion modeling of the data user and the semantic user based on data regression; and S3, carrying out joint optimization on the source channel coding rate, the power distribution and the beam forming. According to the method, a multi-user broadcast channel is considered, and an information source channel rate, power distribution and beamforming joint optimization algorithm is designed, so that weighting and end-to-end distortion of a multi-user system are reduced to the maximum extent.

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.