1743 results about "Decodes" patented technology

The invention provides a satellite image and actually measured RSRP fused ground radio map generation system, and the system comprises a satellite image feature extraction module which is used for converting a high-resolution satellite image of a target region into high-dimensional image features reflecting the ground feature type distribution of the region; the base station physical characteristic input module is used for converting the physical parameters of the communication base station in the target area into characteristic vectors reflecting electromagnetic propagation characteristics; the multi-modal fusion module is used for fusing the high-dimensional image features and the feature vectors to generate joint feature representation; the radio map decoder is used for generating a radio signal power plane distribution diagram of the target area through a decoding network based on the joint feature representation; and the ground RSRP correction module is used for correcting the radio signal power plane distribution diagram output by the radio map decoder so as to output a final radio signal power distribution result. According to the invention, the space-ground collaborative data source fusion is realized to improve the mapping precision.

A system and method for handling acknowledgments in a wireless system. In some embodiments, the method includes, receiving, by a User Equipment (UE), one or more first transmissions; decoding, by the UE, the first transmissions, to generate a first sub-codebook including one or more corresponding Hybrid Automatic Repeat Request Acknowledgement (HARQ ACK) bit strings each having a first length; receiving, by the UE, one or more second transmissions; decoding, by the UE, the second transmissions, to generate a second sub-codebook including one or more corresponding HARQ ACK bit strings each having a second length, greater than the first length; receiving, by the UE, one or more third transmissions; and decoding, by the UE, the third transmissions, to generate a third sub-codebook including one or more corresponding HARQ ACK bit strings each having a third length, greater than the second length.

The invention discloses a soft decoding method and device, a medium and a product, and relates to the technical field of error correction coding, and the method is applied to a low-density parity check code, and comprises the steps: obtaining a target low-density parity check code with an information node and a check node containing an erasure bit; and allocating a preset non-zero log-likelihood ratio to the erasure bit on the check node, and executing first soft decoding. And if the first soft decoding fails, judging whether to carry out second soft decoding or not based on the weight of the syndrome generated by the first soft decoding and the number of the erasure bits on the information node. If it is judged that the second soft decoding needs to be carried out, a preset non-zero log likelihood ratio is distributed to the erasure bit located on the information node, and the second soft decoding is carried out. According to the method and the device, the erasing bits on different nodes are conditionally processed in stages, so that the success rate and the efficiency of decoding are effectively improved.

The embodiment of the invention relates to the technical field of exploration and development, and provides a well logging curve reconstruction method, device and equipment, a storage medium and a product, the method comprises the steps that an original well logging curve in a specified time period is obtained, the original well logging curve comprises a to-be-reconstructed well logging curve and a plurality of basic well logging curves, carrying out representation learning on the original logging curve to obtain an initial feature vector matrix; the initial feature vector matrix is input into a pre-trained curve reconstruction model, a reconstruction curve of the to-be-reconstructed logging curve is obtained, the curve reconstruction model comprises at least one decoding layer, and the decoding layer comprises an asymmetric causal attention layer, a first normalization layer, a feedforward network layer and a second normalization layer; the asymmetric causal attention layer is used for extracting the space-time correlation weight of the initial feature vector matrix. According to the embodiment of the invention, the reconstruction precision of the logging curve can be improved, so that accurate and reliable data support is provided for exploration and development decisions of oil and gas fields.

Disclosed in embodiments of the present application are an encoding method, a decoding method, a code stream, an encoder, a decoder, and a storage medium. The decoding method includes: decoding a relevant syntax element of a current block; according to the relevant syntax element, determining to use an intra-template matching prediction (TMP) (IntraTMP) merged intra prediction mode to perform prediction on the current block; determining a matching block of the current block on the basis of a TMP mode, and determining a first predicted block of the current block according to the matching block; determining a second predicted block of the current block on the basis of a non-template matching intra prediction mode; and merging the first predicted block and the second predicted block to determine a final predicted block of the current block.

The embodiment of the invention provides a model training method, an information recommendation method, equipment, a storage medium and a program product. According to the embodiment of the invention, a multi-encoder-multi-sub-decoder-total decoder hybrid model architecture is provided, sample data of different information modes correspond to different encoders-sub-decoders, and a mode of processing all training sample data by a single model is converted into a divide-and-conquer mode. The internal complexity of each encoder-sub-decoder is relatively low, the complexity of model training can be reduced, resource consumption can be saved, and different encoder-sub-decoders can be trained in parallel, so that the model training time can be shortened; and furthermore, by utilizing a dual decoding mechanism of the sub-decoder and the global decoder, parameters of the encoder can be continuously adjusted through local optimization and global optimization, the performance of the model is optimized, the accuracy of a reasoning result is improved, the convergence speed of the model is accelerated, the model training efficiency is further improved, and the model training time is saved.

The embodiment of the invention discloses a video encoding and decoding method and device, equipment and a medium. The method comprises the following steps: a coding end determines a mode identifier corresponding to a sub-block according to a coding mode of a target transformation block for representing binarization coding distribution of a non-zero transformation coefficient at an internal position of the sub-block, and codes the mode identifier to obtain coding information of the target transformation block, so that the coding end or a decoding end carries out decoding according to the coding information of the target transformation block, and the target transformation block is decoded. And obtaining a coding mode for representing the binarization coding distribution of the non-zero transformation coefficients at the internal positions of the sub-blocks, thereby realizing the determination of the positions of the non-zero transformation coefficients corresponding to the target transformation block. According to the technical scheme, the coding and decoding efficiency of the transform block is improved, and the video coding and decoding reliability is high.

Disclosed herein are a decoding method and apparatus and an encoding method and apparatus for deriving an intra-prediction mode. An intra-prediction mode may be derived using a method for deriving an intra-prediction mode based on a neighbor block of the target block, a method for deriving an intra-prediction mode using signaling of the intra-prediction mode of the target block, or a method for deriving an adaptive intra-prediction mode based on the type of a target slice. An MPM list may be used to derive the intra-prediction mode, and a temporal neighbor block or the like may be used to configure the MPM list.

The invention discloses a time sequence prediction method and system based on adaptive period segmentation and parallel decoding, and the method comprises the following steps: judging the period length of time sequence data, segmenting the time sequence data according to the period length, and obtaining time sequence segmentation data; adaptively adjusting the hiding dimension of the embedded layer according to the period length, and mapping the time sequence segmentation data into the hiding dimension to obtain a time sequence representation; the obtained time sequence representation is input into a Transform encoder to carry out feature extraction; the decoder input is initialized according to the Transform encoder output, the initialized decoder input and the encoder output are subjected to feature interaction in the decoder based on a cross attention mechanism, and finally prediction output is obtained. According to the method, a more flexible period segmentation scheme and a decoding mechanism are adopted, the reasoning efficiency is improved, accumulative errors are reduced, and the time sequence basic model can achieve a better prediction effect with fewer parameters.

The invention relates to a Manchester coded signal decoding method and a Manchester coded signal decoding system, and belongs to the field of electronic information, communication and power system automation. A plurality of clocks with the same frequency and different phases are generated according to Manchester encoding signals, the clocks are used for sampling the signals, a phase-shifting clock sampling method is used, dependence on a high-frequency clock is reduced, most interference in communication signals is determined to be eliminated according to a majority voting strategy for sampling results, and the accuracy of the signals is improved. And the seriously distorted signals are corrected according to special value enumeration, so that the interference of signal duty ratio distortion and burrs is reduced, and the decoding reliability is further improved. And finally, determining an original data stream of the signal according to the two level states of each code element. The method is used for decoding high-speed and ultra-high-speed Manchester encoding signals under the conditions of no high-frequency clock, poor data signal quality or unstable clock, and simultaneously realizing self-adaptive communication of different encoding formats.

The invention provides a coding method and system of a Transform class model for channel state information prediction. The coding method comprises the following steps: S1, acquiring and processing channel state time sequence data; s2, inputting the processed data into an encoder to extract features; s3, CFR data needing to be predicted are embedded, and position codes of the model are added; decoding the relevant parameters using a decoder; s4, processing the output of the decoder, and predicting channel state information; and S5, taking the CFR data and the CSI data obtained in the actual scene as the input of the model, and predicting channel frequency response information. According to the method, the time sequence characteristics of the channel state information are calculated and coded, and the time information is brought into the model, so that the relative stability time of the channel at the future moment is considered, the problem of weak time sequence information embedding capability in a Transform model is solved, and the accuracy of channel state prediction is improved.

The video encoding / decoding method and apparatus according to the present invention can: determine a reference area for intra-frame prediction of a current block; derive an intra-frame prediction mode of the current block; and decode the current block based on the reference area and the intra-frame prediction mode.

In a video encoding / decoding method and device according to the present invention, a merge candidate of a current block may be determined, a merge candidate list may be configured on the basis of the merge candidate, motion information of the current block may be derived from the merge candidate list, and the motion information may be used to perform inter prediction of the current block.

This invention discloses a method for camouflaged target detection, belonging to the field of camouflaged target detection. This method constructs a BiSAM based on the SAM network. The SAM encoder, CNN encoder, and dual-domain cascaded attention module BCAM work collaboratively to enrich multi-scale feature information and extract multi-source features from the input image. Specifically, BCAM operates collaboratively in the spatial and spectral domains, selectively recovering and enhancing high-frequency object boundaries while suppressing irrelevant background noise. The multi-source features are fused using AKM to guide the SAM decoder in decoding the ViT image embedding. The method replaces the original position encoding of the cross-attention key vector in the SAM decoder, injecting task-specific knowledge into the frozen SAM decoder. By replacing the original position encoding, the general attention key vector is transformed into a task-aware attention key vector, specifically adapted to camouflaged target detection scenarios, thereby improving the accuracy of camouflaged target detection while maintaining generalization ability.

The invention discloses a multi-dimensional time sequence anomaly detection method based on correlation characteristics and multi-scale integrated decoding. The method comprises a coding stage, a decoding stage and an anomaly detection stage. In the encoding stage, by investigating the correlation between dimensions and the dependency of time, calculating a correlation feature matrix between the dimensions, and mining effective implicit features by using a convolution encoder; in the decoding stage, decoders with different scales are used for decoding the output of the coding layer, the outputs of the decoders are fused, and finally a reconstructed feature matrix is obtained; in the anomaly detection stage, the anomaly is identified by using errors of the reconstruction matrix and the original feature matrix; the method effectively solves the problems that in the prior art, correlation between the sequences is not considered, and a decoder is prone to error accumulation in the decoding process, and has the advantage that the correlation between the sequences and the time dependence of data can be effectively modeled.

The methods, devices, and systems discussed herein utilize a 2-stage Sidelink Control Information (SCI) design when a forwarding user equipment device (UE) forwards the time-frequency location of communication resources that (1) have been reserved by another UE, or (2) are available for the receiving UE to use for device-to-device (D2D) data transmissions. In some examples, the 1st and 2nd stages of the SCI are required to decode the data channel. In these examples, part of the SCI is in the 1st stage, and the remaining part is in the 2nd stage. Thus, a UE that receives the 2-stage SCI decodes the 1st stage for sensing whether the associated data channel is being used. The 2nd stage has the remaining relevant SCI required to demodulate and decode the same associated data channel.

To provide a method and apparatus for improving image coding efficiency.SOLUTION: An image decoding method includes the steps of: acquiring a sign data hiding enable flag; acquiring a transform skip residual coding (TSRC) enable flag based on the sign data hiding enable flag; acquiring residual information for a current block based on the TSRC enable flag; deriving a residual sample of the current block based on the residual information; and generating a reconstructed picture based on the residual sample. The sign data hiding enable flag is a flag indicating whether sign data hiding is enabled, the TSRC enable flag is a flag indicating whether TSRC is enabled, and the TSRC enable flag is acquired based on the sign data hiding enable flag having a value of zero.SELECTED DRAWING: Figure 10

Provided in the embodiments of the present application are a decoding method, a coding method, a decoder and a coder. The decoding method comprises: determining a residual block of the current block in the current sequence on the basis of a code stream; determining a first prediction block of the current block on the basis of an intra template matching prediction (IntraTMP) mode; determining a second prediction block of the current block on the basis of a first prediction mode, wherein the first prediction mode is different from the IntraTMP mode; determining a target prediction block of the current block on the basis of the first prediction block and the second prediction block; and obtaining a reconstructed block of the current block on the basis of the residual block of the current block and the target prediction block.

The invention discloses a large language model safe decoding method based on a dynamic matching rate, and the method comprises the steps: carrying out the auxiliary decoding of a small language model for the user input content of a large language model, carrying out the speculative sampling, and combining the large language model and the sampling probability distribution of the small language model, constructing sampling distribution in different decoding states; under sampling distribution in different decoding states, dynamically adjusting a decoding mode according to a matching rate of lexical elements generated in collaborative decoding of the large language model and the small language model; and according to the change of the matching rate in the decoding process, parameters of a decoding scheme are adaptively adjusted, and speculative safe decoding of the large language model is realized. According to the method and the system, the security of the large language model is enhanced, so that the large language model has the characteristic of deep security alignment and keeps usefulness for benign problems, and decoding of generated contents is accelerated.

The invention provides an AT command parameter dynamic encoding and decoding method and system based on prefix identifications, and relates to the technical field of communication, the method comprises an encoding process and a decoding process, the encoding process comprises the steps of predefining a special character set and encoding algorithms, and configuring a unique corresponding prefix identification for each encoding algorithm; performing character traversal analysis on each parameter of the AT command to be sent, and judging whether any character in the predefined special character set is included or not; if not, directly outputting the parameter as a plaintext parameter; if so, encoding the parameter according to an encoding algorithm corresponding to the parameter, and splicing a corresponding prefix identifier in front of the encoded data to form an encoding parameter; and assembling all the plaintext parameters and the coding parameters according to the AT command grammar, generating a target command character string, and sending the target command character string. According to the invention, unnecessary processing overhead can be reduced, the command transmission length is shortened, and both transmission efficiency and reliability are considered.

The application discloses a kind of haptic signal encoding processing method, decoding processing method and related equipment, belong to haptic codec field, the haptic signal encoding processing method of the embodiment of the application includes: obtaining at least one of the key frame sequence and first signal corresponding to each haptic signal in multiple haptic signals, the key frame sequence is obtained based on second signal, first signal is obtained based on target residual signal and third signal, target residual signal is obtained based on second signal and key frame sequence, second signal and third signal are obtained based on to haptic signal, and the frequency of second signal is less than the frequency of third signal;At least one of the following is performed: first masking processing is carried out to key frame sequence based on first masking model, and the signal after first masking processing is encoded to obtain first encoding sequence;Second masking processing is carried out to first signal based on second masking model, and the signal after second masking processing is encoded to obtain second encoding sequence.

The invention discloses a trusted decoding method oriented to multi-modal large model sequence generation. The method comprises the following steps: acquiring an original image and text input; performing local focusing and global noise processing on the original image; respectively inputting the original image, the local visual input, the global noise visual input and the text input into a multi-modal large language model to obtain original output, local focusing output and global noise output distribution; calculating a calibrated output distribution based on a difference between the original output, the local focusing output, and the global noise output distribution; dynamically identifying the high-risk illusion lexical elements in combination with a modal dependency evaluation criterion, and calibrating the output probability distribution of the high-risk illusion lexical elements by using the calibrated output distribution; the trusted decoding method oriented to multi-modal large model sequence generation can effectively relieve the problems of semantic segmentation and object illusion caused by statistical deviation and language priori, and the output reliability of a multi-modal large language model in a sequence generation task is remarkably improved.

Devices, systems and methods for specifying the syntax and semantics of the decoding parameter set (DPS) are described. One example method of video processing includes determining, for a conversion between a video and a bitstream of the video, that each output layer set (OLS) in a coded video sequence (CVS) in the bitstream conforms to at least one profile-tier-level (PTL) syntax structure included in a data structure associated with decoding parameter semantics in the bitstream, and performing, based on the determining, the conversion, wherein the PTL syntax structure indicates a profile, a tier, and a level of the bitstream.

The invention discloses a speculation decoding method and device based on a large language model, equipment and a medium, and relates to the technical field of large models, and the method comprises the steps: determining the output probability distribution of a plurality of lexical element positions, and determining a confidence score based on the output probability distribution; determining a target control parameter according to the target state signal, performing aggregation calculation on the confidence coefficient vector to obtain an aggregation confidence coefficient, and determining a target draft length through the aggregation confidence coefficient and the target control parameter; determining a verification tolerance threshold based on the target control parameter and the confidence score, generating a draft sequence based on the target draft length by using a target deep learning model, and verifying each lexical element in the draft sequence based on a preset large language model and the verification tolerance threshold; and adding the successfully verified target lexical units to the end of the currently generated sequence to obtain a target sequence, determining the target sequence as the currently generated sequence, and skipping again to perform the next round of speculative decoding. According to the invention, the efficiency of speculative decoding can be improved.

According to a disclosure of the present document, when the type of inter-prediction of a current block is indicated as biprediction, weight index information for a candidate within a merge candidate list or a sub-block merge candidate list may be derived, and coding efficiency may be increased.