37 results about "Local sequence" patented technology

The hybrid addressing method and the hierarchical multi-core cascading device provided by the invention comprise the following steps: if a core in a basic module initiates a memory access request, analyzing the memory access request to obtain a row offset high order of an access address, if the row offset high order is located in a sequence region, rearranging the access address to obtain a rearranged address, and if the row offset high order is located in the sequence region, rearranging the rearranged address to obtain the hierarchical multi-core cascading device. The rearranged address is restrained in the memory bank of the basic module, the sequence area is a preset row in the memory bank of the core, and if a row offset high bit is located in an interleaving area, the access address is divided to obtain a divided address; wherein the divided addresses are stored in memory banks of different basic modules, and the interleaving area is an area except a sequence area. A dual-mode design of a local sequence region and a global interleaving region is adopted, and an exclusive sequence region is divided in global interleaving mapping by recoding an address high bit, so that balance between a global shared memory view and local low-latency access is ensured.

The invention provides a regional soil fertility space-time evolution prediction method and system, and relates to the field of data processing prediction.The method comprises the steps that agricultural management events such as fertilization and irrigation are captured in real time through an edge computing node cluster, and an asymmetric time window is constructed based on a soil permeation rate model; extracting meteorological and satellite data in the window, querying the coupling rule table by using a triple index, and generating a coupling factor data set with a semantic mark; calculating a sliding time variance of a coupling factor in a grid unit, marking a high-entropy region and starting real-time stream processing when the sliding time variance exceeds a threshold value, and generating a soil state Hash fingerprint and performing dormancy collection when the sliding time variance is lower than the threshold value; constructing a regional event path directed graph, selecting a similar neighborhood event chain as a prediction framework, and registering an empty window region; the neighborhood topology is scanned in a buffer zone of a window area, after a compliance event sequence is captured, a window is removed, similar neighborhood historical data is migrated and injected into a local sequence, and parameters are finely adjusted through incremental learning to reconstruct an exclusive prediction model.

The invention discloses a burst frequency hopping communication system high-precision arrival time estimation method, device and medium, and relates to the field of burst communication system time synchronization, and the method comprises the following steps: a receiving end carries out multi-channel down-conversion and double symbol sampling on a frequency hopping signal, and carries out local sequence correlation processing; aligning related results according to the frequency hopping pattern and the delay difference, performing non-coherent accumulation, and recording frame header stamping time at a peak moment; performing linear fitting on a correlation peak result to calculate a timing error estimation value; querying and obtaining corresponding compensation time by using an offline established time compensation table to correct the timing error estimated value, and obtaining a timing error precise estimated value; and finally, compensating the precise estimation value to the frame header stamping time, and outputting high-precision arrival time. According to the invention, high-precision time synchronization is realized at a low sampling rate, and hardware overhead is effectively reduced.

The application provides an efficient deep learning method and system based on a squeeze-excitation-network and a ConNet network, which comprises the following steps: obtaining a protein global sequence and a protein local sequence as a sample set, and setting model parameters of a DeepNet deep framework; dividing the sample set into a training set and a verification set, setting a model architecture of the DeepNet deep framework, extracting effective feature information, combining negative samples and positive samples in the protein global sequence and the protein local sequence, and sending the samples into the DeepNet deep framework for training and hyperparameter tuning; adaptively coding the protein global sequence and the protein local sequence; designing a local sequence processing branch and a global sequence processing branch, extracting network structure features and key information between long and short sequences by using different scale convolution networks, and calculating final prediction probability according to the key information. The application solves the technical problems that sufficient feature information cannot be extracted and global information is not fully considered and between global information and local information.

The embodiment of the invention provides a frame synchronization method and device based on a WI FI system, and the method comprises the steps: carrying out the delay self-correlation of a short training sequence of a main channel and a secondary channel, carrying out the bandwidth detection of a current WI FI frame according to the delay self-correlation result of the main channel and the secondary channel, and when the bandwidth detection result of the current WI FI frame is greater than a specified bandwidth, carrying out the bandwidth synchronization of the current WI FI frame. And coarse synchronization is carried out according to a delay self-correlation result of the main channel and the secondary channel to obtain long training sequences of the main channel and the secondary channel, and a correlation peak is searched for a cross-correlation result of the long training sequences of the main channel and the secondary channel and a long training sequence of a local sequence to carry out fine synchronization so as to determine a symbol boundary of the current WIFI frame. According to the method and the device, the problems that only a main 20M channel is used, other channels are not used, and timing errors are deteriorated due to the length of the PPDU are solved, and the effects of improving the frame synchronization precision of the WI FI system and reducing the error code probability caused by the overlong length of the PPDU are achieved.

The invention discloses an interference suppression method, system and device based on frequency point quality cognition and a medium, and relates to the field of frequency hopping communication. A transmitting end adopts a frame structure of'synchronous head sequence + information sequence + synchronous tail sequence ', and forms a frequency hopping pulse signal for radiation after processes of coding, framing and frequency hopping modulation; a receiving end processes a received frequency hopping pulse signal after signal detection and timing synchronization, calculates a noise power value of each frequency hopping pulse after frequency hopping pulse synchronization head and tail sequences are correlated with a local sequence, calculates a noise weight value of each pulse, multiplies a weight factor with a pulse signal after channel equalization, and obtains a frequency hopping pulse signal. By reducing the signal observed quantity weight of the interfered frequency point, the influence of the confidence coefficient reduction caused by the interference signal on the channel decoding of the whole communication system is suppressed, so that the reliable transmission under the condition of low signal-to-noise ratio and strong interference is realized.

This invention discloses a frequency offset self-compensation method for UWB signal detection, belonging to the field of ultra-wideband communication technology. The method includes the following steps: First, cross-correlation is performed between the ADC-sampled signal and the local sequence; second, based on the peak detection position, the phase difference is calculated using the calculated cross-correlation result and the cross-correlation result of the previous symbol; then, phase compensation is performed on the currently calculated cross-correlation result; next, the phase-compensated cross-correlation result is added at the same position to the cross-correlation result of the previous symbol; then, peak period detection is performed using the added cross-correlation result, updating the peak detection position and peak period detection count; the phase compensation value is updated based on the peak period detection count and the calculated phase difference; finally, it is determined whether the peak period detection count has reached a set threshold. If it has, the signal detection result is output; otherwise, steps 1-7 are repeated.

In at least one embodiment, processing can include receiving a command at a first node in a system, wherein the first node manages first user data (UD) log resources and a second node of the system manages second UD log resources. The first and second nodes can generate sequence numbers from corresponding node-local sequences. Each command of a UD log is associated with a generic serial number (GENSN). Responsive to determining the command is a write I / O directed to logical addresses owned by the first node, the first node can perform processing to record the write I / O in the UD log without any internode communication with the second node. The recorded write I / O can be associated with a GENSN including a non-zero value that is a sequence number of the first node's local sequence and a zero value corresponding to the second node.

The application discloses a high-precision time of arrival estimation method, equipment and medium for a burst frequency hopping communication system, relates to the field of time synchronization of a burst communication system, and comprises the following steps: a receiving end performs multi-channel down-conversion and 2 times symbol sampling on a frequency hopping signal, and performs correlation processing on a local sequence; non-coherent accumulation is performed on the correlation results after the correlation results are aligned according to a frequency hopping pattern and a delay difference, and a frame header stamping time of a peak time is recorded; a timing error estimation value is calculated by performing linear fitting on the correlation peak results; a corresponding compensation time is obtained by querying a time compensation table established offline, so as to correct the timing error estimation value, and a precise timing error estimation value is obtained; and finally, the precise estimation value is compensated to the frame header stamping time, and a high-precision time of arrival is output. The application realizes high-precision time synchronization under a low sampling rate, and effectively reduces hardware cost.

The application provides a motor ripple counting method, device, equipment and storage medium. The method comprises the following steps: reading sequence data of M ripple periods from a starting point of a motor ripple sampling sequence obtained in advance as a processing sequence according to an initial single period value and a sampling period value of a ripple analog-to-digital converter, performing correlation transformation according to a corresponding local sequence, determining a target algorithm and a measurement point set according to a predicted period of the processing sequence predicted in advance, calculating an upper peak position corresponding to the correlation transformation sequence based on the measurement point set and the target algorithm, accumulating and counting the number of ripples of the processing sequence, and repeating the above steps in a time sequence to start at a new starting point until the motor ripple sampling sequence is processed. Through the above method, the motor ripple sampling sequence is counted based on the measurement point set, the calculation amount is reduced, the accuracy is improved, and the influence of serious distortion and noise is avoided.

The present application relates to the technical field of communication, and especially relates to a correlation processing system, method and device for PSS detection and a medium. The system comprises: a parity separation module, configured to separate received air interface data into odd road sequences and even road sequences and output; two-way matched filters, one of which is configured to multiply the odd road sequences as input data with odd road data in a PSS local sequence to obtain odd road multiplication results, and the other of which is configured to multiply the even road sequences as input data with even road data in the PSS local sequence to obtain even road multiplication results; and a post-processing module, configured to first perform modulo operation on the odd road multiplication results and the even road multiplication results respectively, and then perform addition operation to generate correlation results. The scheme of the present application can effectively resist the detection performance decline caused by frequency offset, without the need for multiple attempts in the possible frequency offset range, greatly shortening the time consumed by PSS detection.

The embodiment of the application provides a kind of signal processing method and device, it is related to terminal, communication and other technical field, the method comprises: obtaining the signal sequence to be handled, and the local sequence corresponding to signal sequence, the total number of signal in local sequence is less than the total number of signal in signal sequence;According to the index of signal in signal sequence, signal sequence is divided into at least one signal group and the remaining signal except signal group in signal sequence, each signal group includes two signals, and the sum of the index of two signals is equal to the total number of signal in signal sequence;For each signal group, determine the pre-processing result corresponding to signal group, and the pre-processing result is used to obtain the correlation between signal sequence and local sequence;According to the pre-processing result corresponding to each signal group, the remaining signal and the local sequence, determine the correlation, for reducing the power consumption of terminal equipment.

This invention relates to a method for extracting entity nesting from equipment maintenance and support text based on multi-technology fusion, belonging to the field of big data. The method includes: acquiring equipment maintenance and support text and performing word segmentation to obtain multiple sequence fragments; setting scanning windows of different lengths and scanning and filtering the sequence fragments according to configured filtering rules to obtain candidate sequences; inputting the candidate sequences into a BERT pre-trained model to convert them into feature vector sequences; using a BiLSTM neural network to extract features from the feature vector sequences and obtain sequence context information; using a TextCNN neural network to process the feature vector sequences and obtain local sequence features; concatenating the features to obtain fused features; mapping the fused features to label scores through a fully connected layer; calculating the label probability of a sequence fragment being an entity based on the label scores to predict the entity label corresponding to the sequence fragment. This invention's method can improve the efficiency and quality of equipment maintenance and support work by integrating multiple methods and strategies.

The application belongs to the technical field of deep reinforcement learning, and discloses a multi-agent multi-task cooperative reinforcement learning method based on a space-time fusion architecture, which comprises the following steps: step 1, initializing a task sampling probability, forming an entity embedding vector sequence and a task embedding vector; step 2, inputting the entity embedding vector sequence and the task embedding vector into a noise-resistant feature extraction layer to obtain deep time sequence features; step 3, generating a dynamic weight matrix in real time to obtain local Q values output by an agent; step 4, a Transformer hybrid network receiving a global state vector of an environment, a task embedding vector and a local Q sequence to give a global action value; step 5, calculating a total loss; and step 6, based on the total loss, training an optimization unit to update all network parameters, and simultaneously, judging whether a preset evaluation round is reached. The application has stronger anti-interference ability and more stable control performance, and realizes adaptive control of multiple heterogeneous tasks.

This application provides a graphical user interface (GUI) operation method, apparatus, device, and medium. The method includes: performing intent recognition and parsing on natural language commands to obtain a structured intent sequence; performing parsing and semantic mapping operations on the candidate GUI operation sequence to obtain a structured GUI operation sequence; constructing a matching score matrix between the structured GUI operation sequence and the structured intent sequence based on a local sequence alignment algorithm; determining the element with the largest value in the matching score matrix as the matching degree; and executing the candidate GUI operation sequence if the matching degree is greater than a threshold. This solves the semantic difference between the GUI operation sequence and the natural language commands, and robustly handles the mismatch in granularity and length between the two sequences, thereby improving the accuracy of the calculated matching degree and thus increasing the consistency between the GUI operation result and the user's expectations, enhancing the user experience.

The application belongs to the field of bioinformatics and computational biology, and particularly relates to a mutation detection method and system based on an attention mechanism and dynamic routing. The method comprises: obtaining a sequencing sequence alignment result, and extracting candidate mutation sites with high confidence through threshold setting preliminary screening; a local sequence window is intercepted with the candidate site as the center, a multi-dimensional feature tensor is constructed by fusing physical space position, positive and negative chain alignment classification and sequencing quality attributes; the multi-dimensional feature tensor is input into a backbone network, background noise is suppressed by using a Gaussian guided space attention mechanism, and long-distance multi-scale mutation features are extracted by using a shift window mechanism of a Swin Transformer and a dynamic routing strategy of a mixed expert module; finally, the existence of mutations, zygote states and allele sequences are determined in sequence by using a multi-task dynamic decoding network, and network parameter optimization and result output are completed by using a cost-sensitive focal loss. The application avoids the statistical feature loss problem caused by traditional image mapping, alleviates the limitation of limited local receptive field, realizes adaptive adjustment of the calculation path according to the sequence complexity by introducing a dynamic routing mechanism, overcomes the configuration imbalance of static models in the allocation of computing power and the capacity of local parameters, and enhances the detection accuracy and stability of the model under complex variation and low sequencing depth conditions.

The application provides a sequence processing method and device, electronic equipment and storage medium, relates to the technical field of data processing, and is applied to electronic equipment. The method comprises the following steps: receiving a local sequence acquisition request, and applying for a current local sequence to a database according to the local sequence acquisition request; in the case that the sequence value used by the current local sequence reaches a first threshold value, determining a new local cache window value of the local sequence applied next time according to a first preset rule; determining new configuration parameters of the local sequence applied next time according to a second preset rule; and acquiring a new local sequence from the database according to the new local cache window value and the new configuration parameters. Therefore, the local cache window value and the configuration parameters of the new local sequence applied from the database can be dynamically adjusted according to the actual use of the local sequence, the access efficiency of the local sequence is improved, the performance of the application system accessing the sequence is effectively improved, and the user experience is improved.

The invention discloses an accurate sequence analysis method and system based on nanopore length and read length sequencing data. The method comprises the following steps: comparing nanopore sequencing data with a reference genome through a minimap2 algorithm, and screening out high-quality long-read-length sequences in a target area and specific upstream and downstream ranges; extracting a target area local sequence of each read length, calculating an editing distance matrix, performing Box-Cox transformation, performing clustering analysis by adopting a Gaussian mixture model, and determining an optimal clustering number through a BIC criterion; performing multi-sequence alignment and polishing on each type of sequences to generate a high-precision consensus sequence; and finally, recognizing homologous conserved sequence fragments through re-comparison and global comparison, and outputting candidate sequences for targeting PCR (Polymerase Chain Reaction) primer or CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) sgRNA design. According to the method, the problem of high error rate of nanopore length and read length data can be effectively solved, the accuracy and reliability of sequence analysis are improved, and reliable technical support is provided for precise gene editing and molecular diagnosis.

The embodiment of the invention provides a data transmission method, a data distribution system, equipment, a storage medium and a program product. In the data transmission method, when a sending end sends a log data packet, a log serial number of the log data packet can be sent together. After a receiving end receives a log data packet, whether the log data packet is a continuous data packet or not can be judged based on the log serial number of the log data packet and the log serial number of the received previous log data packet. Wherein the log sequence number of each log data packet is composed of a stream sequence identifier of the stream transmission connection to which the log data packet belongs and a local sequence identifier of the log data packet in the stream transmission connection. The flow sequence identification can be used for accurately sequencing the flow transmission connection so as to cope with the situation that the flow transmission connection is restarted; according to the technical scheme, the stream sequence identifier and the local sequence identifier can be used for accurately sequencing the log data packets in the stream transmission connection, so that whether the received data packets are continuous or not can be accurately judged even if the stream transmission connection is restarted, and the risks of packet loss and disorder of the data packets are reduced.

A system includes a first device to select and transmit a first code from a plurality of codes by a transmitter to a remote device controlling access. The remote device implements a switching device based on the received first code and generates a local sequence of data. The first device generates and transmits to the remote device a first sequence of signals based on the first code; the remote device processes the first sequence of signals and activates the mechanism based on the first sequence of signals and the local sequence of data. An n-state switching function with n=2{circumflex over ( )}k commutative involution is used in the switching device, the n-state commutative involution is not based on a XORing of 2 words of 2 bits with n and k being integers greater than 2. The first device may be a smartphone, a fob, an access card, or any other computing device.

The invention discloses a time-frequency two-dimensional correlation capturing method, device and equipment based on FFT (Fast Fourier Transform) and a medium, and belongs to the technical field of capturing and tracking of receivers. According to the method, a time-frequency two-dimensional correlation map of a receiving sequence and a local sequence is quickly constructed, and time-domain and frequency-domain two-dimensional simultaneous capture can be realized under the conditions of large frequency offset and high dynamic state by searching and judging a correlation peak value of the time-frequency map and predicting the characteristics of the time-frequency map of multiple adjacent capture events, so that the capture probability is improved.

The invention discloses a cell search method, device and equipment, a medium and a product. The method comprises the following steps: acquiring received data; performing primary synchronization signal detection on the received data to determine a first initial detection result; grouping the first initial detection results to obtain a first final detection result; performing auxiliary synchronization signal detection and combination on the first final detection result to obtain a second final detection result; and determining a cell search result according to the first final detection result and the second final detection result. Candidate sets obtained in a PSS detection process are grouped, so that SSS detection is carried out based on grouping information, and related peak values related to an SSS local sequence in a group are combined and then are finally sorted, so that the influence of a false peak on the cell search accuracy under a low SNR (Signal to Noise Ratio) is reduced, the cell search success rate is improved, and the influence of noise on received data is reduced; and the false detection rate of cell search is reduced.

The invention discloses a ribosome stagnation relative strength prediction method of a MambaPlus and Transform parallel architecture, and belongs to the crossing field of bioinformatics and artificial intelligence. According to the model, firstly, a DNA sequence is converted into multi-dimensional feature representation through K-mer and One-hot composite coding, a local sequence pattern is extracted by adopting a parallel multi-scale convolutional neural network, and long-range dependency and global context information are modeled respectively in combination with a MambaPlus encoder and a Transform encoder; multi-modal features are integrated through an adaptive weighted fusion strategy, dynamic aggregation is carried out on sequences in combination with attention pooling, and finally prediction of ribosome stagnation relative strength is realized in combination with biophysical features. The error of the depth model for predicting the relative strength of ribosome stagnation is smaller than 0.27, and compared with a traditional model, the depth model has higher accuracy.

The invention belongs to the technical field of deep reinforcement learning, and discloses a multi-agent multi-task collaborative reinforcement learning method based on a space-time fusion architecture, and the method comprises the steps: 1, initializing a task sampling probability, and forming an entity embedding vector sequence and a task embedding vector; step 2, inputting the entity embedding vector sequence and the task embedding vector into an anti-noise feature extraction layer to obtain deep time sequence features; 3, generating a dynamic weight matrix in real time, and obtaining a local Q value output by the intelligent agent; 4, the Transform hybrid network receives a global state vector, a task embedding vector and a local Q sequence of the environment, and gives a global action value; 5, calculating the total loss, and 6, based on the total loss, training an optimization unit to update whole network parameters, and meanwhile, judging whether a preset evaluation round is reached or not. The method has higher anti-interference capability and more stable control performance, and realizes adaptive control of multiple heterogeneous tasks.

This invention belongs to the field of broadband communication technology and discloses a UWB signal detection method and system based on equidistant array multi-antenna reception. All antennas are arranged in an equidistant array; the signal received by each antenna is cross-correlated with the local sequence; the cross-correlation results of adjacent antennas are merged using conjugate multiplication to obtain one data stream; the calculation results of the merged data from multiple adjacent antennas are accumulated using the same index, and finally merged into one total data stream; the final total data stream is weighted and accumulated according to the sign period, and the absolute value of the accumulated result is processed; the absolute value processing result is used for peak period detection and peak comparison, and the signal detection result is output. This invention eliminates the influence of carrier frequency offset; the weighted accumulation processing according to the sign period further improves the gain, greatly improving the signal detection sensitivity and enhancing the overall system performance.

The invention provides an authentication processing method and device for avoiding resynchronization and authentication equipment. Relates to the technical field of communication, in the method, an AMF responds to a registration request sent by UE, under the condition that the UE comes from 4G, the AMF obtains a tetrad index field from a mobile management entity MME of 4G, and the tetrad index field is used for indicating the number of used authentication vectors in the last batch of issued authentication vectors; the AMF sends a request message carrying the tetrad index field to an AUSF to obtain an expected serial number determined by the AUSF through a 5G unified data management UDM and a new authentication vector corresponding to the expected serial number; and the AMF sends an authentication request to the UE, the authentication request carrying the expected serial number and the corresponding new authentication vector, so that the UE determines an authentication result according to the expected serial number and a local serial number. And the risk of authentication failure caused by dislocation of the serial number is greatly reduced, and resynchronization is reduced.

The invention belongs to the technical field of point cloud data processing, and discloses a contour point structured processing method for an airplane concave polygon thin-wall part. All contour points are divided into arc points and straight line points based on local linear fitting residual errors, and the arc points and the straight line points are clustered; sorting the interiors of the arc clusters according to the sizes of polar angles, sorting the linear clusters according to coordinate projection, and completing local ordering in the clusters; on the basis of end point distance nearest search, the clusters are arranged in sequence, and ordering among the clusters is achieved; and performing spline curve fitting on the contour points subjected to global sorting, fitting discrete three-dimensional contour points into a smooth contour curve, and realizing structured processing on the contour points of the airplane concave polygon thin-wall part. According to the method, sorting modes based on angles and distances are combined through a mode of firstly classifying and then locally-globally sorting, so that structuring of contour points of the airplane concave polygon thin-wall part with a complex structure is realized, and the problem of local order disorder caused by a single sorting mode is avoided.

The application relates to the technical field of path planning, in particular to a path planning method, device, equipment, medium and program product, wherein the method comprises the following steps: identifying actual requirements of user path planning; determining a starting point position, a final destination and a local sequence constraint condition according to the actual requirements, generating a plurality of original paths based on the starting point position and the final destination, and performing node sequence coding on the original paths to generate a plurality of node sequences, wherein the local sequence constraint condition is a local sequence constraint for a plurality of destination nodes in the original paths; executing a second preset algorithm on any preset length node sequence in a plurality of original paths of the same species based on a first preset algorithm to generate a corresponding new path meeting the local sequence constraint condition; and generating an optimal path by performing multiple iterations on the plurality of new paths by using a third preset algorithm. Thus, the problems that the path generated by the global optimal solution in the related art does not meet the sequence access requirements of the user and the user experience is poor are solved.

The invention discloses a local sequence alignment algorithm and device for detecting the number of continuous similar rows of a file, and belongs to the technical field of code clone detection. The method comprises the following steps: carrying out preprocessing of blank removal, blank line removal and annotation removal on two files to obtain a line sequence; an improved Smith-Waterman algorithm is utilized, a'row 'is taken as a unit, difflib.Sequence Matcher > = 0.8 is taken as a similar threshold to construct a score matrix, and all continuous matching fragments with the length > = minlines are extracted through backtracking; and outputting starting and stopping line numbers and line-by-line contrast contents of each segment in a descending order according to the similar line number. According to the method, a language parser and time complexity O (n.m) are not needed, continuous similar regions of Type-1 to Type-3 clone can be positioned at one time, the result is visual, parameters can be configured, and the method is suitable for repeated code cleaning, plagiarism detection and reuse rate measurement of million row-level codes.

This invention pertains to wireless communication technology, specifically a pre-compensated joint detection and estimation method for satellite IoT, comprising three parts: frame structure design, terminal preprocessing, and preamble detection and frequency offset estimation. In scenarios with multiple random satellite terminal access, this invention employs a preamble sequence composed of two root sequences, which, compared to the traditional preamble sequence frame structure with a single root sequence, increases the number of local sequence sets. The proposed joint detection and estimation algorithm combines the characteristics of the preamble sequence and analyzes how, under different positioning error conditions, it improves the detection success rate of simultaneously accessing terminals compared to traditional detection methods.