76 results about "Time domain correlation" patented technology

The invention relates to an AI-based automatic adaptation method for a work approval process, and the method comprises the steps: collecting multi-source approval data, and carrying out the preprocessing of the multi-source approval data, and forming standardized approval data; analyzing the system rule text by using the pre-trained AI large model, and extracting a structured approval rule comprising a trigger condition, an approval role and a process node sequence; matching a basic examination and approval template according to the form field and the user permission information, and dynamically generating an adaptive process comprising multiple stages of examination and approval nodes, aging parameters and an additional examination and approval link; and through resource scheduling optimization and time domain correlation analysis, establishing an optimized mapping relation based on flow execution characteristics such as approval timeliness deviation and node skipping frequency, and outputting a visual flow chart and execution parameters. A business logic writing mode is replaced by automatic analysis of an AI large model on an unstructured rule; the dynamic template matching and continuous iterative optimization mechanism can quickly respond to business changes, and resource scheduling optimization and automatic process generation shorten the implementation period and reduce the operation and maintenance cost.

The invention relates to the technical field of industrial laser precision measurement, in particular to a laser centering device for a coupler and a using method of the laser centering device for the coupler. Light spot displacement signals and environment vibration signals are synchronously collected through a laser transmitter and an optical sensor array, and a frequency domain feature decoupling module is adopted to separate a shafting displacement component and an interference component; the time domain correlation verification module is used for calculating signal time sequence correlation and generating a deviation vector, and finally the adaptive compensation decision module is used for analyzing the deviation vector and outputting an adjustment instruction. According to the invention, effective separation of real misalignment and transient noise in a dynamic environment is realized, the technical problem of measurement misalignment of an existing laser centering device in a complex industrial environment is solved, and the coupling installation precision and the equipment operation stability are improved.

The invention discloses a dynamic three-dimensional scene representation method based on Gaussian splashing, and belongs to the field of machine vision. A first time feature constructed through a first neural network based on the time index is fused with the Gaussian feature of the original Gaussian point cloud, and then decoding is performed to obtain various parameters of the original Gaussian point cloud; and fusing a second time feature obtained through second neural network coding based on the time index with the feature obtained by the micro renderer, so that time domain information is introduced in the image reconstruction process to assist in constructing the incidence relation of adjacent video frames, and the time domain expression capability of the model is further enhanced. According to the method, the convolutional neural network is combined with Gaussian splash, the modeling capability of a model for a dynamic scene can be effectively enhanced by fusing time domain features, and efficient expression of a dynamic three-dimensional scene is realized; time domain redundancy is eliminated by modeling a time domain incidence relation, and efficient expression of a dynamic scene is achieved.

The invention discloses a transformer monitoring method and system based on a multi-dimensional signal, and relates to the technical field of transformer monitoring, and the method comprises the steps: obtaining the multi-dimensional signal and working condition parameters of a transformer, carrying out the time domain feature extraction of the multi-dimensional signal, obtaining a corresponding time domain correlation feature, carrying out the frequency domain feature extraction of the multi-dimensional signal, obtaining a corresponding frequency domain correlation feature, and carrying out the time domain feature extraction of the multi-dimensional signal; fault analysis is carried out according to the working condition parameters and the frequency domain correlation characteristics, and a corresponding initial fault detection result and an electromagnetic coupling residual value are obtained; and if so, carrying out fuzzy evaluation on the time domain correlation feature, the frequency domain correlation feature, the electromagnetic coupling residual value and the multi-dimensional signal based on a pre-trained fault detection model to obtain a corresponding fault monitoring result. The technical problems that a traditional transformer monitoring method mainly depends on electrical signal analysis, but key parameters such as oil temperature are not included in a monitoring system, so that potential fault hidden dangers cannot be found in time, and the operation reliability of the transformer is reduced are solved.

The invention discloses a wind power blade structure health monitoring method based on multi-field decoupling optical fiber sensing, particularly relates to the technical field of wind power equipment state monitoring, and is used for solving the problem of health state misdiagnosis caused by coherent interference of environmental noise and damage signals. The method comprises the following steps: collecting vibration, strain and temperature signals and generating a background noise vector; calculating a frequency domain coherence function of the vibration signal and the noise vector to identify an interference danger frequency band; analyzing the polarization angle distribution of the vibration signal in the frequency band, and inverting the physical path topology of the noise transmitted into the blade; when the path passes through a predefined weak area, improving a damage weight coefficient of a strain signal of a corresponding frequency band and carrying out Hilbert phase shift reconstruction to generate an anti-interference strain feature vector; calculating the energy dissipation rate of the vector in a dangerous frequency band, and judging an energy leakage event caused by damage by combining a viscoelastic constitutive threshold value of the composite material; the damage type and the spatial position are judged according to the time domain correlation between the energy leakage event and the temperature signal, and the hidden damage detection reliability is improved.

The invention discloses a distributed photovoltaic power prediction method and device based on dynamic spatial correlation, and relates to the field of distributed photovoltaic technology, and the method can reflect the real influence relation between photovoltaic power stations at different moments in real time through constructing dynamic graph structure data which can reflect the spatial relation between the photovoltaic power stations more comprehensively and accurately. And the prediction result of the distributed photovoltaic power is improved. The method comprises the following steps: acquiring an influence factor feature set of distributed photovoltaic power prediction; by taking the distributed photovoltaic power station as a node, constructing dynamic graph structure data of the photovoltaic power station according to the influence factor feature set and the spatial weight matrix fused with the meteorological condition information; performing spatial correlation extraction on the dynamic graph structure data by using a pre-trained first network to obtain spatial correlation characteristics of the distributed photovoltaic power station; and performing time domain correlation extraction on the spatial correlation characteristics by using a pre-trained second network to obtain a point prediction result of the distributed photovoltaic power.

The invention provides a hydraulic turbine set valve fault diagnosis method, system, equipment and product, and is applied to the field of hydroelectric equipment fault diagnosis. On one side of the edge end, an initial voiceprint signal, an initial vibration signal and temperature data of a hydraulic turbine set valve are collected; taking the initial voiceprint signal as a reference signal, and performing noise reduction processing on the initial vibration signal based on the time domain correlation between the fluid noise in the initial voiceprint signal and the first noise in the initial vibration signal; by taking the vibration noise reduction signal as a reference signal, performing noise reduction processing on the initial voiceprint signal based on the frequency domain correlation between the mechanical resonance noise in the vibration noise reduction signal and the second noise in the initial voiceprint signal; and based on the vibration noise reduction signal, the voiceprint noise reduction signal and the temperature data, performing fault diagnosis on the hydraulic turbine set valve to obtain a fault diagnosis result. Therefore, fault diagnosis is carried out through cooperative noise reduction of the voiceprint signal and the vibration signal in combination with multi-dimensional data, and the fault diagnosis accuracy of the hydraulic turbine set valve is improved.

The embodiment of the invention discloses a power grid line state monitoring method and device based on vibration acoustics. The method comprises the following steps: acquiring a power grid power transmission line vibration signal and a sound wave signal; according to the topological structure of the power transmission line, the spatial distribution of adjacent lines and the measuring point positions of different sensors in the same line, constructing a signal propagation model, and calculating a multi-dimensional correlation index between the vibration signal and the sound wave signal, the correlation index including a time domain correlation coefficient, a frequency domain power spectral density and a phase difference feature; simulating signal propagation characteristics in a normal operation mode by using the signal propagation model, generating a reference correlation index, and identifying whether the power transmission line has an abnormal state; and carrying out accurate positioning on the abnormal state by adopting a spatial positioning algorithm, and carrying out multi-level evaluation according to the abnormal confidence coefficient and the influence range to generate a line abnormal report. According to the invention, real-time monitoring and accurate positioning of the abnormal state of the power transmission line are realized.

The present disclosure relates to the technical field of wireless communications. In particular, an information transmission method and apparatus, and an electronic device and a computer program product are provided. The method comprises: on the basis of a first system message, determining at least one first occasion, or on the basis of the first system message and a second system message, determining at least one first occasion, wherein the first system message is related to a beam; or on the basis of at least one of a third system message, a time-domain-related parameter of the third system message, and a time-domain-related parameter of a synchronization signal block (SSB), determining at least one first occasion; and performing information transmission at the at least one first occasion. In the present disclosure, a terminal device determines an information transmission occasion, and thus energy consumption waste caused by transmission failures and repeated transmissions of the terminal device is reduced.

The invention discloses a CAN bus abnormal flow detection method based on multi-scale and frequency domain characteristics, and relates to the technical field of Internet of Vehicles security, and the method comprises the following steps: carrying out the preprocessing of the original message data of a CAN bus, dividing a continuous message sequence according to a preset time window, and constructing a time sequence sample; inputting the time sequence sample into a feature extraction and fusion model, and sequentially executing multi-scale time sequence feature extraction, time sequence correlation modeling and frequency domain feature enhancement processing to obtain feature representation fusing time domain correlation information and frequency domain structure information; and constructing a classification model based on the feature representation, and carrying out anomaly detection and classification on the CAN bus flow. According to the CAN bus abnormal flow detection method based on the multi-scale and frequency domain characteristics, effective fusion of time domain correlation enhancement and frequency domain noise suppression is realized, the detection robustness and accuracy in a complex vehicle-mounted noise environment are improved, and the false alarm rate in the complex vehicle-mounted noise environment is reduced.

A channel estimator circuit receives in one slot a multiplexed representation of one or more time- domain code division multiplexed, TD-CDM, spread received signals. An initial estimator circuit processes a pre-estimation signal that is formed therefrom, uses a base pilot signal as a reference signal, and outputs an initial estimate signal. A frequency-domain processing circuit receives and processes a first set of one or more TD-CDM spread channel estimate signals that is representative of the initial estimate signal, and outputs a second set of signals. An interpolation buffer buffers the second set of signals. A TD-CDM de-spreading circuit de-spreads the buffered second set of signals and outputs TD- CDM de-spread channel estimate signals. In this manner, the frequency-domain-related signal processing and the time-domain-related signal processing are separated, and a significant reduction in the amount of hardware, energy and time resources required may be achieved, improving latency and reducing cost.

The application provides a fracture patient muscle mass detection method based on electromyographic signal analysis, and relates to the technical field of medical treatment. The method comprises the following steps: acquiring electromyographic signals of a target muscle and its adjacent muscles of a patient; when the correlation coefficients of the target muscle and the adjacent muscle signals and their envelope lines meet preset conditions, judging whether the target muscle is interfered by the adjacent muscles based on the signal difference degree; when the adjacent muscles interfere, extracting independent frequency component sequences of the target muscle and the adjacent muscle signals, removing interference components based on the time domain correlation coefficients and the frequency overlap degree of each independent frequency component group, and obtaining a real target muscle signal; determining the muscle recovery state of the patient based on the amplitude variation trend of the real target muscle signal sequence of the patient in a target period, and the amplitude difference between the contraction state sequence segment and the relaxation state sequence segment in the signal envelope line of the target sub-sequence of the sequence, and formulating a rehabilitation training scheme accordingly. The application can more accurately determine the muscle recovery state of the patient.

Provided in the present disclosure are a channel estimation method, a device, and a storage medium. The method is executed by a first device, on which a first model is deployed. The method comprises: when it is determined that a first time unit meets a preset condition, on the basis of first information corresponding to the first time unit, using a first model to determine a channel estimation result corresponding to a second time unit; or when it is determined that the first time unit does not meet the preset condition, receiving second information sent by a second device, wherein the second information is used for indicating whether a first device can use the first model to determine the channel estimation result corresponding to the second time unit. Therefore, channel estimation can be performed on a second time unit on the basis of a first model and first information corresponding to a first time unit, and channel estimation is performed by using the time-domain correlation of a channel, such that the accuracy and efficiency of channel estimation can be improved.

The invention belongs to the technical field of human body electroencephalogram signal processing and brain regulation and control, and provides a noradrenaline oscillation time-frequency-phase three-dimensional coupling sleep coordinated regulation and control device which comprises the following steps: calculating a three-dimensional coupling coefficient by combining a time domain correlation coefficient, a frequency domain correlation coefficient and an instantaneous phase difference between multi-modal physiological signals; determining the coupling state of the signal based on the three-dimensional coupling coefficient and a preset threshold value; predicting to obtain an optimal regulation factor and a modal weight based on a coupling coefficient matrix constructed based on a time domain correlation coefficient and a frequency domain correlation coefficient and a constructed three-dimensional coupling double-layer optimization architecture in combination with the multi-modal physiological signal; calculating the optimized stimulation intensity in combination with the modal weight, the optimal regulation factor and the multi-modal signal characteristic parameters; and adaptively selecting a stimulation mode and outputting a stimulation signal according to the coupling state of the current multi-mode signal and the optimized stimulation intensity. Accurate matching of stimulation parameters and nerve-blood vessel-cerebrospinal fluid system collaborative rhythm is realized.

The invention provides an SSB time-frequency synchronization method and device, and relates to the technical field of mobile communication. The method comprises the following steps: receiving a synchronization signal block SSB signal sent by a base station; processing the SSB signal to obtain a target time domain sequence generated after processing, and performing sliding correlation on the target time domain sequence to obtain a time domain correlation value sequence; acquiring a peak value of the time domain correlation value sequence, and performing time synchronization of the SSB signal based on time offset corresponding to the peak value; after the time synchronization of the SSB signal is completed, obtaining a cyclic prefix (CP) removal sequence corresponding to the time domain sequence of the SSB signal, and obtaining a pre-frequency offset PSS time domain sequence generated after a primary synchronization signal PSS time domain sequence is subjected to multiple times of frequency offset adjustment; performing correlation calculation based on the CP-removed sequence and the pre-frequency offset PSS time domain sequence to determine a target estimated frequency offset; and completing frequency synchronization of the SSB signal based on the target estimation frequency offset. According to the invention, the PSS can be locked quickly and accurately to realize time-frequency synchronization.

The invention relates to the technical field of radar signal processing, and discloses a false target processing method based on radar secondary reflection, and the method comprises the steps: distinguishing a newly-built target from a non-newly-built target, extracting the historical features of the non-newly-built target through exponential decay weighting, recognizing a strong reflection source, and calculating a dynamic region correction factor and the azimuth width in combination with a relative geometric attitude angle; therefore, a protection area which comprises a primary reflection area and a multi-reflection area and changes adaptively along with the attitude is constructed. Judging whether a new target falls into a protection area or not, and sequentially executing kinematics consistency, RCS strength physical upper limit constraint and amplitude fluctuation time domain correlation cascade verification on the falling target; and finally, integrating verification results to remove false targets. Through multi-dimensional feature coupling analysis, the problem that a traditional method is difficult to adapt to target dynamic maneuvering and signal fluctuation is solved, false targets are effectively restrained, and meanwhile the false deletion rate of real targets is reduced.

The invention relates to the technical field of LED backlight source testing, in particular to an LED backlight source brightness detection device and a detection method thereof. The method comprises the following steps: firstly, acquiring a static frame sequence of a brightness image of an LED backlight source to be detected and a synchronous driving current time sequence signal; constructing a brightness disorder coefficient based on the static frame sequence, and generating a detection distortion value by combining edge curvature mutation analysis of the superpixel region; generating a brightness fluctuation index based on the static frame sequence and the driving current time sequence signal, and constructing a defect comprehensive factor; analyzing the time domain correlation between the brightness fluctuation index and the defect comprehensive factor, and determining a brightness anomaly dynamic index; fusing the detection distortion value and the brightness abnormity dynamic index to generate a key space-time dynamic index; and inputting the key time-space dynamic index and the brightness image into a neural network model, and outputting a brightness detection index of the LED backlight source to be detected. According to the invention, the recognition capability of highlight area details and dark area gradient during brightness detection of the LED backlight source is improved.

The invention relates to an audio encoding method, an audio decoding method, a song audio encoding and decoding method, equipment, a medium and a program product, relates to the technical field of audio encoding and decoding, and can improve the audio encoding and decoding quality. The method comprises the following steps: acquiring an original audio signal to be coded; obtaining a first high-frequency sub-band signal and a first low-frequency sub-band signal corresponding to the original audio signal based on a sub-band segmentation result of the original audio signal in a time domain; respectively inputting the first high-frequency sub-band signal and the first low-frequency sub-band signal into respective corresponding sub-band encoders to obtain sub-band encoding results output by the sub-band encoders; and determining time domain association information of the plurality of sub-band coding results, and obtaining an audio coding result of the original audio signal according to the time domain association information and the plurality of sub-band coding results.

This document is directed to methods, systems, and devices related to wireless communication, and more specifically, to provide data transmission service for multiple users with different moving speeds. A method of wireless communication, comprising receiving, by a wireless communication device, a reference signal (RS); receiving, by the wireless communication device, a channel state information (CSI) reporting configuration signaling; determining, by the wireless communication device, according to the RS and the CSI reporting configuration signaling; and transmitting, by the wireless communication device, to a network device, a CSI according to the CSI reporting configuration signaling.

The application discloses a video encoding method, a video decoding method and a device, wherein the video encoding method comprises the following steps: acquiring a video frame to be encoded; using a resolution prediction network, which is used for modeling a video frame by using a space-time correlation of the video frame through a convolutional neural network and a recurrent neural network, and outputting a downsampling ratio corresponding to the video frame to be encoded; respectively encoding the video frame to be encoded according to the downsampling ratio and an original resolution; obtaining an optimal resolution according to a distortion value and an adjusted rate-distortion value; and adding the optimal resolution identifier to the encoded data. The video encoding and decoding method and device can adaptively select the downsampling information, improve the compression rate of the video encoding under the premise of ensuring the subjective quality, and solve the technical problem that the same resolution is used for video encoding and decoding in the related art, resulting in a large fluctuation of the peak signal-to-noise ratio.

The invention relates to a high-parallel spread frequency hopping measurement and control responder rapid capturing system and method, and belongs to the field of communication measurement and control, and the capturing method comprises the following steps: S1, presetting a frequency hopping sequence to output a corresponding carrier frequency, and outputting a frequency hopping synchronization signal after the initial capturing of the frequency hopping frequency is successful; s2, filtering processing is carried out, and then automatic gain control is carried out; s3, reducing the frequency of data extraction through data interleaving and off-chip DDR, and changing the sequence of data extraction; s4, completing time domain correlation on a frequency domain; s5, dividing n intervals to compensate the initial phase of the frequency hopping code phase and the phase sliding caused by Doppler; s6, dividing the data into N intervals, and performing FFT (Fast Fourier Transform) operation to find a maximum peak value; s7, determining a Doppler frequency offset value, a frequency hopping code phase and a direct spread code phase; and S8, the Doppler frequency offset value is fed back to a carrier NCO receiving signal, the frequency hopping code phase is fed back to local frequency hopping code de-hopping, and the direct spreading code phase is fed back to direct spreading code de-spreading.

Provided are a method and an apparatus for port mapping of a sounding reference signal SRS resource, and a terminal. A method for port mapping of an SRS resource includes following steps. A terminal sends an SRS resource. Port mapping of the SRS resource is implemented based on a target parameter, the target parameter includes at least one of a first parameter and a second parameter, the first parameter includes a Doppler domain-related parameter or an orthogonal cover code OCC sequence-related parameter, and the second parameter includes a time domain-related parameter.

The application provides a neural network-based lightweight streaming speech coding system and method, which comprises an encoding compression end and a decoding reconstruction end; the encoding compression end comprises a speech encoder and a quantizer; the speech encoder comprises a time-frequency conversion module, a feature extraction module, an encoding end channel conversion module and a long-range time domain correlation extraction module; the feature extraction module comprises a time-frequency feature extraction submodule and a time-frequency size downsampling submodule; the quantizer comprises two or more layers of quantization modules, each layer of quantization module comprising an encoding end first domain conversion module, an encoding end vector quantization module, an encoding end inverse vector quantization module and an encoding end second domain conversion module; and the decoding reconstruction end comprises an inverse quantizer and a speech decoder. The application can effectively extract multi-scale feature information in a speech signal, so that high-quality speech compression coding and reconstruction can be realized at an extremely low code rate, and the parameter quantity is small, the complexity is low, and streaming coding and decoding can be realized.

The invention provides a Chinese lute string fundamental frequency determination method and system, and the method comprises the steps: carrying out the time-frequency conversion of an audio signal, extracting a spectrum peak value, carrying out the energy weighting of the peak value according to a preset harmonic attenuation function, setting a candidate fundamental frequency set, constructing a preliminary harmonic cluster based on an initial non-harmonic coefficient, selecting a cluster with the highest energy, and calculating a real-time non-harmonic coefficient; and reconstructing candidate harmonic clusters according to the coefficient, and evaluating each harmonic cluster from two aspects of harmonic energy continuity and time domain correlation: calculating the sum of harmonic energy and combining with missing penalty to obtain an energy continuity score, and obtaining a time correlation score through a time cross-correlation mean value of fundamental frequency and each harmonic component energy envelope; and a comprehensive score is obtained after weighted summation.

The present disclosure provides a primary synchronization signal detection method, device and computer readable storage medium. The method comprises: performing segment compression preprocessing on three groups of local PSS time domain sequences respectively; performing down-sampling processing on a received signal; sliding point by point on a plurality of down-sampled data, and performing segment compression preprocessing on the time domain signal of the down-sampled data in each sliding correlation window; performing correlation operation on the time domain signal and the three groups of compressed time domain sequences to obtain three groups of time domain correlation values; searching for a maximum correlation peak value from the three groups of time domain correlation values, calculating the average value and the peak-to-average ratio value of the three groups of time domain correlation values; in the case that the ratio value is greater than or equal to a threshold value, determining the corresponding intra-cell identification group number and coarse synchronization time point according to the maximum correlation peak value; in the case that the ratio value is less than the threshold value, calculating a frequency domain correlation value, and determining the corresponding intra-cell identification group number and coarse synchronization time point according to the maximum correlation peak value of the frequency domain correlation value.

The invention discloses a switching power supply peak signal detection method based on improved CFAR, and belongs to the technical field of signal processing and power electronics. The method comprises the following steps: controlling superposition of high-frequency ripples and noise through a dynamic random switching sequence, generating a transient peak in combination with a Gaussian pulse model, and synthesizing a high-trueness interference signal; designing a band-pass filter and a cross-correlation alignment algorithm to realize signal preprocessing and time domain alignment; multi-dimensional similarity evaluation indexes (a time domain correlation coefficient, dynamic time warping and spectrum energy similarity) are proposed to quantize signal features; an improved CFAR (Constant False Alarm Rate) detection algorithm is combined with a clustering matching strategy, and the detection precision and robustness of the transient peak are improved. The method can be applied to interference simulation, fault diagnosis and signal quality evaluation of power electronic equipment, and has the advantages of high-fidelity signal generation and low false alarm rate detection.

The invention provides a lightweight streaming speech coding system and method based on a neural network. The system comprises a coding compression end and a decoding reconstruction end, the coding compression end comprises a voice coder and a quantizer; the voice encoder comprises a time-frequency transformation module, a feature extraction module, an encoding end channel transformation module and a long-range time domain correlation extraction module. The feature extraction module comprises a time-frequency feature extraction sub-module and a time-frequency size sampling sub-module; the quantizer comprises more than two layers of quantization modules, and each layer of quantization module comprises a coding end first domain transformation module, a coding end vector quantization module, a coding end reverse quantity quantization module and a coding end second domain transformation module; and the decoding reconstruction end comprises an inverse quantizer and a voice decoder. According to the method, the multi-scale feature information in the voice signal can be effectively extracted, so that high-quality voice compression coding and reconstruction can be realized at an extremely low code rate, the parameter quantity is small, the complexity is low, and streaming coding and decoding can be realized.

The utility model belongs to the technical field of radar signal testing, and discloses an E-band large-bandwidth radar signal testing system which comprises an E-band external mixer, an FSV spectrum analyzer, an RTO oscilloscope, a one-to-three-end power divider and a radio frequency cable used for being connected with a testing link, a tested E-band radar signal is connected with the input end of the E-band external mixer, and the input end of the E-band external mixer is connected with the output end of the FSV spectrum analyzer. A local oscillator output port of the FSV spectrum analyzer is connected with a local oscillator input port of the E-band external mixer, and an output port of the E-band external mixer is connected with an input port of the power divider. According to the invention, a spectrum analyzer with common performance and an oscilloscope are combined, a high-performance instrument is replaced by using the down-conversion principle of an external mixer and the large bandwidth of the oscilloscope, the frequency domain and time domain related performance index test of an E-band large-bandwidth radar signal is completed, the feasibility of the test and the accuracy of a test result are ensured, and the test efficiency is improved. And the test difficulty and the use cost are greatly reduced.

The invention relates to the technical field of network communication and information security, in particular to a patrol talkback terminal identity authentication method. The method comprises the steps of context initialization, environment perception acquisition, token iteration generation and server reconstruction verification. The terminal receives the initial parameters, determines a first context, fuses radio frequency, motion characteristics and biological information in offline patrol to generate an authentication token, and circularly constructs an orderly transmitted authentication token chain by taking the current token as a context element of a next node; the method is characterized in that a discrete patrol behavior is converted into a cryptographic Hash chain by using an iterative protocol, and reverse verification is carried out by a server after a network is recovered; according to the method, the time domain relevance of the data is ensured, replay attacks and track tampering in an offline environment are effectively prevented, and the security of a communication network is ensured.

The present disclosure provides a video coding method, device, electronic equipment, storage medium, program product and a method for storing a bitstream, the video coding method comprising: obtaining a frame set, wherein the frame set comprises a current frame and a plurality of frames subsequent to the current frame; performing time domain correlation analysis on the frame set to determine a correlation category of the frame set from a plurality of preset correlation categories, wherein the time domain correlation is a time correlation between adjacent frames, the plurality of preset correlation categories are used to represent different correlation degrees of the time domain correlation, and each of the plurality of preset correlation categories has a corresponding code rate prediction parameter; performing code rate prediction on the frame set according to the code rate prediction parameter corresponding to the correlation category of the frame set to obtain a predicted code rate of the frame set; determining a quantization parameter according to the predicted code rate of the frame set; and encoding the current frame using the quantization parameter. The method helps to improve the accuracy of code rate prediction.