28 results about "Gaussian approximation" patented technology

The invention discloses a covert communication system based on a generative diffusion model, and belongs to the technical field of covert communication. In order to solve the problems of insufficient concealment and poor anti-noise performance in the prior art, hidden transmission and reliable recovery of information are realized by constructing a diffusion generation and classification discrimination module. The sending end carries out noise addition and shaping on the original bit waveform by using a forward diffusion process to form a noise-like hidden signal; and a receiving end recovers a signal structure through a reverse denoising process, and accurately judges bit information through a classifier. According to the method, a Gaussian approximation hidden waveform library is constructed by adopting a signal pair training model which is consistent in statistics but distinguishable in structure, and random sampling mapping and boundary smooth splicing are combined, so that transmission signals are difficult to distinguish from noise in a frequency domain and a feature space; therefore, the avoidance capability, the anti-interference robustness and the information recovery accuracy under the low signal-to-noise ratio of the detection means are remarkably improved.

The invention discloses a GNN signal detection method based on an attention mechanism in a cellular-removed large-scale MIMO system, and belongs to the technical field of wireless communication. Aiming at the problem that the traditional EP algorithm adopts independent Gaussian approximation for multi-user posterior distribution and cannot effectively capture interference association among users, the method is combined with a graph neural network and a 2D MHA module, the 2D MHA module captures the interference relation between users through the time attention sub-block, the frequency attention sub-block captures the correlation between different features, the two outputs are spliced and subjected to linear projection to form enhanced feature representation, and meanwhile the fusion capacity of prior and likelihood information is enhanced through the EP module. According to the method, the low calculation complexity is kept while the detection precision is improved, and the adaptability and robustness of the algorithm in different channel and network environments are remarkably enhanced.

The invention relates to the technical field of computers, and discloses an industrial object-oriented Gaussian approximation filtering method for a nonlinear system. Mathematical modeling is carried out on a physical system to be subjected to state estimation, and a nonlinear state space model corresponding to the physical system is obtained; matching the first Gaussian distribution of the system state at the time t to a given distribution through a moment matching operation based on the non-linear state-space model to determine a predictive estimate and a predictive estimate error of the system state at the time t; acquiring a system observation value at the moment t; iteratively updating the optimal estimation and the optimal estimation error of the system state at the moment t based on a natural gradient descent method and a Fisher information matrix associated with the second Gaussian distribution of the system state at the moment t, and obtaining the optimal estimation and the optimal estimation error at the moment t until an iteration stop condition is met; linearization errors can be avoided, and more accurate system state estimation of a nonlinear system is provided.

A method of processing wireless communication signals for joint communication and environmental awareness in a region of interest (ROI) is presented. The method alternately uses a first iterative process and a second iterative process for determining an initial representation of a voxelized environment of the ROI and for determining the transmitted signal. The first iterative process and the second iterative process may implement a Gaussian approximation belief propagation process.

A method for evaluating classification models that are trained by using incomplete data sets for which data is known to be missing and the missing data is known to be non-random is provided. The method includes: receiving first information that relates to data to be used for training and evaluating a performance of a classification model that is designed to make a determination with respect to a particular query; analyzing the first information to determine second information that relates to a known portion of the first information and third information that relates to missing data; estimating, based on the third information, an uncertainty that corresponds to the missing data; and calculating, based on the second information and the estimated uncertainty, a first Gaussian approximation to a performance metric that relates to the first classification model.

The invention discloses an uplink outage probability analysis method and system for an unmanned aerial vehicle cooperating with a wolfberry picking trolley, and the method comprises the steps: constructing a joint effect model in a non-static multi-input multi-output scene, and determining an unmanned aerial vehicle and wolfberry picking trolley uplink cooperative communication scheme for achieving the maximum channel gain; deducing to obtain an uplink outage probability closed expression containing transmitting power, interference statistical characteristics and mobility parameters by adopting an interference statistic calculation method based on Laplacian transformation; based on the obtained uplink outage probability closed expression, an improved Gaussian approximation method is adopted, and an uplink outage probability approximate expression is obtained through a dynamic truncation criterion; and based on the obtained uplink outage probability approximate expression, obtaining the total error upper bound of approximate errors by using Gaussian approximation errors and space average errors, and realizing efficient and accurate evaluation and guaranteeing the reliability of agricultural automation communication through dynamic interference modeling and improved Gaussian approximation.

The application discloses a kind of multi-energy coupling and conversion comprehensive energy system multi-state reliability evaluation method.Establish the multi-state reliability model of multi-energy conversion element considering multi-energy conversion, using clustering algorithm reliability aggregation, and mapping formation aggregated multi-state reliability model;Multi-state reliability model of multi-energy coupling element considering multi-energy coupling is established, and then using Gaussian approximation and sampling approximation reliability approximation processing in sequence obtains multi-state approximate reliability model;The aggregated multi-state reliability model and multi-state approximate reliability model are processed according to the fast reliability evaluation method to obtain the reliability of the comprehensive energy system, and the reliability evaluation is realized.The application improves the traditional reliability evaluation method from time and accuracy, reduces the calculation time, and quickly and effectively realizes the estimation of system reliability.

The application provides a CRC concatenated Polar code encoding method for key set protection, which comprises the following steps: according to a Polar code Gaussian approximation (GA) construction algorithm, selecting reliable bit channels as information bits and unreliable bit channels as frozen bits; obtaining the information bit most likely to have the first error, i.e. the key set, through a code tree structure or Monte Carlo simulation; selecting a CRC polynomial to pre-encode the key set, and then appending the obtained CRC check vector to the end of the information bit vector; and finally encoding the pre-encoded vector by using a Polar code encoding method. The method has the following advantages: compared with a traditional CRC concatenated Polar code encoding method, the method can use a smaller CRC code length by protecting the key set, and can reduce the block error rate when applied to SC-Flip decoding.

The variational parameter determination unit 81 determines a variational parameter that specifies a position where a likelihood function and a lower bound of the likelihood function to be approximated by Gaussian are in contact. The gradient direction lower bound calculation unit 82 generates a likelihood function made one-dimensional in a gradient direction at the center of a prior distribution and calculates the lower bound of the generated likelihood function. The full dimensional lower bound calculation unit 83 sets covariances in directions other than the gradient direction to an arbitrary covariance and calculates the lower bounds of the set covariances.

The invention discloses a signal detection method and device based on Gaussian approximation interference and parallel architecture, relates to the field of digital signal processing, and solves the problem of complex calculation of a traditional E-MPA algorithm. The technical scheme is characterized in that a received signal vector is modeled to obtain a signal model; modeling interference terms in the received signal model as a Gaussian random variable distribution model, and determining to obtain Gaussian information; updating the function node to obtain a logarithm domain function node message; executing a cyclic shift gating operation according to the control signal; receiving a logarithm domain function node message, and carrying out variable node updating to obtain a normalized probability domain variable node message; the probability domain variable node message is returned for iterative updating until a preset number of times is reached; after the last iteration is completed, calculation is carried out, and the log-likelihood ratio of the bit stream is output; and the effects of reducing the calculation complexity, optimizing the in-chip storage access scheduling and greatly reducing the resource overhead are achieved.

The present invention discloses a non-orthogonal multiple access communication method based on Polar code. The information sent from the source is first encoded with Polar code, then modulated with GMSK and enters the channel; the signal is demodulated at the receiving end, then Polar code is decoded, and finally sent to the destination. Gaussian approximation (GA) structure and Tal-Vardy (TV) structure are used in Polar code construction. The present invention reduces the bit error rate and improves the performance of the NOMA system by encoding and decoding Polar code and modulating with GMSK; error control by Polar code can effectively improve the reliability of the communication system.

The invention discloses an anti-attack windowing Gaussian approximate fusion filtering method under unknown noise statistics. The method comprises the following steps: 1, establishing a multi-sensor nonlinear system dynamic model; 2, establishing a measurement model actually received by a local estimator; 3, designing an anti-attack windowing Gaussian approximation local filter unified framework; 4, calculating, and summing; 5, obtaining an estimator of unknown noise statistics based on a mobile windowing and random weighting estimation method; 6, determining a random weighting factor; seventhly, Gaussian weighted integral involved in the approximate local filtering unified framework is obtained, and local filtering is obtained; and 8, providing an anti-attack windowing Gaussian approximate sequential weighted covariance cross fusion filter in combination with a sequential thought and a weighted covariance cross fusion criterion. According to the method, the accuracy of the filtering performance of the fusion filtering problem of the multi-sensor nonlinear system with attack and unknown noise statistics under the Gaussian approximation filtering framework is effectively improved.

In a method of receiving a binary data sequence from one or more mobile UEs, the binary data sequence is represented by an SCMA signal transmitted over an OTFS communication channel to at least two RRHs of a CoMP radio communication system, the RRHs communicatively connected to a common BBU and serving the one or more mobile UEs from different directions, a continuous time domain signal representing an SCMA signal transmitted from the mobile UE is received at each RRH. After removing a cyclic prefix from a received time domain signal, OTFS demodulation is performed on the received signal, and centralized or decentralized signal detection and recovery is performed on a two-dimensional arrangement of information symbols in the delayed Doppler domain, both of which perform an iterative Gaussian approximation expected propagation process on the information symbols. The detected symbols are de-mapped to recover the binary sequence of transmissions of the respective mobile UEs that have received the signal.

The present invention relates to the technical field of power line carrier communication, and in particular to a coding method of polarization coding cascade space-time coding for MIMO-PLC systems. The method comprises: S1. polarization coding is performed on a transmitting end information source by Gaussian approximation; S2. the polarization code is modulated by binary phase keying to obtain modulated symbols; S3. the modulated symbols are passed through a space-time encoder, so that polarization coding and space-time coding are cascaded to construct PC-STBC coding; S4. the PC-STBC-coded information is sent to a receiving end through a transmitting end, and the receiving end decodes after receiving the PC-STBC coding. The method of the present invention brings diversity gain to the system through space-time coding, and brings coding gain to the system through the excellent error correction capability of polarization codes, so that the error performance of the MIMO-PLC system is effectively improved.

The invention discloses a polarization code decoding optimization method and a communication system, and the method comprises the following steps: A1, optimizing a Gaussian approximation method, and calculating a reliability value of a polarization channel based on the optimized Gaussian approximation method; a2, when the first continuous elimination decoding fails, determining a first bit index set based on a reliability value, a log-likelihood ratio and a channel index value, carrying out single bit flipping decoding in sequence based on the sequence of the first bit index set, and if flipping cyclic redundancy check decoding is successful in a preset flipping decoding time threshold, ending decoding; otherwise, executing the step A3; a3, combining the polarization channels in pairs, determining a second bit index set, performing two bit flipping decoding in sequence based on the sorting of the second bit index set, and if flipping cyclic redundancy check decoding is successful in a preset flipping decoding time threshold, ending decoding; and otherwise, the decoding process is ended, so that the bit flipping decoding performance is effectively improved.

The present invention discloses a self - adjustment method for achieving stable tracking and ranging based on Gaussian approximation of the laser optical axis. A set of data distributed according to the Gaussian distribution is randomly generated through a Gaussian surface. By controlling the offset of the laser optical axis for each group of data, a group of data is randomly selected, and laser ranging is performed according to the data distribution position. By detecting whether data is returned, if data is returned, the adjustment of the laser beam is stopped; if no data is returned, other groups of data are randomly selected. If during the ranging process, the laser ranging changes from having data returned to having no data returned, at this time, by adjusting the variance of the Gaussian surface, the randomly generated data distribution becomes more concentrated at the position where the data is lost, and the offset of the laser optical axis is controlled again according to the above process until data is returned by the laser ranging. Through the method of the present invention, the missing measurement rate of the laser rangefinder can be effectively reduced, and the visual field tracking center can be re - corrected in the case of the loss of target tracking and ranging, so as to achieve stable tracking and ranging of the laser rangefinder.

A residual life prediction method based on nonlinear wear and random jump comprises the following steps: firstly, constructing a health index of multi-source information fusion, and establishing a composite degradation model integrating a power law time scale function and a non-homogeneous Poisson process so as to simultaneously represent progressive accelerated wear and time-varying burst impact characteristics of equipment; then, designing an improved two-stage parameter estimation strategy, utilizing an expected condition maximization algorithm to process impact frequency hidden variables, identifying time-varying intensity parameters in combination with maximum likelihood estimation, and realizing robust identification of complex model parameters; deriving an approximate probability density function of the residual life based on a first passing time frame and a Gaussian approximation theory, and realizing probabilistic prediction through numerical integration; finally, a sliding window updating mechanism is established, and online self-adaptive adjustment and dynamic prediction of model parameters are achieved. The method is high in nonlinear fitting capability, sensitive in impact capture, high in prediction precision and accurate in uncertainty quantification under complex working conditions and limited observation data conditions.

The variational parameter determination unit 81 determines a variational parameter that specifies a position where a likelihood function and a lower bound of the likelihood function to be approximated by Gaussian are in contact. The gradient direction lower bound calculation unit 82 generates a likelihood function made one-dimensional in a gradient direction at the center of a prior distribution and calculates the lower bound of the generated likelihood function. The full dimensional lower bound calculation unit 83 sets covariances in directions other than the gradient direction to an arbitrary covariance and calculates the lower bounds of the set covariances.

The invention discloses a transmission method for an orthogonal frequency division multiplexing underwater acoustic communication system, and relates to the technical field of underwater acoustic communication, and the method comprises the steps: carrying out the Gaussian approximation construction and polarization coding of a coding sequence according to two groups of polarization construction parameters, carrying out the punching position selection of the polarization coding according to a channel reliability judgment result, and carrying out the punching position selection of the polarization coding; according to the method, the bit error rate is calculated through modulation and decoding of an orthogonal frequency division multiplexing underwater acoustic communication system, polarization construction parameters are iteratively optimized by comparing the bit error rate, system polarization codes are constructed through the optimized parameters, and system transmission is carried out. According to the method, the soft decision information obtained by Gaussian approximation construction is used for the punching algorithm, a quasi-uniform punching mode is adopted, the problem of characteristic change of the underwater acoustic channel after punching is solved, the influence of the channel and the actual transmission condition on the system is fully considered, the optimal punching and polarization structure is realized, and the system performance is improved. The whole communication system has more stable performance and environmental adaptability, and the system can realize stable transmission under different transmission conditions.

The application discloses a kind of multi-energy coupling's comprehensive energy system fast multi-state reliability improvement method.For the comprehensive energy system, a multi-state reliability model considering multi-energy coupling is established;Gaussian approximation is used to obtain a multi-state Gaussian approximation reliability model by approximating the reliability of the multi-state reliability model; a multi-state sampling approximation reliability model is obtained by approximating the reliability of the multi-state Gaussian approximation reliability model using sampling approximation; the approximate reliability of the comprehensive energy system under different multi-energy load requirements is calculated using a fast reliability evaluation algorithm for the multi-state sampling approximation reliability model; the approximate reliability is used to establish a reliability constraint condition for comprehensive energy system structure planning and standby optimization scheduling, thereby improving the reliability of the comprehensive energy system.The application improves the traditional reliability evaluation method in terms of time and accuracy, reduces the calculation time, and effectively improves the system reliability.

The present application discloses a transmission method for an orthogonal frequency division multiplexing water acoustic communication system, which relates to the field of water acoustic communication technology. The method includes: Gaussian approximation construction and polarization coding of a coding sequence according to two sets of polarization construction parameters, puncturing position selection of polarization coding according to the channel reliability judgment result, bit error rate calculation through modulation and decoding of the orthogonal frequency division multiplexing water acoustic communication system, iterative optimization of polarization construction parameters by comparing the bit error rate, and system polarization code construction by optimized parameters for system transmission. The present application uses the soft decision information obtained by Gaussian approximation construction for the puncturing algorithm, adopts a quasi-uniform puncturing method, compensates for the problem of changes in water acoustic channel characteristics after puncturing, fully considers the influence of the channel and actual transmission conditions on the system, and realizes the most optimized puncturing and polarization structure, so that the entire communication system has more stable performance and environmental adaptability, and the system can achieve stable transmission under different transmission conditions.

The invention relates to the technical field of unmanned aerial vehicle communication, particularly discloses a polarization code construction method suitable for a Rician fading channel, and provides two low-complexity polarization code construction methods suitable for a fast Rician fading channel, the first method is a simplified discrete density evolution (DDE) method, and the second method is a low-complexity polarization code construction method suitable for a fast Rician fading channel. According to the method, a probability density function PDF of a received symbol log-likelihood ratio LLR is discretized into a probability quality function PMF, optimization is achieved through PMF evolution based on minimum sum decoding, a numerical result shows that the proposed DDE method can effectively evaluate the polarization code performance and can also be used as a practical construction tool, and the method is suitable for popularization and application. According to the second method, a Rice channel is approximated to be a binary input additive Gaussian white noise B-AWGN channel with equivalent capacity, a Gaussian approximation density evolution (DEGA) method is adopted for optimization, the simulation result shows that the performance of the polarization code constructed by the Gaussian equivalent GE method is equivalent to that of the polarization code constructed by the DDE method, and meanwhile, the construction complexity is reduced.

The invention belongs to the technical field of communication channel coding, and particularly relates to a space coupling polarization code construction and decoding method under an AWGN channel, which comprises the following sequentially executed steps: S1, acquiring a reliability distribution sequence adaptive to the AWGN channel by adopting a Gaussian approximation algorithm; s2, calculating performance improvement scores under different coupling ratios by taking the bit error rate and the frame error rate of the first iteration as base lines, and selecting the ratio with the highest performance improvement score as the optimal coupling ratio; s3, generating a space coupling structure based on the optimal coupling ratio and the reliability distribution sequence; s4, optimizing the time aggregation weight based on the normalized kurtosis score, and obtaining system operation parameters; s5, performing enhanced iterative decoding, and outputting a decoding result; a quality index optimization weight coefficient is introduced, and time domain correlation among different iteration stages is fully mined.

The present invention provides an image processing method, system, and device based on a covariance-optimized diffusion model for image reconstruction, image denoising, image restoration, image deblurring, or image super-resolution. The method comprises: obtaining measurement values; establishing, based on diffusion model theory, a guided unconditional pre-trained diffusion model to implement conditional probability sampling, with the final sampling result serving as the reconstructed image; and using the maximum likelihood method in the conditional probability sampling to obtain the optimal posterior covariance, which serves as the covariance for the guided Gaussian approximation. The present invention can improve the accuracy of existing image reconstruction and reduce sensitivity to model parameters, making it applicable to a wide range of reconstruction scenarios, including image denoising, restoration, and enhancement.

A method for evaluating classification models that are trained by using incomplete data sets for which data is known to be missing and the missing data is known to be non-random is provided. The method includes: receiving first information that relates to data to be used for training and evaluating a performance of a classification model that is designed to make a determination with respect to a particular query; analyzing the first information to determine second information that relates to a known portion of the first information and third information that relates to missing data; estimating, based on the third information, an uncertainty that corresponds to the missing data; and calculating, based on the second information and the estimated uncertainty, a first Gaussian approximation to a performance metric that relates to the first classification model.

The invention provides a wind power plant power adjustment method and device, equipment and a storage medium. The wind power plant power adjustment method comprises the steps of generating wind speed time sequence data of a target working condition by using a Kaimal model based on an average wind speed, turbulence intensity and scale parameters of the target working condition; obtaining a conditional probability density function satisfied by the wind speed time sequence data through Gaussian approximation; performing convolution correction on a known calibration power curve based on a conditional probability density function satisfied by the wind speed time sequence data to obtain a corrected power curve under the turbulence intensity; and adjusting the output power of the wind turbine generator under the turbulence intensity based on the modified power curve and the real-time wind speed. The embodiment of the invention can effectively improve the adjustment accuracy of the output power of the wind turbine generator under the turbulence condition.

The invention provides an incremental pulsar candidate body identification method and system based on a low-rank Bayesian neural network. The method comprises the following steps: firstly, preprocessing observation data of a radio telescope to generate a multi-modal diagnostic graph; then constructing a Bayesian neural network containing one-dimensional and two-dimensional convolution branches, introducing a low-rank and diagonal Gaussian approximation technology in a variational inference process, decomposing a weight matrix into the sum of a low-rank matrix and a diagonal matrix, and greatly reducing the parameter space complexity; and meanwhile, a mixed loss function is constructed in combination with Focal Loss and KL divergence. According to the system, model parameters can be updated online along with inflow of new observation data without forgetting old knowledge, the calculation complexity is reduced from O (d2) to O (dr), memory occupation and training time are remarkably reduced, and the system is suitable for resource-limited real-time astronomical data processing terminals and large-scale patrol projects.

The present invention specifically relates to a polar code channel construction method based on frozen bit improvement. The present invention belongs to the field of channel coding technology. The method first estimates the reliability measure of each polarization sub-channel by using the Gaussian approximation principle, selects the most reliable channel, then finds the row weight of the generator matrix corresponding to the selected channel, and selects the channel with smaller row weight again. Finally, according to the two proposed frozen channel setting principles, namely: the principle of setting frozen channels with appropriate bits for channel segments with different reliabilities and the principle of setting frozen channels at intervals of long information channel segments with smaller row weights and at the back, select channels with appropriate bits and set them as frozen channels, and the remaining channels are information channels, and SCL decoding is used for decoding. Simulation results show that the polar code channel construction method based on frozen bit improvement proposed by the present invention has obvious performance improvement, and the computational complexity is similar.