127 results about "Decorrelation" patented technology

The invention discloses a transformer equipment state real-time monitoring method and system based on multi-source data fusion, and particularly relates to the technical field of transformer equipment state monitoring, and the method comprises the steps: firstly obtaining a unified time reference through the multi-channel time alignment driven by an event anchor point, and employing a strategy of combining rough alignment with refined alignment; on the basis, the channel alignment confidence coefficient is constructed according to the main peak sharpness ratio, the group delay consistency, the phase locking consistency and the geometric consistency of temperature compensation; then acoustic emission spectrum energy and pulse number, vibration impact characteristics and cross-sensor consistency characteristics are extracted under a unified time reference, and dynamic threshold setting is carried out in combination with load and environment context; performing gating weighting, intra-group decorrelation and probability calibration on the multi-source evidence according to the channel health factor to obtain calibrated fault probability and inconsistency; and finally, outputting a grading result under the constraint of multi-stage judgment and physical consistency rechecking controlled by the error discovery rate.

The invention discloses a bearing fault diagnosis method based on a causal decoupling network, and relates to the technical field of computers. The method comprises the following steps: extracting overall characteristics of a sample bearing vibration signal; extracting cross-domain consistent causal factors of the overall features, and carrying out bearing fault classification on the causal factors; an extractor extracts non-causal factors of the overall features, performs fault classification on the non-causal factors, and performs domain classification on the non-causal factors; and determining the loss of the causal decoupling model based on the cross entropy loss of the causal branch and the non-causal branch, the cross-branch decorrelation loss, the maximum entropy loss and the branch specialization loss, and adjusting the parameters of the causal decoupling model until the loss of the causal decoupling model is minimum. The false correlation between the non-causal factors and the fault classification labels is blocked, and a trained causal decoupling model is obtained; and carrying out fault diagnosis on the to-be-classified bearing vibration signals through the trained causal decoupling model. The method can improve the diagnosis precision of the bearing fault.

The invention discloses a subcarrier-level diversity combining method and subcarrier-level diversity combining equipment for multi-frequency diversity, and relates to the technical field of wireless communication. The method comprises the following steps: receiving a plurality of frequency points bearing the same service, and respectively carrying out orthogonal frequency division multiplexing demodulation on each frequency point to obtain a symbol estimation value; calculating a soft decision log-likelihood ratio and a reliability vector according to the symbol estimation value; aligning the time deviation, the carrier frequency deviation and the sampling rate deviation generated by frequency crossing of each frequency point based on each symbol estimation value; performing decorrelation processing on the aligned soft decision log-likelihood ratio to obtain a decorrelated soft decision log-likelihood ratio, and performing merging operation on the decorrelated soft decision log-likelihood ratio according to the aligned reliability vector to obtain a merged soft decision log-likelihood ratio; and decoding the merged soft decision log-likelihood ratio to obtain a decoding result, and adjusting the merging operation according to the decoding result. By implementing the technical scheme provided by the invention, the diversity combining accuracy can be improved.

The invention relates to a double-antenna BDS-R real-time water level monitoring method and an integrated device, and belongs to the technical field of GNSS remote sensing. The method comprises the following steps: data acquisition; data processing: firstly decoding the received data, and extracting a double-frequency pseudo range and a carrier phase observation value; a second step of performing quality control on the decoded data, including constraint of an elevation angle and an azimuth angle, cycle slip detection and the like, and eliminating non-water-surface reflection signals and abnormal data; a third step of establishing a double-difference observation equation based on the pseudo-range and carrier phase observation value, introducing a horizontal baseline constraint into the observation equation, and enhancing the resolving stability through virtual observation quantity; fourthly, Kalman filtering is used for achieving per-epoch baseline estimation, and a least square ambiguity decorrelation adjustment (LAMBDA) method is used for solving a baseline fixed solution; and finally calculating the water level of the current epoch by using the baseline vector. And transmitting data. According to the invention, the problems of poor real-time performance, complex deployment and high cost in the existing water level monitoring technology are solved.

The invention relates to the technical field of satellite navigation signal processing, in particular to an integer ambiguity resolving method based on a hybrid adaptive differential evolution grey wolf algorithm, which comprises the following steps of: loading GNSS (Global Navigation Satellite System) original data to carry out decorrelation, and calculating an adaptive integer search space boundary; calculating the solution of each individual, storing, comparing the fitness of each individual, and updating and recording globally optimal, suboptimal and third optimal solutions; executing a variation-crossover-selection process of differential evolution to generate a new generation of population; parameter self-adaption and Levy flight are executed; checking whether the current number of iterations reaches a preset maximum number of iterations, if not, adding one to the counter, returning and repeating the steps of comparing the fitness of each individual, updating and recording the global optimal solution, the suboptimal solution and the third optimal solution, and if yes, starting local search to find a better global optimal wolf; and the final calculation result finally recorded in the global optimal wolf variable is output, so that the premature convergence problem in the traditional algorithm solution is solved, and the solution success rate is improved.

This invention discloses a radar embedded communication method based on OTFS modulation. The implementation steps are: 1. Generating an integrated signal based on OTFS modulation; 2. Estimating the relative speed and distance of the RF tag by the integrated signal receiver; 3. Modeling the time-domain channel based on the speed and distance measurement results of the RF tag by the integrated signal receiver; 4. Equalizing the received signal using the constructed time-domain channel matrix and performing decorrelation decision on the equalized signal. This invention utilizes the characteristic that OTFS signals can obtain full channel diversity in both time and frequency, achieving a more accurate estimate of the time-varying frequency-selective bidispersive wireless channel, and equalizing the fading signal, reducing the communication symbol error rate and effectively improving the communication reliability of the radar embedded communication system.

The invention discloses a fracturing pump multi-cylinder vibration signal processing method and device, equipment, a medium and a product. A vibration data sequence and a key phase pulse signal are obtained, and the vibration data sequence is vibration data collected by a vibration sensor installed between adjacent cylinder bodies of a fracturing pump; the key-phase pulse signals are key-phase pulse signals collected by a phase sensor installed at the crankshaft part of the fracturing pump, then carrying out decorrelation on the vibration data sequence to eliminate the correlation of the vibration data sequence, then carrying out independent analysis on the vibration data sequence after decorrelation, outputting a plurality of vibration data sequences to be matched, and outputting the vibration data sequences to be matched; and finally, based on the key phase pulse signal, matching the plurality of to-be-matched vibration data sequences with the adjacent cylinders to obtain a target vibration data sequence corresponding to each cylinder, so that vibration data with stronger feature information can be extracted while the use amount of sensors is remarkably reduced and the cost and complexity are reduced, and the accuracy of the vibration data is improved. Therefore, the accuracy and timeliness of fault diagnosis of the fracturing pump are effectively improved.

The invention discloses an electric power operation safety supervision target detection method, system and device based on semantic clustering and a medium, and belongs to the technical field of target detection and semantic analysis, and the method comprises the steps: extracting the image features of a target picture, determining candidate boxes needed by target detection through a region generation network, and unifying the sizes of the candidate boxes; extracting category semantic features of the target picture, and generating category semantic feature vectors; according to the candidate box, generating a clustering feature vector through a multi-layer sensing mechanism; calculating class decorrelation loss based on the clustering feature vector; calculating semantic clustering loss; and according to the candidate box, a target detection result is obtained through a multi-layer sensing mechanism, and classification loss and regression loss are calculated. According to the method, the wearing state of safety protection equipment and abnormal equipment can be accurately detected in a complex power grid environment, the problems of misjudgment and missing detection of unknown samples by a traditional detection model are effectively solved through semantic feature constraint and feature space reconstruction, and the intelligent safety supervision efficiency in scenes such as electric power inspection and high-altitude operation is improved.

The invention discloses a data processing method and system based on Lie algebraic dynamics and an entropy modulation mechanism, and relates to the technical field of artificial intelligence and data processing, and the method comprises the steps: constructing a group action operator on a physical manifold, and carrying out the manifold enhancement of input data; the Hilbert subspace decomposition and decoupling of the feature channel are completed in parallel through a learnable decorrelation kernel and tensor contraction operation by using a matrix parallel elastic orbit layer; mapping the features to a symplectic geometric phase space, and introducing an adaptive symplectic respiration operator and a Hamiltonian kinetic equation to carry out physical conservation evolution; constructing a Lie algebra classifier, and determining a data category by calculating a Lie bracket transpose norm of a feature generator and a category base; and guiding model training by using an entropy modulation action quantity loss function containing physical potential energy. The method can solve the problems of poor generalization and weak anti-noise capability of a traditional deep learning model, and can be widely applied to the fields of power equipment monitoring, computer vision, natural language processing and the like.

The audio device comprises a receiver (201) arranged to receive a set of input audio signals. An audio beamformer (101) performs beamforming by combining the outputs of the filters. The feedback circuit (103) comprises a set of matched filters having a complex conjugate frequency response, and the beamforming adapter (105) adapts the filters in response to a comparison of the input audio signal and the feedback audio signal. An adaptation coefficient processor (207) determines decorrelation coefficients for a set of spatial decorrelation filters that generate a decorrelated output signal from an input audio signal, where the decorrelation coefficients are adapted based on the input signal. A set of spatial filters (205, 301, 401) is arranged to apply spatial filtering to the input audio signal or the feedback signal, wherein the set of spatial filters has coefficients determined from the decorrelation coefficients.

The invention relates to a broadband distributed radar interference waveform estimation and suppression method and device, and the method comprises the steps: inputting a receiving sampling signal of a distributed radar, including an interference signal, a target echo and receiving noise; constructing an observation matrix according to the interference parameters; through Fourier transform, converting the time domain signal model of the distributed radar for confronting multiple interferences into a frequency domain model; interference parameters are initialized through design of orthogonal waveforms and cross-correlation analysis, interference signals, a complex coefficient matrix and the interference parameters are optimized through internal and external nested loops, and interference waveform estimation is achieved. And eliminating the interference signal after waveform estimation from the received signal to complete interference suppression. Therefore, the problem that a traditional airspace interference suppression algorithm fails due to interference decorrelation of a current broadband distributed radar system is solved.

This disclosure provides an audio encoding method, an audio decoding method and apparatus therefor, an electronic device, a storage medium, a computer program product, and a computer program. [Solution] The method includes the steps of: grouping a channel sequence to obtain a plurality of channel groups, each channel group containing a plurality of consecutive channels in the channel sequence, with one or more identical channels between adjacent channel groups; performing a frequency domain transformation on each audio signal of each channel in the channel sequence frame by frame to obtain frequency domain coefficients for each frame of each channel; determining a target transformation matrix for each frequency band in a frequency band set corresponding to the channel group from a set of transformation matrices based on the frequency domain coefficients of each channel; performing same-band decorrelation on the frequency domain coefficients of the channels in the channel group based on the target transformation matrix for each frequency band to obtain coding information for the channel group; and obtaining a coded stream based on the coding information for the channel group and sending the coded stream to a decoder for decoding.

A method for determining a velocity of objects in a medium comprises inputting a wave into a wave interference network, generating a first and at least one second point spread function (PSF), outputting at least one propagation mode of the wave to the medium for illuminating the medium therewith, collecting a scattered signal from the medium, acquiring a first signal having the first PSF associated therewith and at least one second signal having the at least one second PSF associated therewith, determining a first correlation of at least one of the first signal and the at least one second signal, and a second correlation of at least one of the first signal and the at least one second signal, determining a ratio between the first correlation and the second correlation, and determining the velocity of the one or more objects in the medium based on the ratio.

This disclosure provides systems, methods, and devices for wireless communications that support operation with an antenna array, such as multiple-in-multiple-out (MIMO) and / or beamforming. In a first aspect, a method for wireless communications includes exciting elements of an antenna array simultaneously using a plurality of encoded signals; determining a correlation matrix indicating a response of the antenna array based on responses of the elements of the antenna array captured during simultaneous excitation of the antenna array; and transmitting signals from at least some elements of the antenna array simultaneously based on the correlation matrix. Other aspects and features are also claimed and described.

The invention provides a conventional beam forming method and system and a water depth detection method and system based on array data decoherence, and the beam forming method comprises the steps: carrying out the frequency mixing and filtering of a signal received by an array element, obtaining a baseband signal, calculating an array baseband signal covariance matrix, and introducing a tiny regularization factor; performing eigenvalue decomposition on the array baseband signal covariance matrix, and calculating an inverse square root matrix of the array baseband signal covariance matrix to obtain a solution coherence matrix for eliminating spatial correlation; multiplying the array baseband signal by the decoherence matrix to realize elimination of correlation data between array elements and obtain a decoherence array baseband signal; and carrying out total energy normalization processing on the array baseband signal after decoherence, and then inputting the array baseband signal into a conventional beam former to carry out beam forming. The method has the advantages that space correlation noise is effectively suppressed, and the integrity of signal energy is kept; not only is the resolving power of beam forming improved, but also the robustness in a complex noise environment is enhanced.

An apparatus for decoding a signal is provided. The apparatus comprises a transient separator (410) for separating an apparatus input signal into a first signal component and into a second signal component such that the first signal component comprises transient signal portions of the input signal and such that the second signal component comprises non-transient signal portions of the input signal. Moreover, the apparatus comprises a transient decorrelator (420) for decorrelating the first signal component according to a first decorrelation method to obtain a first decorrelated signal component; wherein the transient decorrelator (420) is configured to decorrelate the first signal component according to the first decorrelation method by multiplying a phase term with the first signal component. Furthermore, the apparatus comprises a further second decorrelator (430) for decorrelating the second signal component according to a second decorrelation method to obtain a second decorrelated signal component, wherein the second decorrelation method is different from the first decorrelation method. Moreover, the apparatus comprises a combining unit (440) for combining the first decorrelated signal component and the second decorrelated signal component to obtain a decorrelated combination signal. Furthermore, the apparatus comprises a mixer (450), being adapted to receive mixer input signals and being adapted to generate output signals based on the mixer input signals and a mixing rule. The mixer (450) is adapted to receive correlation / coherence parameter data indicating a correlation or coherence between two signals and is adapted to generate the output signals based on the correlation / coherence parameter data.

The audio device comprises a receiver (101) arranged to receive a set of input audio signals segmented by a sectionalizer (103). An output signal generator (105) generates an output audio signal by performing, for each segment, the following steps: generating (201) a frequency bin representation of the input audio signal; generating (203) a frequency bin representation of the output audio signal as a weighted combination of frequency bin values of the input audio signal of the frequency bin; the frequency bin representation is converted to the time domain. The adapter (107) updates a weight for a given weight in response to a correlation metric between an output frequency bin value of the output audio signal being generated and the output audio signal linked to the input signal weighted by the weight. The approach may generally provide improved frequency domain adapted spatial decorrelation of audio signals.

The audio device includes a receiver 101 configured to receive an audio signal from which an audio beamformer 103 generates a beamformed output audio signal. The beamformer 103 includes a signal processor 201 that applies signal processing to the audio signal. Signal processing includes spatial beamforming and spatial decorrelation, which is often adapted spatial decorrelation. A decorrelation adapter 203 adapts decorrelation parameters depending on the audio signal, and a beamform adapter 205 adapts beamform parameters depending on the beamformed output audio signal. An equalizer 105 applies frequency equalization to the beamformed output audio signal to generate an output signal, and an equalization adapter 107 adapts frequency equalization depending on the beamform parameters, typically also depending on the decorrelation parameters. This approach provides improved fidelity to the desired sound source and attenuates interfering sound sources.

The present invention discloses a multi-exposure image fusion method based on pyramid convolution, comprising the following steps: Step 1: splicing overexposed and underexposed images by channel and preprocessing them to obtain a system input; Step 2: sending the system input to a decorrelation module to eliminate channel-level and pixel-level correlations in the data; Step 3: performing feature fusion on the output of Step 2 through an encoder and mapping it to a high-dimensional data space; Step 4: performing dimensionality reduction on the fused high-dimensional data through a decoder, reconstructing the fused image, and completing multi-exposure fusion. The multi-exposure image fusion method of the present invention can improve halos and artifacts when fusing extreme lighting scenes, enhance the generalization ability of the multi-exposure image fusion algorithm for extreme scenes, and is widely used in scenes such as underwater and nighttime observation.

The application discloses a kind of parallel random number generation devices based on pulse driving micro-ring resonator cavity, by adopting pulse mode driving micro-ring resonator cavity, improve the instantaneous power level in cavity, enhance nonlinear effect, to effectively expand the effective bandwidth of chaotic entropy source, improve the complexity of entropy source.Meanwhile, using the characteristics that micro-ring resonator cavity naturally supports multi-wavelength output, and combining with filter demultiplexing structure, the parallel output of multiple chaotic entropy sources is realized, which is beneficial to improve the parallel generation ability of random number.Finally, by combining post-processing methods such as difference, quantization and decorrelation, the overall generation rate of random bits is improved while ensuring randomness quality.The application has relatively simple structure, is suitable for integrated implementation, and can meet the application requirements of high-speed parallel random number generation.

The present solution can provide content based stereo signal processing for an audio system, such as an audio system of a vehicle. An audio system can include one or more processors of a data processing system coupled with memory to identify a stereo signal of an audio system of a vehicle. The one or more processors can determine a factor indicative of correlation between a first portion of the stereo signal and a second portion of the stereo signal. The one or more processors can select, based on the factor, a setting for generating a plurality of audio signals. The audio system can include a decorrelation circuit to generate, based on the stereo signal and according to the setting, the plurality of audio signals for a plurality of speakers in the vehicle.

This invention discloses an optimization prediction method for software testing based on big data management, specifically including: Step 1, collecting test data and performing time index alignment and numerical processing to form a test feature set; Step 2, constructing a static Markov blanket and a dynamic Markov blanket, and determining the target feature subset by switching input boundaries; Step 3, constructing a neural prediction model based on the target feature subset and outputting predicted values; Step 4, dividing the target feature subset into relevant feature clusters and updating the model parameters using the decorrelation-based isoangular minimum angle regression rule; Step 5, outputting test results, defect risk, and resource consumption prediction values; Step 6, generating test optimization configuration results based on the predicted values. This invention completes the prediction through isoangular regression using a two-layer Markov blanket.

The invention provides a physical layer key generation method of a hidden key construction path, which comprises the following steps: two communication parties use a shared partitioning algorithm to block an original key to obtain a non-repeated and ordered key fragment sequence; the method comprises the following steps: a first communication party samples a secret key fragment sequence of the first communication party, disturbs unsampled secret key fragments by using a disturbance device, and then splices the unsampled secret key fragments with the sampled secret key fragments according to the sequence of original secret key fragments to obtain a disturbed secret key fragment sequence; the second communication party carries out information coordination on a secret key fragment sequence of the second communication party on the basis of the sequence to obtain an error-corrected secret key fragment sequence; converting the error correction result into a sampling index; and the two communication parties perform sampling according to the sampling index, and then perform compression by adopting a privacy amplification technology to obtain a final key. According to the method, a secret key path is hidden as a means, a stronger security protection choice is provided for a PKG task in a spatial decorrelation or even active attack scene, and the security boundary of the PKG is greatly widened.

The invention provides a gross error detection method, gross error detection equipment, a readable storage medium and a product, and relates to the technical field of positioning. The method comprises the following steps: inputting a satellite observation value into an RTK filter, and obtaining a residual error output by the RTK filter at the current moment and a prediction variance covariance matrix of the residual error; determining an error in a unit weight according to the residual error and the predicted variance covariance matrix, and calculating a dynamic threshold value according to the error in the unit weight; according to a preset experience threshold value and a dynamic threshold value, performing first gross error elimination on the residual error to obtain a first residual error sample; according to the condition number of the predicted variance covariance matrix, performing second gross error elimination on the first residual error sample to obtain a second residual error sample; and performing de-correlation calculation on the second residual error sample construction, and performing adaptive robust filtering on a de-correlation residual error subset. According to the method, gross error elimination is carried out from a data layer and a model layer, and more accurate and efficient RTK gross error detection capability is achieved.

The invention discloses an unsupervised time sequence action positioning method for cross-view audio-visual enhancement based on CLIP assistance. The method comprises the following steps: extracting audio features, classification pre-training (CBP) visual features and visual language pre-training (VLP) features from an input video; performing multi-stage iterative optimization on the audio and CBP features through an audio and video cross attention fusion module, and generating audio-visual fusion features retaining modal features in combination with cross attention weight calculation and dense jump connection; executing a multi-modal attention mechanism on the CBP and VLP features by using a cross-view cooperation normal form, and generating enhanced double-view features; a self-supervised learning mechanism is further introduced, feature decorrelation constraint is applied to the fused features, cross-view instance distinguishing constraint is applied to the enhanced view features so as to enhance the representation discrimination force, and the model is jointly optimized; and finally, outputting a high-precision action time sequence positioning result. According to the method, multi-modal information is fused and self-supervised learning is cooperated, so that the action boundary positioning integrity and the recognition robustness of audio-related actions are remarkably improved.

The application provides a kind of missing distribution offset based on the prediction method and system of incomplete data, comprising: with incomplete feature as input, construct the prediction function network based on multilayer perceptron, predict complete label;Construct the prediction function parameter network based on multilayer perceptron, learn the relevance between prediction function parameter and missing condition;Using random Fourier feature, the relevance between incomplete feature and missing condition is measured;According to random Fourier feature, the weight of incomplete sample in data set is redistributed;By minimizing the prediction reconstruction error, the prediction function parameter network and the prediction function network are jointly trained, and the overall predictability of the combined two networks is optimized.The application uses a prediction framework based on decorrelation, which can effectively learn the underlying relevance between complete labels and incomplete features, thereby achieving good generalization performance when the missing distribution is offset.

This invention proposes a stable target recognition method and apparatus based on visual feature random partitioning and decorrelation. The method includes: acquiring a visual feature set of a training dataset consisting of industrial images and their defect labels, and performing multiple random partitions; after each partition, all dimensions of visual features are divided into two mutually exclusive feature segments; under each feature partitioning scheme, using the training dataset, learning a set of sample weights to decorrelate the two feature segments in a weighted distribution; weighting the training data using the sample weights, and using the weighted training data to train a base recognition model; inputting the image to be recognized into the trained base recognition model to obtain the corresponding recognition result; and integrating the recognition results from all models to obtain the final stable recognition result. This invention can effectively alleviate the environmental bias problem in industrial production lines and improve the stability and generalization performance of defect detection models with limited training data.

Disclosed is an audio signal encoding / decoding method that uses an encoding downmix strategy applied at an encoder that is different than a decoding re-mix / upmix strategy applied at a decoder. Based on the type of downmix coding scheme, the method comprises: computing input downmixing gains to be applied to the input audio signal to construct a primary downmix channel; determining downmix scaling gains to scale the primary downmix channel; generating prediction gains based on the input audio signal, the input downmixing gains and the downmix scaling gains; determining residual channel(s) from the side channels by using the primary downmix channel and the prediction gains to generate side channel predictions and subtracting the side channel predictions from the side channels; determining decorrelation gains based on energy in the residual channels; encoding the primary downmix channel, the residual channel(s), the prediction gains and the decorrelation gains; and sending the bitstream to a decoder.

The application provides a self-adaptive signal beam forming method, device, equipment and storage medium. The method is based on a 2N+1 element uniform linear array receiving signal. The method comprises the following steps: a multiple Toeplitz matrix is constructed, and a covariance matrix is obtained by merging; a signal direction vector is calculated according to an eigenvalue and an eigenvector, and an expected signal direction vector is obtained by optimization; a noise power is estimated by using a minimum eigenvalue, a corresponding relationship between a signal power and the eigenvector is established, and an expected signal power is determined; a covariance matrix of mutually independent noise is reconstructed according to the noise power, the corresponding relationship and the expected signal power; and the expected signal direction vector and the reconstructed covariance matrix are brought into a Cap on beam former, and an optimal weight vector is calculated to control beam forming. The method improves the performance and reliability of the beam forming system in a complex signal environment by constructing a multiple Toeplitz matrix and using the characteristics of the multiple Toeplitz matrix for signal decorrelation and covariance matrix reconstruction.