173 results about "Decorrelation" patented technology

The invention discloses a big data auxiliary key generation method and system in communication data encryption transmission, and relates to the technical field of big data analysis and processing. The dynamic entropy source processing module is used for generating a high-randomness entropy pool by combining an information entropy quantification model and adopting a Shannon entropy and minimum entropy fusion algorithm; the anti-quantum key generation module is used for generating a dynamic variable-length key seed based on an entropy pool driven post-quantum cryptographic algorithm; the hierarchical key negotiation module adopts a clustering Diffie-Hellman protocol, dynamically divides negotiation according to network topology, and precomputes and reduces the load of a core network through edge nodes; and a lightweight verification and update module. According to the method, high-entropy sources such as environmental noise, user behaviors and equipment hardware fingerprints are fused with low-entropy sources such as network messages and sensor data, and an intelligent acquisition strategy and a nonlinear decorrelation technology are combined, so that the anti-quantum dynamic entropy pool is generated, and the randomness of a secret key and the reliability of the entropy sources are improved.

A diagnosis system is provided for diagnosing the partial discharge faults in a power transformer. The system includes a feature extractor, a fault classifier and a domain discriminator and whose parameters are optimized by minimizing a combination of feature loss, classifier loss and domain discrepancy discriminator loss. The feature loss is a weighted sum of cosine similarity distance loss, batch-based instance separation loss, and batch-based feature decorrelation loss. The measured applied voltages and partial discharge voltages are pre-processing using sliding window method to represent the each partial discharge event as a series of statistics based moments for a set of overlapped time blocks within the duration of fault event, wherein statistics based moments include an average value of applied voltage for representing the applied voltage magnitude and fault event occurring moment for each time block, and the mean, standard deviation, Kurtosis, and Skewness of partial discharge voltages for representing the variations of partial discharging within each time block.

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 belongs to the technical field of synthetic aperture radars, and relates to an InSAR sequence time decoherence suppression method based on a complex covariance matrix, and the specific process is as follows: for a plurality of input SLC SAR image complex vectors, extracting a single-pixel p-dimensional complex scattering vector at a pixel x, and generating an initial complex covariance matrix; the method comprises the following steps: generating a rectangular search window Wx by taking a pixel x as a center, aiming at multiple input SLC SAR image complex vectors, extracting a p-dimensional complex scattering vector of a single pixel at a pixel y in the search window, and generating a reference complex covariance matrix; enabling the pixel y to traverse each pixel except the pixel x in the rectangular search window Wx, and calculating a maximum likelihood test statistic Q (x, y) according to the initial complex covariance matrix and the reference complex covariance matrix; and based on a complex covariance matrix # imgabs0 # estimated by Q (x, y), extracting the intensity, the phase and the correlation coefficient of the InSAR sequence after de-coherence suppression at the pixel x from the complex covariance matrix # imgabs0 #, and finally obtaining a time sequence de-coherence suppression result of the complete SAR interferogram sequence.

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.

An apparatus for decoding an encoded multichannel signal includes: a base channel decoder for decoding an encoded base channel to acquire a decoded base channel; a decorrelation filter for filtering at least a portion of the decoded base channel to acquire a filling signal; and a multichannel processor for performing a multichannel processing using a spectral representation of the decoded base channel and a spectral representation of the filling signal, wherein the decorrelation filter is a broad band filter and the multichannel processor is configured to apply a narrow band processing to the spectral representation of the decoded base channel and the spectral representation of the filling signal.

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.

The invention relates to the technical field of broadband radar signals, and provides a radar target robust intelligent detection and interference adaptive suppression method and system, and the method comprises the steps: carrying out the decorrelation transformation of received data and a parameter matrix through employing the skew symmetry characteristic of a clutter covariance matrix, and completing the preprocessing of initial data; carrying out correlation calculation estimation under the condition of no target hypothesis and under the condition of target hypothesis, and constructing distance extension target Gradient detection statistics under the condition of a known clutter skew symmetry covariance matrix; constructing a detection statistic lambda of the radar target robust intelligent detection and interference adaptive suppression method; and determining a detection threshold T through theoretical calculation or Monte Carlo simulation according to a preset false alarm probability, comparing the detection statistic lambda with the detection threshold T, and judging whether a distance expansion target exists in the current distance unit to be detected or not according to a comparison result. According to the method, an analytical expression design is adopted, a complex iterative calculation process is avoided, and the operation efficiency 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.

A method performed by a network node is provided. The method includes obtaining a first channel estimation value of a channel between the network node and a user equipment, by performing frequency-domain channel estimation based on a decorrelation signal related to reference signal symbols received from the user equipment, determining whether a channel type of the channel is a high-speed train channel, and in accordance with a determination that the channel type of the channel is the high-speed train channel adjusting frequency offset of the channel, and obtaining a second channel estimation value based on the adjusted frequency offset and the first channel estimation value.

The invention provides a large-view-field high-precision monitoring method and system, and relates to the technical field of real-time monitoring. The detection method combines a machine vision technology and a DIC technology based on deep learning to optimize a monitoring process, can perform high-precision deformation monitoring on multiple points of a large view field, and is suitable for deformation monitoring of reservoir dam abutment rock mass; before detection, a convolutional neural network is used to carry out defogging operation and intelligent analysis on a surface image of a to-be-detected area, a key target area is automatically identified, and errors caused by manual intervention are effectively avoided; after the target area is determined, displacement field distribution of the target area is calculated by adopting a digital image correlation algorithm based on deep learning, and deformation measurement with sub-pixel-level precision is realized; through fusion of deep learning and a traditional image processing technology, the influence of manual parameter setting is reduced, the problem of decorrelation during matching is solved, and the precision and reliability of displacement calculation are effectively improved.

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 provides an OTFS-based secret key generation method and system, and relates to the field of physical layer security, and the method comprises the steps that based on multiple rounds of channel detection between a master node and a slave node, the two nodes respectively execute the following operations by using respective received signals: based on the received signals, channel estimation is performed, and by using a channel estimation result, a secret key is generated; estimating a channel state information vector of the delay Doppler domain; performing decorrelation transformation on the estimated channel state information vector; and mapping the channel state information vector subjected to decorrelation transformation into a corresponding quantization interval, dynamically generating a coding index by adopting a self-adaptive index adjustment mechanism according to an index of the quantization interval, extracting high-order bits from a Gray code corresponding to the coding index, and generating a local shared key. According to the method, OTFS modulation and demodulation are used for physical layer key generation, autocorrelation caused by OTFS is solved through decorrelation transformation, and the efficiency, robustness and consistency of key generation in a mobile communication scene are 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 invention discloses a rope free end take-up and pay-off speed estimation method based on multi-sensor fusion, and belongs to the technical field of information physical systems. In order to solve the problem that real-time and accurate speed and position estimation is carried out in a mode of fusing an accelerometer and other sensors mounted at the winding end, the method comprises the following steps of: constructing a kinematic model by using an angle measurement sensor based on the winding end or the fixed end of the steel wire rope, and constructing a kinematic model by using a speed measurement sensor based on the winding end or the fixed end of the steel wire rope; performing integration to obtain a state equation model of the system, discretizing the state equation model of the system, introducing process noise, performing process noise and observation noise decorrelation processing on the obtained state equation model of the system introduced with the process noise, and obtaining a decorrelated state equation model; and designing a steady-state Kalman filtering algorithm by using the obtained decorrelated state equation model, wherein the steady-state Kalman filtering algorithm is used for estimating the winding and unwinding speed of the free end of the rope based on multi-sensor fusion. The method is accurate in estimation.

A method, system and apparatus are disclosed. A UE (22) is provided. The UE (22) configured to: determine at least one reference signal measurement and assistance information that is associated with the at least one reference signal measurement where the assistance information comprising at least one of: a probability of a line of sight, LOS, channel being reported by the UE (22); a decorrelation rate of measurements; a variation of a strongest beam of a plurality of measured beams; a number of different beam directions; channel impulse response information; an interference level experienced by the UE (22); UE rotational speed information; or information associated with receiver beam gain. The UE (22) is configured to transmit the at least one reference signal measurement and the assistance information to the network node (16).

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.

A multi-input, multi-output audio processing is implemented as a linear system for use in an audio filter bank to convert a set of frequency-domain input audio signals into a set of frequency-domain output audio signals. The transfer function from one input to one output is defined as a frequency-dependent gain function. In some implementations, the transfer function includes a direct component that is substantially defined as a frequency-dependent gain and one or more decorrelating components having a frequency-varying group phase response. The transfer function is formed by a set of sub-band functions, where each sub-band function is formed by a set of corresponding component transfer functions that include the direct component and one or more decorrelating components.

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.