12 results about "Matrix inverse" patented technology

The invention discloses a single-epoch GNSS (Global Navigation Satellite System) double-difference parameter conversion method for any main satellites, which relates to the technical field of satellite navigation and positioning and comprises the following steps of: constructing a main satellite conversion matrix, a double-difference observed quantity sequence conversion matrix and an inverse matrix thereof between any two main satellites based on a single-epoch single-frequency single-system GNSS double-difference mathematical model; the method comprises the following steps: establishing a single-epoch multi-frequency multi-system main satellite transformation matrix with inverse transformation invariance and orthogonality, obtaining the invariance and orthogonality of matrix inverse transformation, constructing a single-epoch multi-frequency multi-system main satellite transformation matrix with inverse transformation invariance and orthogonality, a double-difference observed quantity sequence transformation matrix with inverse transformation invariance and orthogonality and an inverse matrix of the double-difference observed quantity sequence transformation matrix by establishing a single-epoch multi-frequency multi-system double-difference mathematical model and analogy derivation, and establishing a single-epoch multi-frequency multi-system and constructing a single-epoch GNSS double-difference model parameter and estimation parameter conversion and inverse transformation formula between any two or two groups of main satellites, and performing single-epoch double-difference parameter conversion.

The invention belongs to the field of metasurface electromagnetic signal processing, and particularly relates to a deep learning aided design-based metasurface two-dimensional high-resolution signal source positioning method. The super-surface two-dimensional high-resolution signal source positioning method based on deep learning aided design comprises a matched filtering algorithm and an image denoising algorithm. The method comprises the following steps: firstly, performing principle analysis and mathematical modeling on a metasurface two-dimensional signal source positioning function based on a ray tracing method and metasurface physical parameters to obtain a matrix equation; secondly, performing matrix inverse operation on the equality by adopting a matched filtering algorithm, preliminarily estimating two-dimensional position information of the signal source, and outputting the two-dimensional position information in an image form; and finally, inputting image information into the image denoising deep neural network by adopting an image denoising algorithm, and finally realizing two-dimensional high-resolution signal source positioning. According to the high-resolution signal source positioning method, multiple times of simulation and experiments are carried out on the basis of the two-dimensional gradient programmable metasurface platform, and a large number of data results prove that the method has the advantages of high resolution, low complexity and the like.

The invention provides an ISAC system signal detection method based on block diagonal expected propagation, and the method comprises the steps: obtaining a communication signal and a target echo signal transmitted by multi-antenna user equipment through a receiving end, carrying out the whitening of the received signal and noise, and minimizing the interference of a radar to communication; converting the optimized complex signal into a real value system model; initializing a mean vector and a covariance matrix parameter of the expectation propagation algorithm, and setting the number of iterations; calculating diagonal elements of the covariance matrix by adopting a block diagonal Neumann series approximation method; updating a mean vector and adjusting an iteration step length through a dynamic residual factor; and after a preset number of iterations, outputting a final detection signal. According to the method, the complexity is reduced by calculating the diagonal elements of the matrix inversion instead of directly solving the matrix inversion, and a special averaging method is designed for the diagonalization characteristic of the matrix with the similar channel hardening characteristic to optimize the precision.

An electric-gas coupling system quasi-steady-state simulation method, device and computer readable medium based on branch compensation method. It relates to the improvement of the simulation method of the electric-gas coupling system. It is suitable for occasions with high real-time requirements and can realize fast approximate quasi-dynamic energy flow calculation. It includes the following steps: 1) in the natural gas system, the "circuit-like" method is used to model the natural gas pipeline in a steady state; 2) using the matrix inverse auxiliary theorem, the node pressure is calculated without considering the change of the gas resistance of each pipeline; 3) calculating the branch flow without considering the change of the gas resistance of each pipeline; 4) calculating the node gas pressure considering the change of the gas resistance of each pipeline. The present application extends the branch compensation method to the natural gas system and is suitable for comprehensive modeling, quasi-steady-state simulation and many other scenes of the electric-gas coupling system. When the branch connection condition changes locally, the node admittance matrix is not recalculated, but an approximate result in the new scene is given based on the original calculation result by using the correction method.

The present invention discloses a single-epoch GNSS double-difference parameter conversion method for any master satellite, relating to the field of satellite navigation and positioning technology. The method comprises: constructing a master satellite conversion matrix and a double-difference observation quantity sequential transformation matrix and their inverse matrices between any two master satellites based on a single-epoch single-frequency single-system GNSS double-difference mathematical model, and obtaining the invariance and orthogonality of the inverse transformation of the matrix; constructing a single-epoch multi-frequency multi-system master satellite conversion matrix and a double-difference observation quantity sequential transformation matrix and their inverse matrices with inverse transformation invariance and orthogonality by establishing a single-epoch multi-frequency multi-system double-difference mathematical model and analogical deduction; constructing a single-epoch GNSS double-difference model parameter and estimated parameter conversion and inverse transformation formulas between any two or two groups of master satellites based on the above matrices and properties; and performing single-epoch double-difference parameter conversion.

The application provides an ISAC system signal detection method based on block diagonal expectation propagation, wherein a communication signal and a target echo signal sent by a multi-antenna user equipment are acquired by a receiving end, the received signals are subjected to noise whitening processing, and interference of radar on communication is minimized; the optimized complex signals are converted into real value system models; mean vector and covariance matrix parameters of an expectation propagation algorithm are initialized, and an iteration number is set; diagonal line elements of the covariance matrix are calculated by using a block diagonal Neumann series approximation method; the mean vector is updated, and an iteration step is adjusted by using a dynamic residual factor; and finally, a final detection signal is output after a preset number of iterations. The diagonal line elements of the matrix inverse are calculated to replace direct solution of the matrix inverse, so that the complexity is reduced, and a special mean calculation method is designed for the matrix diagonalization characteristics with similar channel hardening characteristics, so that the precision is optimized.

The present application relates to power distribution network technical field, specifically to a kind of power distribution network modeling method based on shallow physical information neural network, comprising the following steps: S1, constructing modeling base model: establishing power flow model of distribution network, while using non-negative weight and ReLU activation function, ICNN network is constructed;S2, ICNN-based distribution network topological structure modeling: the weight of ICNN network is discretized by clustering method, the inverse of branch association matrix is estimated and its inverse matrix is solved, so that the topological structure of distribution network is obtained by inversion;S3, ICNN-based distribution network line parameter modeling: the line resistance and reactance diagonal matrix are estimated by ICNN network, and a regularization term is introduced for optimization, to realize the inversion modeling of distribution network line parameters;The present application realizes the joint inversion of distribution network structure and parameter, significantly improves the practicability and robustness of modeling.

The application discloses a power amplifier DPD coefficient estimation method based on an RLS algorithm, obtains an input signal of an input power amplifier (PA) and a feedback output signal after gain adjustment; performs time delay alignment processing on the input signal and the feedback signal; based on a memory polynomial model and a memory polynomial model of cross terms, constructs a nonlinear input matrix and a coefficient matrix of the PA; the recursive least square (RLS) algorithm based on Givens rotation of complex QR decomposition is adopted, a CORDIC algorithm is used to solve a rotation angle and a modulus value, the nonlinear input matrix and the coefficient matrix are iteratively calculated, and DPD coefficients are estimated. The memory polynomial model or the memory polynomial model of cross terms is adopted, so that the PA model is clearer, and data processing is facilitated; the RLS algorithm adopts the RLS expression based on Givens rotation of complex QR decomposition, direct solution of a matrix inverse is not needed, a large number of division operations are avoided, and the problem that the original RLS algorithm is not conducive to engineering implementation in DPD coefficient estimation is solved.

The invention discloses a rapid prediction method and system for an axial force load of a variable cross-section beam. The method comprises the following steps: 1) establishing a coupling dynamics differential equation and corresponding boundary conditions of the variable cross-section beam under the action of an axial force; 2) performing spatial discretization processing through a differential quadrature method; (3) geometric parameters and material parameters of the target variable cross-section beam and actually-measured inherent frequency values of the first m orders are obtained; and 4) resolving the value and direction of the axial force of the variable cross-section beam in real time by using the adjoint matrix inverse operation. According to the method, a dynamic prediction scheme based on the Tiangshencaro beam theory is provided, a frequency inversion mapping mechanism is adopted in a breakthrough mode, and rapid prediction of the axial tension / pressure under the variable cross-section beam condition is achieved. Meanwhile, the system can be integrated on equipment such as a bridge cable monitoring terminal and an aero-engine blade load analyzer, and the problem of real-time force measurement of a complex variable cross-section beam structure is effectively solved.

The application discloses a kind of matrix inverse-free ISAR imaging methods based on gamma process-Laplacian prior, mainly solve the problem of two-dimensional reconstruction accuracy not high, long operation time in prior art.It is implementation scheme: receiving defective echo and generating echo matrix;According to defective echo matrix, obtain real Fourier dictionary Φ;According to echo matrix and real Fourier dictionary, the sparse observation model y of each distance unit is constructed q =Φω q +ε;Based on sparse observation model, the weight vector ω of each distance unit q Gamma process-Laplacian hierarchical prior is introduced;Gamma-Gaussian hierarchical prior is introduced to noise vector ε;Using matrix inverse-free fast inference method iteratively solves the weight vector of each distance unit;According to the obtained weight vector, two-dimensional high-resolution image is obtained.The reconstruction accuracy of the application is high, the operation time is short, and can be used for feature extraction and classification identification of space and air non-cooperative target under complex electromagnetic environment such as target echo low signal-to-noise ratio and existence defect.

A communication method and a communication device, the communication method comprising: a first communication device acquiring a signal represented by a 2 M M number of elements, M being an integer greater than or equal to 2, and transmitting the signal to a second communication device through at least one antenna group, each antenna group comprising antennas corresponding to different spatial dimensions, implementing transmission of the signal represented by 2 M M number of elements. Specifically, the algebraic properties of the 2 M M number of elements include a conjugate operation instead of a matrix inverse operation, compared to a scheme in which a signal is represented by a complex number, the technical solution can reduce the processing complexity of the signal to a certain extent by representing the signal by a hypercomplex number.