39 results about "System matrix" patented technology

The invention belongs to the technical field of magnetic particle imaging, relates to a magnetic particle imaging reconstruction method based on a calibration magnetic field generation system matrix, and aims to solve the problems that a traditional magnetic particle imaging reconstruction method is poor in applicability in asymmetric bilateral structure magnetic particle imaging equipment (A-MPI) and cannot perform imaging in any region. The method comprises the following steps: performing grid division on an imaging area, calibrating magnetic field intensity, and obtaining magnetic field gradient distribution of each point; obtaining a theoretical system matrix according to a mathematical calculation mode; randomly moving the positions of the non-magnetic field points for scanning to obtain actually measured magnetic field gradient distribution and a system matrix, and constructing a data set; expanding the data set based on the simulation system; constructing a deep learning model, and inputting the extended data set and the measured data into the training deep learning model; and inputting a theoretical system matrix at any position, and obtaining an accurate system matrix by using the trained model. According to the invention, the system matrix at any position can be obtained under the A-MPI equipment, so that imaging at any position is realized.

The invention relates to a load flow sparse equation set matrix parallel hierarchical elimination tree calculation method and device, and the method comprises the steps: starting to search a sub-matrix from a topmost layer node and a bottommost layer node in a Jacobian matrix optimal block division set, and calculating a local sub-tree of the sub-matrix; combining the obtained local sub-trees of the sub-matrixes to obtain a blocked local elimination tree; matching the obtained local elimination trees of the blocks according to a node connection relationship to obtain a matching relationship of the local elimination trees of the blocks; and merging the local elimination trees of the matched blocks to obtain a parallel hierarchical elimination tree of the original Jacobian matrix. According to the method, the calculation time of the matrix parallel hierarchical elimination tree is shortened, and the load flow calculation effectiveness is improved.

The invention relates to the technical field of data processing, in particular to a structure dynamic stiffness analysis method based on frequency response function polycondensation substructure impedance coupling, which comprises the following steps: acquiring node information, unit connection relation and material attribute based on a global finite element model; defining a focus point set, a boundary point set and an internal point set according to the unit connection relationship; partitioning the global quality matrix, the stiffness matrix and the damping matrix to obtain a partitioned system matrix; introducing an inertia compensation term to construct a transformation matrix based on the block system matrix and the highest analysis frequency of the system, condensing the system matrix until only the freedom degrees of a concern set and a boundary point set are reserved, and calculating a dynamic stiffness matrix in a frequency domain; a dynamic stiffness result of a focus set is extracted through inverse operation of a dynamic stiffness matrix, the calculation scale is remarkably reduced through system matrix condensation, meanwhile, the inertia effect and the stiffness coupling effect of a far-field structure are strictly reserved, and the contradiction between low calculation efficiency of a global model and precision distortion of a local substructure method is effectively solved.

The present invention belongs to the field of computational electromagnetics and provides a multi-state simulation method for a reconfigurable intelligent surface to achieve the purpose of shortening the calculation time and reducing the memory consumption. First, obtain the unit model of the reconfigurable intelligent surface, expand the unit model to form a 3×3 characteristic sub-unit basic array, and regard it as an invariant geometric structure item, and regard the two-dimensional equivalent circuit model as a variable state description item. Then, extract the characteristics of the invariant geometric structure item and the variable state description item to obtain the system matrix of the reconfigurable intelligent surface and construct a system equation. Finally, solve the system equation to obtain the unknown electromagnetic field quantities to be solved, so as to calculate the electromagnetic characteristics of the reconfigurable intelligent surface and complete the multi-state simulation of the reconfigurable intelligent surface. The present invention effectively optimizes the repeated calculation part in the multi-state simulation process of the reconfigurable intelligent surface, significantly reduces the memory consumption, and greatly shortens the simulation time under the condition of ensuring the solution accuracy.

The invention discloses a meshless Galerkin-Newmark method for calculating a transient wave propagation problem. The meshless Galerkin-Newmark method comprises the following steps: dispersing a transient wave propagation problem domain into nodes; selecting an interpolation primary function and a weight function; constructing a node interpolation primary function and a global interpolation format by adopting a moving least square method based on the selected function; based on a global interpolation format, combining a partial differential control equation and a Galerkin weighted residual value method to obtain a transient wave propagation problem system matrix equation; performing time domain discretization through a Newmark time integration method to obtain a discrete time equation; solving the discrete time equation to obtain a numerical calculation result; and analyzing a result and comparing the result with a common method to finish solving and analyzing a transient wave propagation problem. The meshless Galerkin-Newmark method for calculating the transient wave propagation problem has a monotonous consistent convergence characteristic in the numerical calculation of the transient wave propagation problem, and the calculation precision can be continuously improved along with the reduction of the time integral step length.

The invention discloses a rapid calculation method and device for the sensitivity of a linear periodic time-varying system based on a matrix sparse technology, and belongs to the technical field of modeling analysis of the linear periodic time-varying system.The rapid calculation method comprises the steps that an LTP system is converted into an equivalent LTI system, and the eigenvalue, the left eigenvector and the right eigenvector of the LTP system are obtained; based on a functional derivative method, obtaining a sensitivity analytical expression of the LTP system characteristic value to the parameter; according to the influence mechanism of the parameters on the system matrix, obtaining an analysis form of the influence of the parameters on the LTP system matrix in the sensitivity analysis expression; and converting a partial derivative of a system matrix to a steady-state trajectory into sparse calculation of a vector field Hessian matrix by using a matrix sparse technology, thereby obtaining a calculation result of the characteristic value sensitivity of the LTP system. According to the method, the sparse characteristic of the system matrix in the PEPS is utilized, the calculated amount and the storage requirement of the system matrix on trajectory partial derivative solving are reduced, and therefore calculation of the LTP characteristic value sensitivity is accelerated.

In order to overcome the problem that the current technology is difficult to estimate and continuously correct the bridge twin model by obtaining a series of test and test data, the application provides a bridge twin dynamic model Fourier modeling method based on test data, which is only related to the parameters of the bridge according to the system matrix related to all nodes of the bridge and the observation coefficient matrix related to all nodes, and the first continuous test process of the bridge does not change greatly, and the first comprehensive detection of the bridge twin dynamic mathematical model and the subsequent each time of the bridge twin dynamic mathematical model comprehensive correction process is relatively short, according to the characteristics of the fast and slow change matrix, the slow change matrix is set as a constant matrix in the first continuous test, and the system matrix related to all nodes of the bridge and the observation coefficient matrix related to all nodes in the bridge twin model are established through a series of effective tests and optimal indexes, and the bridge twin model is continuously corrected in the whole life cycle of the bridge, so that the technical problem of estimating and improving the bridge vibration model by obtaining a series of test and test data is solved.

The application discloses an enhanced mobile least square meshless-Newmark integral method for reducing total dispersion error of transient wave propagation, and belongs to the technical field of numerical analysis and total dispersion error prediction of transient wave propagation, and comprises the following contents: a wave propagation problem domain is discretized into a series of nodes; a standard mobile least square interpolation base function of each node is derived; a local numerical approximation of an enhanced least square algorithm is completed; a global interpolation format of a general scalar field based on the enhanced least square algorithm is constructed; a system matrix equation of the dispersion analysis of the transient wave propagation problem is obtained by adopting a Galerkin weighted residual method and a Newmark time integral method; and based on a given node distribution, the total dispersion error of different calculation methods along different wave propagation directions under different time integral step lengths is calculated. The application adopts the above method, reduces the total dispersion error caused by the coupling of spatial dispersion and time dispersion, and improves the solving precision.

The present invention belongs to the field of magnetic particle imaging, specifically to a generative reconstruction method for magnetic particle imaging based on physical priors. This method aims to address the issues of long matrix calibration time for magnetic particle imaging systems, reliance on model assumptions in mathematical modeling methods, and difficulty balancing acceleration performance and recovery accuracy in acceleration-based calibration methods, which in turn lead to low accuracy in reconstructed MPI images. The method comprises: constructing a system matrix containing physical priors; splitting the system matrix by column to obtain a set of system matrix columns as the original system matrix columns; inputting the original system matrix columns and various physical priors into a potential diffusion model based on physical priors for fine-tuning and training; inputting newly measured physical priors into the trained model to obtain generated system matrix columns, thereby forming a complete system matrix. The method then combines the measured signals to solve ill-conditioned equations and obtain an MPI image of the object to be measured. The present invention improves the accuracy of MPI image reconstruction while eliminating the need to calibrate the system matrix.

The invention discloses a mode identification method based on an unsupervised optimization covariance random subspace method. The method comprises the following steps: arranging a vibration sensor on a to-be-detected structure with noise interference or a weak excitation mode to obtain a structure dynamic response; constructing a Hankel matrix, calculating a covariance matrix Ri, and constructing a Toeplitz matrix based on the Ri; calculating an extended observable matrix Oi and an extended controllable matrix Gamma i based on the weighted Toeplitz matrix; defining the range of the row block number i and the model order N of the Toeplitz matrix; analyzing the sensitivity of the row block number i of the Toeplitz matrix and the model order N based on a parameter optimization index kP (i, N); the singular entropy increment of the weighted Toeplitz matrix T1i is calculated; calculating the singular entropy increment curvature of the weighted Toeplitz matrix T1i, and determining a critical model order Nc (i); calculating an accumulated parameter optimization index kappa P value from a minimum model order Nmin to a critical model order Nc (i) under the condition of different Toeplitz matrix row block numbers i; selecting a parameter combination {iopt, Nopt} corresponding to the minimum parameter as an optimal parameter; identifying a system matrix and determining modal parameters, and drawing an original stability diagram; and on the basis of DBSCAN clustering, automatically identifying each order of physical modality from candidate modalities containing noise interference. A corresponding system is also disclosed.

The present invention discloses a method and system for analyzing electromagnetic scattering characteristics of metal targets based on a hybrid nested equivalent source direct solver. Specifically, the method comprises the following steps: establishing a target equivalent surface current model to be solved, and dividing the global basis functions to be solved corresponding to the model into multiple groups in different spatial regions; constructing an elimination matrix for the far-field coupling matrix blocks for each group to compress and eliminate the admissible blocks; eliminating the inadmissible blocks by calculating the Schur complement of the remaining inadmissible matrix blocks; compressing the fill-in matrix blocks added to the admissible blocks, extracting their column vectors and adding them to the orthogonalized receiving matrix of the next group; skipping the remaining decomposition process of the group in the event of overflow caused by matrix addition or translation from a sublayer to a parent layer; and sequentially traversing each layer and group to solve the system matrix equation, ultimately obtaining the electromagnetic scattering characteristics of the target, such as the radar cross-section. The method has high computational efficiency and lower memory requirements.

This invention discloses a method and system for extracting S-parameters of microwave passive devices, comprising: geometrically modeling the microwave passive device and then meshing it to obtain a processed device model; discretizing the processed device model according to basis functions, and performing mode function expansion on the ports of the processed device model to establish a transfinite element matrix equation; performing partial LU decomposition of the system matrix in the transfinite element matrix equation using the multi-wavefront method to obtain the Schur complement matrix of the system matrix and the decomposed system matrix; obtaining the dense S-parameter matrix equation for the microwave passive device based on the Schur complement matrix of the system matrix and the decomposed system matrix; and solving the dense S-parameter matrix equation to obtain the S-parameters of the microwave passive device. This invention effectively reduces the memory usage of matrix calculations and reduces computation time.

The invention belongs to the field of magnetic particle imaging, particularly relates to a magnetic particle imaging generative reconstruction method based on physical prior, and aims to solve the problems that a magnetic particle imaging system is long in matrix calibration time, depends on model hypothesis based on a mathematical modeling method, and is difficult to balance acceleration performance and recovery precision based on an acceleration calibration method. Therefore, the problem of low precision of the reconstructed MPI image is solved. The method comprises the following steps: constructing a system matrix containing physical prior; splitting the system matrix according to columns to obtain a group of system matrix columns as original system matrix columns; inputting the original system matrix array and each physical priori into a potential diffusion model based on the physical priori, and performing fine tuning and training; and inputting each newly measured physical priori into the trained model to obtain a generated system matrix array, forming a complete system matrix, and further combining a measurement signal to solve an ill-conditioned equation to obtain an MPI image of the to-be-measured object. According to the method, the MPI image reconstruction precision is improved, and a system matrix does not need to be calibrated.

The invention discloses an enhanced moving least square algorithm for reducing frequency dispersion errors of wave propagation analysis, which comprises the following steps of: dispersing a wave propagation problem domain into nodes, and constructing an interpolation primary function of the nodes based on a standard moving least square algorithm; constructing local strengthening numerical approximation containing a local strengthening primary function and a coefficient at the node; constructing a global interpolation format of a general scalar field based on an enhanced moving least square algorithm on the premise of meeting unit decomposition characteristics; and obtaining a system matrix equation for frequency dispersion analysis of the wave propagation problem by using the constructed enhanced global interpolation format, combining with a partial differential control equation of the wave propagation problem and adopting a Galerkin weighted residual value method, and further calculating to obtain a frequency dispersion error of the wave propagation problem. According to the enhanced moving least square algorithm for reducing the frequency dispersion error of the wave propagation analysis, the frequency dispersion error can be obviously reduced during frequency dispersion analysis, so that a more accurate numerical result can be obtained during wave propagation problem analysis.

The application discloses an estimation method of an unknown failure tumbling target angular velocity based on an electromagnetic induction torque, which is composed of the following steps: obtaining historical data of the unknown failure tumbling target, wherein the historical data comprises angular velocity historical data and electromagnetic induction torque historical data; performing dimension increasing on the historical data through nonlinear transformation to obtain dimension-increased data; performing dynamic mode decomposition on the dimension-increased data to obtain a system matrix, an output matrix and a prediction matrix; constructing a linear predictor model of the unknown failure tumbling target in the electromagnetic despinning process according to the system matrix, the output matrix and the prediction matrix; and solving the linear predictor model as a constraint condition of an optimal estimation problem to obtain a real-time accurate estimation value of the angular velocity of the unknown failure tumbling target. In the electromagnetic despinning process of a close-range space target, the application realizes real-time accurate estimation of the target angular velocity by using electromagnetic despinning torque data, thereby solving the problem that the target angular velocity is difficult to measure in a close-range despinning task.

To overcome the current technical problems of difficulty in analyzing the causes of bridge anomalies and the inability to actively prevent bridge resonance, this invention provides a Fourier method for anomaly reproduction and resonance prevention based on a bridge twin dynamic model. This method relies on the fact that the system matrix related to all bridge nodes and the observation coefficient matrix related to nodes are only related to the bridge parameters and do not change significantly during a single continuous bridge test. The reproduction of bridge anomalies or the simulation of bridge resonance and abnormal loading tests are relatively short. Based on the characteristics of slowly changing matrices, a singular perturbation method is used to set the slowly changing matrix as a constant matrix in a single continuous test. Fourier series approximation is used to approximate the fast-changing variable over time, obtaining the ambiguous excitation input when bridge anomalies occur. The system's reproduction of anomalies is verified through equivalent bridge simulation; thus, the artificial excitation input for simulating bridge resonance or anomalies is obtained, solving the technical problems of difficulty in analyzing the causes of bridge anomalies and the inability to actively prevent bridge resonance.

The present invention relates to the field of multi-agent consensus control, and specifically provides an event-driven control design method applicable to multi-agent systems with saturated inputs, which is characterized by including the following steps: for agents with saturated inputs, construct the state-space model of each agent and give the assumption conditions that the system matrix needs to satisfy; based on the multi-agent system model established in step 1, design a control law that can make the system reach consensus; design an appropriate low feedback gain to optimize the non-linear agent model into a linear model; use the Lyapunov function method to prove the consensus of the event-driven control law. The present invention can optimize it into a linear system by using the low-gain technology based on the algebraic Riccati equation, reducing the dependence; the present invention can effectively reduce the number of control law updates on the basis of completing the consensus control task, saving resources; the present invention can effectively avoid the Zeno phenomenon.

Method for compensating for undesired power oscillations propagating throughout a power grid, the method comprising: obtaining phasor angle measurements of an electrical metric characterising said undesired power oscillations at consecutive time instances; determining, based on the measurements, a system matrix; performing an eigenvalue decomposition of the system matrix, thereby obtaining complex eigenvectors and complex eigenvalues; selecting a dominant eigenvalue associated to an undesired power oscillation and a corresponding dominant eigenvector; identifying two furthest entries in the dominant eigenvector having a largest difference of arguments among all entries in the dominant eigenvector; projecting entries of the dominant eigenvector in a complex plane along directions defined by the furthest entries, resulting in a projected eigenvector having complex projected entries, characterising compensating phase angles of the undesired power oscillation; determining, in the power grid, respective time delays from the compensating phase angles for compensation of the undesired power oscillation.

The application discloses a smooth finite element-Newmark calculation method for underwater target transient acoustic scattering, and belongs to the technical field of underwater transient acoustic scattering numerical simulation. First, a calculation domain of an underwater transient acoustic scattering field is discretized into a standard quadrilateral element grid, and an acoustic pressure field interpolation format is constructed. The quadrilateral element is divided into multiple smooth domains, a smooth acoustic pressure gradient field is obtained through acoustic generalized gradient smoothing technology, and a smooth acoustic pressure gradient matrix is obtained through Gaussian integration. A system matrix equation is constructed in combination with a transient acoustic scattering control equation and a Galerkin weighted residual value method. A parameter-optimized Newmark time integration method is used to complete time domain discretization and recursive solving, and numerical results of the transient acoustic scattering field are obtained. The application softens the system stiffness matrix through gradient smoothing technology, reduces spatial discretization error, eliminates time domain false numerical damping, and has higher precision than the standard finite element method under the same grid, thereby providing an efficient and reliable scheme for underwater transient acoustic scattering engineering calculation.

The present invention discloses an application of a high-precision enhanced radial point interpolation gridless calculation method in computational acoustic problems, which relates to the application of grid calculation methods in the field of computational acoustic problems. First, the wave propagation problem domain is discretized into a series of scattered points, and the interpolation format of the general scalar field is constructed based on the radial basis function, and each scattered point interpolation basis function is derived; in order to improve the interpolation accuracy of the obtained interpolation format, a new node degree of freedom is constructed at each scattered point, and the node degree of freedom is a local numerical approximation composed of a local enhanced interpolation basis function and a coefficient to be determined. Based on the obtained local numerical approximation, a global interpolation format of the general scalar field is constructed under the premise of satisfying the unit decomposition characteristics. The final discrete system matrix equation is obtained, and the matrix equation is solved to obtain the sound pressure of any point within the entire acoustic problem calculation domain. The present invention realizes high-order interpolation without increasing unit nodes, which can reduce numerical calculation errors.

The invention relates to a coil topology design method and device based on magnetic field reverse reconstruction, computer equipment, a computer readable storage medium and a computer program product, relates to the technical field of electromagnetic engineering and wireless power transmission, and can improve the robustness of coil design. The method comprises the following steps: acquiring a target magnetic field distribution vector of a coil in a target area, and determining a spatial weighting matrix according to spatial position distribution; constructing a primary function dictionary of the stream function; performing weighting processing on the physical mapping matrix and the target magnetic field distribution vector by using a space weighting matrix to obtain a weighting system matrix and a weighting magnetic field vector; performing truncation singular value decomposition on the weighted system matrix to obtain a truncation result, and determining a target weight coefficient of the primary function dictionary based on the truncation result and the weighted magnetic field vector; and reconstructing stream function distribution on the extended computational domain based on the primary function dictionary and the target weight coefficient, and determining a geometric topology path of the coil according to the stream function distribution.

This invention discloses a method, system, and medium for determining the stability of a linear periodic time-varying system based on a harmonic state-space model, belonging to the field of linear system dynamics analysis. The method includes: constructing harmonic state-space models M with high truncation order H and low truncation order L for the system, respectively. H M L ; Calculate M L The first eigenvalue and the first eigenvector; for M H Arrange its state variables in the order of to transform them; calculate M under the first eigenvalue. L The system matrix relative to the transformed M H The deviation of the system matrix is ​​used to obtain the deviation matrix; the eigenvalue deviations are calculated based on the deviation matrix and the first eigenvector; the sum of the eigenvalue deviations and the first eigenvalue is calculated to obtain M. H The second eigenvalue is used to determine the stability of the linear periodic time-varying system. This approach ensures the accuracy of eigenvalue calculation while improving computational efficiency, thus enhancing the applicability of the harmonic state-space model to large-scale systems.

This invention discloses a smoothed finite element adjustable damping implicit integral algorithm for underwater transient acoustic scattering, belonging to the field of underwater transient acoustic scattering numerical simulation technology. First, the computational domain of the underwater transient acoustic scattering field is discretized into a standard quadrilateral element mesh to construct an interpolation scheme for the sound pressure field. Then, each quadrilateral element is divided into multiple smooth domains, and the smoothed sound pressure gradient matrix is ​​obtained through acoustic generalized gradient smoothing technology. Combining differential control equations, the virtual displacement principle, and the Galerkin weighted residual method, the system matrix equation is constructed. An adjustable damping implicit time integral algorithm is used to complete the time-domain discretization, and the numerical results of the transient acoustic scattering field in the entire time domain are obtained through recursive solution. This invention can soften the "overly stiff" stiffness matrix to reduce spatial discretization errors, suppress high-frequency errors through adjustable numerical damping matching, and achieve coordinated control of spatiotemporal errors. Under the same mesh, its accuracy is superior to the standard finite element method, providing an efficient and reliable solution for underwater transient acoustic scattering engineering simulation.

The invention discloses an enhanced meshless Galerkin algorithm for reducing the frequency dispersion error of wave propagation analysis, which comprises the following steps: dispersing a wave propagation problem domain into nodes, selecting an interpolation primary function and a weight function, constructing an approximate interpolation function based on a standard meshless Galerkin algorithm, determining an undetermined coefficient through least square fitting, and determining the frequency dispersion error of the wave propagation analysis. Further establishing a physical field global interpolation format; constructing local reinforcement numerical approximation containing a local reinforcement interpolation primary function and a coefficient at the node; constructing a global interpolation format based on an enhanced meshless Galerkin algorithm on the basis of local enhanced numerical approximation under the condition of meeting unit decomposition characteristics; and an obtained global interpolation format is combined with a wave propagation problem partial differential control equation and a Galerkin weighted residual value method to obtain a system matrix equation which is used for frequency dispersion error analysis of the wave propagation problem. By adopting the enhanced meshless Galerkin algorithm for reducing the frequency dispersion error of wave propagation analysis, the frequency dispersion error can be remarkably reduced, and a more accurate numerical calculation result can be obtained.

The invention discloses a linear periodic time-varying system stability judgment method and system based on a harmonic state space model and a medium, and belongs to the field of linear system dynamics analysis, and the method comprises the steps: respectively constructing harmonic state space models MH and ML with a high truncation order H and a low truncation order L for the system; calculating a first characteristic value and a first characteristic vector of ML; for the MH, arranging state variables of the MH according to the sequence of # imgabs0 # so as to transform the MH; calculating the deviation of the system matrix of the ML under the first characteristic value relative to the system matrix of the transformed MH to obtain a deviation matrix; calculating a characteristic value deviation according to the deviation matrix and the first characteristic vector, and calculating the sum of the characteristic value deviation and the first characteristic value to obtain a second characteristic value of the MH; and determining the stability of the linear period time-varying system according to the second characteristic value. The calculation efficiency is improved while the characteristic value calculation accuracy is ensured, and the applicability of the harmonic state space model to a large-scale system is enhanced.

The present application relates to the technical field of data processing, and more particularly to a structure dynamic stiffness analysis method based on frequency response function condensation substructure impedance coupling, comprising: obtaining node information, element connection relationship and material properties based on a global finite element model; defining a focus point set, a boundary point set and an internal point set according to the element connection relationship; obtaining block system matrices by blocking the global mass matrix, the stiffness matrix and the damping matrix; introducing an inertia compensation term to construct a transformation matrix based on the block system matrices and the highest analysis frequency of the system, condensing the system matrix to only retain the degrees of freedom of the focus point set and the boundary point set, and calculating the dynamic stiffness matrix in the frequency domain; and extracting the dynamic stiffness results of the focus point set by inverting the dynamic stiffness matrix, which significantly reduces the calculation scale through system matrix condensation, while strictly retaining the inertia effect and stiffness coupling effect of the far-field structure, effectively solving the contradiction between the low computational efficiency of the global model and the precision distortion of the local substructure method.

The invention belongs to the field of computational electromagnetism, and provides a multi-state simulation method for a reconfigurable intelligent surface, which is used for achieving the purposes of shortening calculation time and reducing memory consumption. The method comprises the steps that firstly, a unit model of the reconfigurable intelligent surface is obtained, the unit model is expanded to form a 3 * 3 feature subunit basic array, the basic array is regarded as an invariant geometric structure item, and a two-dimensional equivalent circuit model is regarded as a variable state description item; then, obtaining a system matrix of the reconfigurable intelligent surface through feature extraction of an invariant geometric structure item and a variable state description item, and constructing a system equation; and finally, solving the system equation to obtain the unknown quantity of the electromagnetic field to be solved, thereby calculating the electromagnetic characteristics of the reconfigurable intelligent surface and completing the multi-state simulation of the reconfigurable intelligent surface. According to the method, the repeated calculation part is effectively optimized in the multi-state simulation process of the reconfigurable intelligent surface, the memory consumption is remarkably reduced, and the simulation time is greatly shortened under the condition that the solving precision is guaranteed.

The invention discloses a load identification method and system based on singular value adaptive improved regularization, and relates to the technical field of aircraft dynamic load identification. The method comprises the steps that singular value decomposition is carried out on a pre-constructed system matrix, adjustment indexes corresponding to all orders are calculated according to singular value distribution characteristics, and the adjustment indexes are used for applying differential suppression intensity to singular values of different sizes; setting a range of regularization parameters, and screening to obtain an optimal regularization parameter by adopting a minimization criterion of a generalized cross validation GCV function; and carrying out load identification in combination with the adjustment index and the regularization parameter, constructing an improved regularization objective function, and solving the improved regularization objective function to obtain an optimal solution of load identification. According to the characteristic that singular values of different sizes have different influences on the stability of an identification result, differential suppression is carried out on the different singular values, the robustness of the model to small singular value disturbance and the fidelity of the model to main energy components are improved, and therefore the accuracy of ill-conditioned matrix inversion is improved.

A magnetic particle imaging (MPI) measurement method includes generating a multi-dimensional image-domain system matrix A using an MPI-sequence with a field free line, using a multi-dimensional sinogram-based system matrixASinogram(t,r,z)∈ℝ[T,Nr,Nz],comprising the following steps:for each time point tc, c∈[1, T]:get a time slice matrix Ac=ASinogram(t=tc, r, z)∈[N<sub2>r< / sub2>,N<sub2>z< / sub2>],replicate the time slice matrix Ac Nr−1 times and copying these replications along a newly added 2nd offset-dimension, resulting in a time volume matrixAc′∈ℝ[Nr,Nr,Nz],rotate the time volume matrixAc′ by the FFL θc=θ(t=tc) at time point t=tc in its 1st and 2nd offset-dimensions, resulting in a rotated matrixAcθ cconcatenate the rotated matricesAcθ c of all time points along a time-dimension and vectorize the spatial dimensions (x, y, z), resulting in a constructed system matrix cSM∈[T,(N<sub2>r< / sub2>×N<sub2>r< / sub2>×N<sub2>z< / sub2>)], andperform a Fourier transformation on the constructed system matrix cSM on its time-dimension resulting in the multi-dimensional image-domain system matrix A.

This invention relates to the field of geophysical exploration technology, specifically to a high-precision three-dimensional forward modeling method for airborne electromagnetic spectral elements considering induced polarization effects. Based on the Cole-Cole model, a complex conductivity expression considering induced polarization effects is established, and the frequency domain Helmholtz equation is introduced to construct the corresponding governing equations. A regular hexahedral mesh is generated, and reference domain vector basis functions are constructed using the Gauss-Lobatto-Legendre orthogonal polynomial method according to the spectral element method. The mapping relationship between these functions and physical mesh elements is established. The Galerkin weighted residual method is applied to discretize the governing equations into element system matrices, which are then assembled to form the overall system matrix and the corresponding linear equation set. A direct solver is used to obtain the frequency domain three-dimensional electromagnetic response, and the time domain three-dimensional forward modeling result of the computational region is obtained through Hankel transformation. This invention achieves rapid and high-precision three-dimensional forward modeling simulation of complex geological models containing induced polarization effects.