33 results about "Interpolation matrix" patented technology

The invention discloses an irregular grid seismic data reconstruction method based on deep learning, and belongs to the technical field of compressed sensing irregular grid seismic data reconstruction. In order to improve the quality of seismic data reconstruction, the method comprises the steps that a seismic data training set is generated, and each group of data in the seismic data training set comprises complete seismic data and two interpolation matrixes; an irregular convex set projection convolutional neural network is constructed, and the irregular convex set projection convolutional neural network is obtained by unfolding a loop structure of an irregular convex set projection method into a cascade structure and replacing original sparse transformation with a convolutional layer and an activation function; training the irregular convex set projection convolutional neural network by using the seismic data training set to obtain a trained irregular convex set projection convolutional neural network; and inputting acquired missing irregular grid seismic data and two interpolation matrixes calculated according to the irregular grid information into the trained irregular convex set projection convolutional neural network, and outputting reconstructed seismic data.

The invention discloses an order reduction method for aerodynamic reconstruction in a wallboard ground flutter simulation test, and relates to the technical field of aircraft design, and the method comprises the following steps: employing a hypothesis modal method to carry out spatial discretization on a wallboard structure of an aircraft, and obtaining a first expression; determining a second expression based on the intrinsic mode matrix; substituting the second expression into the first expression to obtain a third expression; substituting the second expression into the first aeroelastic equation to obtain a second aeroelastic equation under the intrinsic mode coordinates; physical aerodynamic force is determined based on the third expression and the second aeroelastic equation; the physical aerodynamic force is subjected to order reduction through the displacement interpolation matrix and the force interpolation matrix, and the physical aerodynamic force after order reduction is obtained. According to the method, the number of loading points is reduced, it is guaranteed that the limited number of loading points are equivalent to the distributed aerodynamic force, the method is not limited by the structure size, test implementation is facilitated, time domain fitting is not needed, and the calculation precision and efficiency are higher.

The invention discloses a geological mineral data intelligent modeling method and system based on multilevel space-time intrinsic coding, and the method comprises the steps: generating a 9-level adaptive grid through employing an improved HEALPix subdivision algorithm for the geological complexity and target data density of a to-be-detected region; based on a 9-level adaptive grid, encoding space time-varying grid units of existing geological mineral resource data to obtain a geological feature space matrix; constructing a multi-modal data register based on Transform, inputting the 9-level adaptive grid and the geologic feature space matrix into the multi-modal data register, and outputting an associated feature matrix; using a hybrid interpolation model to perform hybrid interpolation on the correlation feature matrix to obtain a full-grid correlation correlation interpolation matrix; and a CNN error correction module is used to optimize the full-grid correlation degree correlation interpolation matrix to obtain a geological mineral resource space-time intrinsic code, and geological mineral resource data intelligent modeling is realized based on the geological mineral resource space-time intrinsic code.

The invention relates to the technical field of machining, in particular to an integral impeller machining method, device and equipment based on a five-axis machining center, and the method comprises the steps: obtaining cutter location data of a starting cutter location point and an ending cutter location point of an interpolation path section according to geometric features of an impeller model, the time interval between the starting cutter location point and the ending cutter location point is determined; randomly generating a plurality of interpolation matrixes, and constructing a judgment matrix corresponding to each interpolation matrix; obtaining each effective interpolation matrix; the overall non-smoothness, the interpolation anomaly, the cutter location point optimization weight and the interpolation self-adaption degree of each column in each effective interpolation matrix are obtained; iteration is conducted on the interpolation matrix through an optimization algorithm, an optimal interpolation matrix is obtained, and the integral impeller is machined. According to the machining method, the change speed of the cutting tool in the machining process can be smooth, shaking of the cutting tool is effectively reduced, and the machining quality of the integral impeller is improved.

The invention relates to an interpolation method and an interpolation model for scRNA-seq data. An interpolation method for scRNA-seq data comprises the following steps: performing dropout interpolation on the scRNA-seq data through an automatic encoder of a Markov self-attention mechanism and a self-adaptive threshold low-rank approximation method to obtain an interpolation matrix XCG and an interpolation matrix XMF; the interpolation matrix XCG and the interpolation matrix XMF are integrated through a cell-level interpolation matrix integration method, and an interpolation result is obtained; and taking the interpolation result as the input of the next iteration until the iteration condition is met, and obtaining the final interpolation result after the loop is ended. According to the interpolation method and the interpolation model for the scRNA-seq data, the global heterogeneity of the scRNA-seq data is ensured, meanwhile, the local structure of the scRNA-seq data is captured, the interpolation value is highly consistent with the real data in trend, and the optimal numerical precision is also obtained.

The invention provides an antenna radiation characteristic obtaining method based on skeletonization and a MoM-PO algorithm. The method comprises the steps that an electrically-large-size platform and an antenna on the electrically-large-size platform are subdivided; defining an RWG primary function of the triangular patch pair; constructing matrix equations of the MoM region and the PO region based on the RWG primary functions of the MoM region and the PO region; the near-field matrix and the far-field matrix are filled based on an MoM-PO method and a skeletonization algorithm; and obtaining radiation characteristics of the antenna. According to the method, a skeletonization algorithm is adopted, far-field matrixes of coupling matrixes of the MoM and PO regions are filled through each group of impedance sub-matrixes of the coupling matrixes calculated through each group of interpolation matrixes of the MoM and PO regions and the coupling matrixes between the corresponding skeleton basis functions, the number of the skeleton basis functions is smaller than that of basis functions of the MoM and PO regions, and calculation is faster; the antenna radiation characteristic obtaining efficiency is effectively improved, and the computer memory requirement is reduced.

The invention belongs to the field of power equipment multi-physical field rapid calculation, and discloses a magnetic field rapid analysis and calculation method under a transformer short-circuit fault and a related device. The method comprises the following steps: calculating vector magnetic potentials of a plurality of previous time steps through a full-order calculation model of a transformer short-circuit magnetic field in a high-dimensional space; constructing a snapshot matrix of a solution vector and a snapshot matrix of a nonlinear term; obtaining a group of orthogonal bases based on an intrinsic orthogonal decomposition method and in combination with the snapshot matrix of the solution vector; constructing a reduced-order subspace by using an orthogonal basis; projecting the full-order calculation model of the short-circuit magnetic field of the transformer into the reduced-order subspace; based on a discrete experience interpolation method and in combination with the snapshot matrix of the non-linear term, obtaining an interpolation matrix of the non-linear term; updating a nonlinear term in the transformer short-circuit magnetic field reduced-order calculation model by using the interpolation matrix, and then calculating to obtain a vector magnetic potential in a reduced-order subspace; and reconstructing the vector magnetic potential back to the high-dimensional space, and calculating the magnetic field under the short-circuit fault of the transformer according to the reconstructed vector magnetic potential.

In various implementations, method and devices are disclosed that encode or decode a block of a picture with an interpolated matrix based intra prediction mode. For instance, the method comprises determining that a block is coded using a regular intra prediction mode, a regular intra prediction mode being an angular directional mode; responsive to determining that the regular intra prediction mode used to code the block belongs to a list of intra prediction mode candidates comprising at least two matrix-based intra prediction modes, obtaining a predicted block from an interpolation of a first intra matrix based intra prediction mode and of a second matrix based intra prediction mode.

The invention discloses a frequency domain super-resolution reconstruction OFDM (Orthogonal Frequency Division Multiplexing) waveform distortion suppression method, and belongs to the field of wireless communication. The method solves the problems that an existing method is high in complexity, sensitive to channel conditions and poor in error rate performance. The method comprises the following steps: constructing an interpolation matrix at a receiving end, and carrying out weighted interpolation on a frequency domain receiving signal by utilizing adjacent spectral line weighting to generate an interpolated frequency domain signal; the method comprises the following steps of: deducing to obtain a time domain equivalent relation of interpolation processing of a transmitting end and a receiving end by combining the logic of performing frequency domain zero insertion on an original frequency domain signal by a transmitting end, further jointly estimating an interpolated channel, and designing an equalizer according to a minimum mean square error criterion to perform equalization processing on the interpolated frequency domain signal to complete data recovery. According to the method, the problem of inter-symbol interference caused by insufficient CP of a common OFDM system with insufficient cyclic prefixes is solved, inter-symbol interference and inter-subcarrier interference caused by insufficient cyclic prefixes can be effectively suppressed, and accurate demodulation data can be obtained. The method can be applied to the field of wireless communication.

The present application belongs to the technical field of structure optimization design, and discloses a structure topology optimization design method and device, steps are as follows: (1) dividing a physical design domain into a background grid, based on coordinate information of background nodes of the background grid, a sparse filtering matrix is constructed by using a Gaussian kernel function with row normalization; (2) using the sparse filtering matrix to perform front filtering on design variables on the background nodes to obtain a smooth density field, and then obtaining a level set function field; (3) using an adaptive grid subdivision algorithm to cut and locally adaptively reconstruct the level set function field to obtain an analysis grid; (4) interpolating the level set function field to the analysis grid through a sparse global interpolation matrix from the background grid to the analysis grid to obtain a level set function field; (5) projecting the level set function field to obtain a pseudo-density field on the analysis grid nodes, and then obtaining an optimal topology configuration. The present application realizes good boundary smoothness while improving optimization efficiency.

The present disclosure relates to systems and methods for wide neural networks and sensing array measurement estimation. A full sensing array can be modeled using a wide neural network (BNN). A sensing array can produce a first vector comprising P measurements. The full sensing array can be modeled by producing a second vector comprising Q wave domain measurements using the first vector as follows. The first vector can be multiplied by an interpolation matrix to produce interpolated vectors each comprising Q interpolated values. Applying a transformation function to the interpolated vectors produces a representation vector which can be interleaved to produce Q pooling inputs. The second vector can be produced by performing a plurality of nonlinear pooling operations on the Q pooling inputs, where one of the nonlinear pooling operations produces one of the Q wave domain measurements in the second vector from one of the Q pooling inputs. The interpolation matrix can be produced by training the BNN.

The invention discloses a method for calculating deformation of a component with a large length-width ratio based on a local radial basis function point collocation method. The method comprises the following steps: 1) obtaining mechanical parameters of the inspected component; 2) configuring a dot matrix of a plurality of observation points in the interior and the boundary of the inspected component; 3) respectively determining local influence points for each observation point in the dot matrix; 4) obtaining an interpolation matrix of the calculation field quantity at each observation point according to a local radial basis function collocation method; 5) establishing a control equation of component deformation, and determining boundary conditions according to working conditions of the components; 6) constructing an equation for calculating a displacement field, and calculating the displacement value of each observation point; and 7) according to engineering requirements, calculating a stress field and a strain field by using the displacement value of the observation point. According to the method, the precision of structural deformation calculation is improved, the deformation calculation efficiency of the component with the large length-width ratio is greatly improved, the influence of shape parameters on the calculation precision is greatly reduced, and therefore the stability of deformation calculation is improved.

The invention relates to the technical field of electromagnetic field simulation modeling, in particular to a magnetotelluric efficient parallel simulation method and device based on random path integration, and the method comprises the steps: rewriting a deterministic solution based on a solution matrix equation into a form based on random path integration; in the offline preparation stage, the number of times that random walk particles pass through each lattice point is recorded, a path matrix is generated, the number of times that all random walk particles pass through all lattice points of a Robin boundary is recorded, a boundary path matrix is generated, and preset model grids are interpolated to different random walk grids to generate an interpolation matrix; and in the online stage, obtaining a final calculation result according to the path matrix, the boundary path matrix and the interpolation matrix. Therefore, the problems of unit communication, load balancing and I / O bottleneck in parallel simulation of a large-scale electromagnetic positive problem caused by parallelization transformation of a non-parallel algorithm adopted by an existing deterministic simulation method based on equation set solution in the prior art are solved.

The invention discloses a filter training and energy distribution matrix generation method, device and equipment, and relates to the technical field of image processing, and the method comprises the steps: carrying out the energy tracing processing according to the sub-coupling-out step number of light in a target optical waveguide coupling-out region, and generating a partial energy distribution matrix; determining a sample matrix region from the partial energy distribution matrix, and determining a predicted energy value of an interpolation matrix region according to a first actual energy value of the sample matrix region and a to-be-trained weight of the to-be-trained image interpolation filter; updating the to-be-trained weight according to the predicted energy value, and generating a target image interpolation filter; wherein the target image interpolation filter is used for performing interpolation prediction on the complete energy distribution matrix. According to the method, the complete energy distribution matrix of the optical waveguide coupling-out region can still be generated without introducing all coupling-out steps for operation, the operation complexity is reduced, the operation resources are saved, and the generation efficiency of the energy distribution matrix is improved.

The present invention discloses a finite element simulation method based on a multi-layer neural network. The specific process is as follows: in cloth simulation, the cloth to be predicted is modeled as a cloth hyperelastic body model and divided into several units. For each unit, a dynamic energy expression is constructed and solved to construct a training data set for the multi-layer neural network; a multi-level coarse and fine grid structure is constructed using the farthest point sampling method, and an interpolation matrix is ​​constructed for each layer of coarse grid; the multi-layer neural network is trained on the training data set, and the trained multi-layer neural network completes predictions at multiple moments. At each moment, the multi-layer neural network outputs a displacement matrix of a fine grid until a preset maximum number of inferences is reached. The displacement matrices of the fine grids output by the multi-layer neural network at all moments are used as position prediction results. The present invention realizes efficient solution of nonlinear equations for finite element simulation, which can improve the efficiency of finite element simulation.

In various implementations, method and devices are disclosed that encode or decode a block of a picture with an interpolated matrix based intra prediction mode. For instance, the method comprises determining that a block is coded using a regular intra prediction mode, a regular intra prediction mode being an angular directional mode; responsive to determining that the regular intra prediction mode used to code the block belongs to a list of intra prediction mode candidates comprising at least two matrix-based intra prediction modes, obtaining a predicted block from an interpolation of a first intra matrix based intra prediction mode and of a second matrix based intra prediction mode.

This invention discloses a fast beamforming method based on nested non-uniform Fourier transform, comprising the following steps: (1) pre-calculating relevant parameters of the nested non-uniform Fourier transform, including the fast Fourier transform length, the pre-interpolation coefficient matrix, and the post-interpolation coefficient matrix; (2) performing pre-interpolation on the array response signal in the frequency domain based on the pre-interpolation coefficient matrix to obtain the pre-interpolation matrix; (3) performing fast Fourier transform on the pre-interpolation matrix based on the fast Fourier transform length to achieve spatial domain transformation and obtain the transformed matrix; (4) interpolating the transformed matrix based on the post-interpolation coefficient matrix to obtain the post-interpolation matrix as the beamforming result. This method significantly reduces the computational burden of beamforming in a phased array three-dimensional camera sonar system while ensuring accuracy.

The invention provides an arbitrary array MIMO radar parameter estimation method and device, and belongs to the field of radar signal processing. The method comprises the following steps: in an offline stage, constructing an array manifold matrix of a physical arbitrary array and a virtual uniform linear array at a plurality of calibration angles, solving a regularization least square problem, and obtaining a transmitting end interpolation matrix and a receiving end interpolation matrix; in the on-line stage, digital pre-weighting is carried out on a baseband transmitting signal by using a transmitting end interpolation matrix, a radar echo signal of a target is received, a three-dimensional mixed data tensor is constructed, and then demodulation is carried out; and decomposing the demodulated tensor by adopting a parallel factor analysis algorithm to obtain a virtual transmitting factor matrix and a physical receiving factor matrix, and estimating the direction of arrival and the direction of arrival of the target in combination with a receiving end interpolation matrix. Through space virtualization, an advanced tensor algorithm is expanded to any actual array platform from an ideal uniform array, and the problem of algorithm applicability under hardware constraint is solved.

The embodiment of the invention provides a method and device for optimizing configuration parameters of a multiplication device. The method comprises the following steps: acquiring a first valuation matrix, a second valuation matrix, an interpolation matrix and an input parameter set corresponding to target multiplication; the first valuation matrix and the second valuation matrix are respectively used for controlling a decomposition combination mode of a multiplier and a multiplicand under a Karatsuba algorithm of decomposing the multiplier and the multiplicand into k fragments, the interpolation matrix is used for recovering a multiplication result, and the input parameter set at least comprises mode parameters of target multiplication operation; the multiplier is used for defining multiplication types; determining a row range of a plurality of rows for optimizing the interpolation matrix according to the mode parameters; aiming at the interpolation matrix, aiming at reducing the overhead, performing optimization processing in the row range to obtain an optimized interpolation matrix, and correspondingly updating the first valuation matrix and the second valuation matrix, the overhead comprising the area overhead of the multiplication device; the optimized interpolation matrix, the first valuation matrix and the second valuation matrix are used as configuration parameters of the multiplier.

The invention discloses a fast beam forming method based on nested non-uniform Fourier transform, which comprises the following steps of: (1) pre-calculating relevant parameters of the nested non-uniform Fourier transform, including fast Fourier transform length, a front interpolation coefficient matrix and a rear interpolation coefficient matrix; (2) performing pre-interpolation on the array response signal of the frequency domain based on the pre-interpolation coefficient matrix to obtain a pre-interpolation matrix; (3) performing fast Fourier transform on the pre-interpolation matrix based on the fast Fourier transform length, and realizing spatial domain transform to obtain a transformed matrix; and (4) interpolating the transformed matrix based on the post-interpolation coefficient matrix to obtain a post-interpolation matrix as a beam result. According to the method, on the premise that the precision is guaranteed, the beam forming calculation burden of the phased array three-dimensional camera shooting sonar system is remarkably reduced.

The application provides an infrared wide-spectrum classification method and system for isomorphism objects with different materials, and belongs to the technical field of infrared photoelectric imaging and target classification and identification. The method comprises the following steps: normalizing a one-dimensional discrete spectrum signal to a 0-1 range; decomposing the normalized one-dimensional discrete spectrum signal into an intrinsic mode signal by EMD; obtaining an i*n-sized spectrum signal interpolation matrix by cubic spline interpolation of the intrinsic mode signal; performing point multiplication of the spectrum signal interpolation matrix and a full-spectrum weight matrix to obtain a spectrum feature matrix; and inputting the spectrum feature matrix into a spectrum classification model to obtain a spectrum category. The application can effectively extract real information in the spectrum while suppressing noise in the spectrum, and can guarantee the accuracy of the classification result by using a neural network under the condition of few samples.

The application relates to the field of spacecraft propulsion technology, in particular to a continuous adjustable electric propulsion testing method and device, the method comprising setting a test instruction change period synchronized with a satellite orbit period; constructing an atmospheric resistance interference model changing with an orbit phase and converting the atmospheric resistance interference model into a dynamic thrust demand benchmark; generating at least one dynamic thrust instruction in a sine wave, a triangular wave, a step signal or a composite waveform; using a three-dimensional interpolation matrix to solve power and gas supply parameters in real time and driving a thruster to perform wide-range dynamic adjustment; and evaluating dynamic tracking performance based on a root mean square error and a frequency response characteristic index. The application realizes high-fidelity ground reproduction of a complex interference environment of a satellite in orbit, overcomes the limitations of existing static tests and single working conditions, and provides a scientific and effective testing scheme for dynamic performance verification of a continuous adjustable electric propulsion system.

The present application discloses a visual monitoring method, device, computer equipment and storage medium for conveyor belt wear, including receiving first thickness data of the conveyor belt uploaded by a laser sensor array, updating a data matrix based on the first thickness data; updating a corresponding first interpolation matrix based on the updated data matrix; determining RGBA color values ​​for rendering and display based on the thickness data in the updated first interpolation matrix, and updating and displaying a Bitmap image according to a color value matrix composed of RGBA color values. This solution converts the cover glue thickness collected by the sensor array into the RGBA value of a pixel image and generates a visual dynamic image display, which reflects the wear of the conveyor belt with changes in image color and depth, and realizes the conversion of rigid values ​​into intuitive visual image display.

This application relates to the field of image processing technology, and further to a method and apparatus for local black level calibration, a computer-readable storage medium, and a computer program product. The method includes: performing temporal accumulation on multiple acquired original images to determine a target image; determining effective pixels of the target image based on the median and standard deviation of multiple target pixels and the mean of each pixel in the target image; determining normalized weights for all effective pixels based on the mask and variance of all effective pixels; determining mesh nodes based on the normalized weights of all effective pixels, the mean of each pixel in the target image, the sampling interpolation matrix, and the regularization coefficient; and performing local black level calibration on the multiple original images based on the mesh nodes. This method significantly eliminates spatial distribution noise from the image sensor and improves image quality.

This application relates to the field of machining technology, specifically to an integral impeller machining method, device and equipment based on a five-axis machining center. The method includes: obtaining the tool position data of the starting tool position point and the ending tool position point of the interpolation path segment according to the geometric characteristics of the impeller model, as well as the time interval between the starting tool position point and the ending tool position point; randomly generating a plurality of interpolation matrices, and constructing a judgment matrix corresponding to each interpolation matrix; obtaining each effective interpolation matrix; obtaining the overall non-smoothness, interpolation abnormality degree, tool position point optimization weight, and interpolation adaptability degree of each column in each effective interpolation matrix; iterating the interpolation matrix using an optimization algorithm to obtain the optimal interpolation matrix, and machining the integral impeller. This application can make the change speed of the cutting tool relatively smooth during the machining process, effectively reduce the cutting tool jitter, and improve the machining quality of the integral impeller.

This application provides an uncertainty analysis method and product for reactor multiphysics coupling calculations. The uncertainty analysis method includes obtaining a first snapshot matrix of reference multiphysics coupling calculation results for the reactor at multiple times under multiple first operating conditions, and a first reduced-order basis matrix and a first reduced-order basis coefficient matrix of the first snapshot matrix; determining a second snapshot matrix of predicted multiphysics coupling calculation results for the reactor at multiple times under multiple second operating conditions based on the first reduced-order basis matrix, the first reduced-order basis coefficient matrix, and interpolation matrices of multiple first operating conditions and multiple second operating conditions; and determining the uncertainty of the predicted multiphysics coupling calculation results for the reactor at multiple times under multiple second operating conditions based on the average vector and variance vector of all row vectors in the second snapshot matrix. This application can improve the efficiency of uncertainty analysis for reactor multiphysics coupling calculations and reduce the cost of uncertainty analysis.

The present invention proposes an improved radial basis function grid deformation method based on modal space and greedy algorithm, and uses the greedy algorithm to solve the support point set M of each order modal vibration function. i , and taking their union, a set M of support points that meets all modal requirements is found. The support points in this set meet the physical displacement reconstruction requirements at all times, and these points can be used to update the positions of all grid points within the fluid computational domain. The support point set determined according to the present invention meets the physical displacement reconstruction requirements at all time steps, eliminating the need to repeatedly screen the support point set and calculate the RBF interpolation matrix at each time step. This significantly improves the efficiency of solving RBF mesh deformations and reduces the computational complexity of mesh deformations, thereby improving the efficiency of CFD / CSD coupled time-domain calculations using RBFs for mesh deformations.

The invention provides a rapid modeling method capable of realizing twin crystallization design of a lattice structure, and belongs to the technical field of modeling and simulation. According to the method, a lattice unit cell overall interpolation matrix to be mapped is constructed, a twin crystallization target subspace unit cell structure and an overall layout scheme are determined, point cloud data are mapped to a target subspace, finite element entity unit model reconstruction and assembly are carried out, and rapid twin crystallization design of a lattice structure is achieved. According to the rapid modeling method capable of achieving twin crystallization design of the lattice structure, the modeling efficiency can be effectively improved, the design cost is reduced, the method is suitable for twin crystallization design of various lattice structures, rapid modeling can be achieved under the condition of low computing resources, and the modeling efficiency is improved. And the requirements of practical engineering application such as aerospace, automobile manufacturing and biomedicine are met.

The invention relates to an aeroelastic dynamic grid construction method oriented to an SU2 format aerodynamic grid, belongs to the technical field of aeroelastic mechanics, and comprises the following steps: reading grid and deformation parameters of an SU2 format aerofoil aerodynamic grid model under working conditions, and obtaining coordinates of all grid nodes and deformation information of deformation points; before deformation calculation is started, an efficient greedy simplification method is adopted, part of nodes are selected from grid nodes to serve as supporting points of the aeroelastic dynamic grid, and low-dimensional radial basis function interpolation meeting the precision requirement is established according to displacement on the nodes. Constructing an interpolation matrix through a radial basis function, solving a deformation weight coefficient, obtaining deformation information of all nodes, recovering node connection information of the SU2 grid, and obtaining a finally deformed grid; the construction of grid deformation in efficient and high-precision aeroelastic analysis is realized.