9 results about "Interpolation matrix" patented technology

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 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 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 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.

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.