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42results about How to "Reduce approximation error" patented technology

Beam forming method based on subspace interference-plus-noise covariance matrix reconstruction

The invention belongs to the field of array signal processing and mainly relates to robustness of a standard Capon self-adaptive beam forming algorithm based on covariance matrix reconstruction to interference signal steering vector errors. The beam forming algorithm based on subspace interference-plus-noise covariance matrix reconstruction comprises the following steps: at first, utilizing matrix received data to estimate the steering vector a(theta d), d=2,3,...,D and the power sigma<2> d(theta d) of all D-1 interference signals and meanwhile estimate the noise power sigma<2>, wherein d=2,3,...,D; then reconstructing an interference-plus-noise covariance matrix R' according to the definition R of the interference-plus-noise covariance matrix; finally, constructing a signal covariance matrix in a relatively small angle range 1; taking the dominant eigenvector of the signal covariance matrix as a desired signal steering vector to estimate a(theta 1); together with the reconstructed R', obtaining a novel beam forming weighing vector W, wherein the formulas of R, R' and W are shown in the description. The beam forming method provided by the invention overcomes the defects of the conventional beam forming algorithm, thereby having good robustness to interference signal steering vector errors.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA

Program segment smooth compression processing method suitable for numerical control device

The invention relates to a program segment smooth compression processing method suitable for a numerical control device, comprising the following steps: (1) analysis of a processing path, i.e. removing irregular programming points in a numerical control program by filtration, and deducing parts required to conduct smoothness in shape; (2) parameterization of the programming points, i.e. carrying out parameterization on each programming point by means of distances among the programming points; (3) selection of characteristic programming points, i.e. dividing the programming points into the characteristic programming points and non-characteristic programming points by means of processing shape and bending direction at the programming points; (4) calculation of tangent vector at the characteristic programming points, i.e. calculating the tangent vector at the characteristic programming points by constructing an interpolation curve; (5) compression of program segments, i.e. compressing the program segments between the adjacent programming points into a segment of a spline curve; and (6) control of mismachining tolerance, i.e. ensuring the compressed spline curve to meet requirements of machining accuracy by adjusting the shape of the curve segment. The method in the invention can prevent irregularity of a workpiece surface from being caused by line interpolation at transition of the programming segment and has the advantages of high machining accuracy and high efficiency.
Owner:SHENYANG GOLDING NC & INTELLIGENCE TECH CO LTD

MIMO radar single measurement vector DOA estimation method based on iterative weighted near-end projection

The invention discloses an MIMO (Multiple Input and Multiple Output) radar single measurement vector DOA (Direction of Arrival) estimation method based on iterative weighted near-end projection. The method comprises the following steps of: vectorizing a covariance matrix of received data after dimensionality reduction; constructing a weighting matrix by using high-order power of a covariance inverse matrix after dimensionality reduction so as to perform proper weight constraint on a sparse vector; establishing a weighted near-end function optimization model to represent a non-convex and non-smooth sparse optimization problem in MIMO radar single measurement vector DOA estimation; and finally, obtaining a near-end operator through an SCAD (Smoothly Clipped Absolute Deviation Penalty) function in an iteration process, and projecting the near-end operator to a feasible set to solve the weighted function optimization model so as to obtain a sparse solution, and obtaining a real target DOA estimation value by searching the position of a spectral peak. Compared with a reweighted l1-SVD algorithm and a weighted SL0 (Smoothed l0norm) algorithm, the method can obtain the better DOA estimation performance, and the prior information of the number of the targets is not needed to be known in advance.
Owner:NANJING UNIV OF INFORMATION SCI & TECH

Interfering noise covariance matrix reconstruction method aiming at incoming wave direction error

The invention belongs to the array signal processing field, and mainly relates to robustness of a standard Capon adaptive beamforming algorithm, based on covariance matrix reconstruction, against interfering signal incoming wave direction error; the interfering noise covariance matrix reconstruction method aiming at incoming wave direction error comprises the following steps: firstly using array reception data to estimate guide vectors (see formula, wherein d=1, 2..D ) of all D signals, to estimate D-1 interfering signal power (see formula, wherein d=2,3.. D), and to simultaneously estimate a noise power (see formula); then reconstructing the interfering noise covariance matrix (see formula) according to the definition of the interfering noise covariance matrix (see formula); combining the estimated guide vectors with the reconstructed interfering noise covariance matrix so as to obtain a novel beamforming weighting vector (see formula). The method can improve estimation precision of the interfering noise covariance matrix, can effectively reduce desired signal elements, can greatly weaken or prevent desired signal self-elimination phenomenon, thus greatly improving output SINR.
Owner:UNIV OF ELECTRONIC SCI & TECH OF CHINA

Three-dimensional grid model simplification method and system based on optimized feature preservation

ActiveCN111667565AEliminate slender trianglesTo achieve the effect of feature preservationInternal combustion piston enginesDetails involving 3D image dataTheoretical computer scienceQuadratic error
The invention discloses a three-dimensional grid model simplification method and system method and system based on optimized feature preservation. The three-dimensional grid model simplification method includes the steps: firstly, calculating the Gaussian curvature of each edge in a three-dimensional grid, combing the Gaussian curvature and the secondary error measure of the edge to calculate thefolding cost of the edge, and constructing edge folding operation based on feature preservation; combining an edge splitting operation sequence and an edge folding operation sequence based on featurepreservation to generate a mixed sequence, and using a mixing mechanism for simplifying a three-dimensional grid model; replacing a global search stage in whale optimization by crossover and mutationoperation of differential evolution, and constructing a whale differential evolution optimization algorithm; and finally, searching an optimal edge splitting operation and edge folding operation sequence combination mode by utilizing an optimization algorithm, so that the approximate error between the simplified three-dimensional model and the original model is minimum. According to the three-dimensional grid model simplification method, through grid simplification, the optimal three-dimensional grid simplification effect with the minimum approximate error can be obtained, meanwhile, geometrical characteristics can be well kept, and the quality of triangles in the model is improved.
Owner:WUHAN UNIV

Adaptive wide-area damping controller

The invention relates to an adaptive wide-area damping controller. The adaptive wide-area damping controller comprises an adaptive delay compensator and an N input and output GrHDP unit; the adaptivedelay compensator is used for obtaining N first wide-area measurement signals, performing adaptive delay compensation and outputting N second wide-area measurement signals; the N input and output GrHDP unit is used for receiving the N second wide-area measurement signals and obtaining N first coordinated control signals based on an adaptive dynamic programming algorithm; and the adaptive delay compensator is also used for receiving the N first coordinated control signals and obtaining N second coordinated control signals by calculation based on a GrHDP model algorithm. According to the adaptive wide-area damping controller disclosed by the invention, multiple input and multiple output are carried out by adoption of the GrHDP unit; multi-target coordinated adaptive control on multiple low-frequency oscillation modes of a power system can be simultaneously carried out; the adaptive capability of the power system is improved; furthermore, both the first wide-area measurement signals and the first coordinated control signals are subjected to delay compensation; the control influence of delay onto the power system is greatly avoided; and the damping improvement of the controller onto the power system is improved.
Owner:HUAZHONG UNIV OF SCI & TECH

Method for inhibiting velocity fluctuation of electric vehicle driving system

The invention provides a method for inhibiting the velocity fluctuation of an electric vehicle driving system. The method comprises the following steps: obtaining a rotor position by adopting an encoder, and transmitting the rotor position to a velocity control ring; and adopting a parallel mode combining a prediction PI joint controller, a repetitive controller and a nonlinear adaptive feedback observer by the velocity control ring, adopting the parallel mode of the prediction PI joint controller and the repetitive controller during electric start, substituting two continuous sampling values into a prediction domain of the prediction PI joint controller by the encoder, switching to the parallel mode of the repetitive controller and the nonlinear adaptive feedback observer when an electric vehicle enters a stable operation mode, and then transmitting an output signal of the velocity control ring. According to the method provided by the invention, the prediction PI joint control, the nonlinear adaptive feedback observation control, the repetitive control and the vector control are combined together to improve the stability, the accuracy and the dynamic response ability of the electric vehicle driving system and inhibit the velocity fluctuation in an electric vehicle running process.
Owner:NANJING INST OF TECH

Indoor firefighter positioning method based on single reference node/inertia combination

The invention discloses an indoor firefighter positioning method based on single reference node / inertia combination, thereby providing self position information for firefighters executing emergency rescue tasks in a fire scene. According to the positioning method, only one reference node is needed and a firefighter entering a fire scene temporarily places the reference node in an environment for executing a rescue task; a virtual reference node array is established by combining the movement speed and posture data of the firefighter; a relative distance between the firefighter and the virtual reference node is obtained by utilizing a wireless distance measurement principle; a distance measurement equation set is established and the position of the firefighter is calculated. When a firefighter begins to execute a task, autonomous positioning is firstly realized through the inertial navigation system; after the condition of constructing the virtual reference node array is met, the virtualreference node array is constructed by utilizing the speed and posture information calculated by the inertial sensor carried by the firefighter; and finally, the satisfied distance measurement equation set between the firefighter and the virtual reference node is calculated to realize indoor positioning of the firefighter.
Owner:BEIHANG UNIV

Time sequence feature extraction method and system based on confidence interval

ActiveCN110162552AReduce approximation errorOvercoming problems that cannot be captured accuratelyVisual data miningStructured data browsingData segmentFeature extraction
The invention discloses a time sequence feature extraction method and system based on a confidence interval. The method comprises the steps that the value range of the number of segments of historicaltime sequence data is determined; a data segment segmentation step: determining the number K of segments, and segmenting the historical time sequence data into K continuous non-overlapping data segments; a weight mean value calculation step: calculating the area of the intersection of the parallelogram confidence space of each divided data segment and the discrete signal convex hull, and calculating the weight of the area of each intersection in the area of the parallelogram and the mean value of the weights; adding 1 to the value of the piecewise number K, and repeating the data segment segmentation step and the weight mean value calculation step to obtain the mean value of the weights under different piecewise numbers; performing ending until the number K of segments is greater than themaximum number of segments; selecting the number of segments corresponding to the maximum value of the weight mean value as the optimal number of segments; and segmenting the historical time sequencedata by using the optimal segmentation number to obtain a historical time sequence data feature extraction result.
Owner:SHANDONG UNIV OF SCI & TECH

Program segment smoothing and compression processing method suitable for numerical control device

The invention relates to a method for smoothing and compressing program segments suitable for a numerical control device, comprising the following steps: 1) Analyzing the processing path: filtering out irregular programming points in the numerical control program, and inferring the part requiring shape smoothness; 2) programming Point parameterization: parameterize each programming point by the distance between the programming points; 3) Select feature programming points: divide the programming points into feature programming points and non-feature programming points by the bending direction of the processed shape at the programming points ; 4) Calculate the tangent vector at the feature programming point: calculate the tangent vector at the feature programming point by constructing an interpolation curve; 5) Compress the program segment: compress the program segment between the adjacent feature programming points into a section of the spline curve; 6) Control machining error: ensure that the compressed spline curve meets the machining accuracy requirements by adjusting the shape of the curve segment. The method of the invention can avoid uneven workpiece surface caused by linear interpolation at the transition of program segments, and has high machining accuracy and high efficiency.
Owner:SHENYANG GOLDING NC & INTELLIGENCE TECH CO LTD

Time series feature extraction method and system based on confidence interval

ActiveCN110162552BReduce approximation errorOvercoming problems that cannot be captured accuratelyVisual data miningStructured data browsingFeature extractionData segment
The invention discloses a time sequence feature extraction method and system based on a confidence interval. The method comprises the steps that the value range of the number of segments of historicaltime sequence data is determined; a data segment segmentation step: determining the number K of segments, and segmenting the historical time sequence data into K continuous non-overlapping data segments; a weight mean value calculation step: calculating the area of the intersection of the parallelogram confidence space of each divided data segment and the discrete signal convex hull, and calculating the weight of the area of each intersection in the area of the parallelogram and the mean value of the weights; adding 1 to the value of the piecewise number K, and repeating the data segment segmentation step and the weight mean value calculation step to obtain the mean value of the weights under different piecewise numbers; performing ending until the number K of segments is greater than themaximum number of segments; selecting the number of segments corresponding to the maximum value of the weight mean value as the optimal number of segments; and segmenting the historical time sequencedata by using the optimal segmentation number to obtain a historical time sequence data feature extraction result.
Owner:SHANDONG UNIV OF SCI & TECH
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