15 results about "Design matrix" patented technology

A method of estimating noise for individual gates of a quantum circuit uses averaged circuit eigenvalue sampling to determine an overall eigenvalue for the circuit. The circuit is sampled a sufficient number of times to fill a design matrix, wherein the design matrix allows for solving of a system of equations to determine eigenvalues for the individual gates using the averaged eigenvalue for the overall quantum circuit, the samples, and the sample results. Applying a logarithm to these relationships enables solving the system of equations using linear estimation or linear regression, in some embodiments.

A kind of GNSS data processing method based on single observation filtering, comprising the following steps: first, design matrix, observation vector and covariance matrix are decomposed into multiple row vectors or scalar, then one observation is processed each time, after all the observations of current epoch are processed through multiple cycles, the state vector and covariance matrix of current epoch recursive update are obtained;GNSS parameters in state vector are divided into common parameters and non-common parameters, when processing each observation, update common parameters, then gradually increase new parameters in state vector, i.e. process observation by observation, to obtain extended state vector and covariance matrix;In the third step, when data processing is carried out using the above-mentioned extended state vector and covariance matrix, it includes single epoch processing and multi-epoch processing;The state estimation of current epoch is output as the result of GNSS positioning.The present application has high efficiency when processing high-dimensional observation data.

The invention provides a Beidou multi-frequency positioning method and device, electronic equipment and a storage medium. The method comprises the following steps: S1, collecting observation data and satellite ephemeris data of two target frequency points of a Beidou satellite; s2, based on the satellite ephemeris data, modeling the Beidou satellite clock correction by adopting a quadratic polynomial to obtain a clock correction modeling error, and taking the clock correction modeling error as a constraint term of an original design matrix to generate a design matrix with clock correction constraint; s3, constructing an observation vector based on the observation data, and substituting the design matrix with the clock error constraint and the observation vector into a TLS resolving model for resolving to obtain a positioning parameter initial value and a corresponding resolving residual error; s4, fitting a mapping relation between the residual error and the noise intensity based on the resolving residual error, generating a weight matrix, and performing weighted updating on the TLS resolving model by using the weight matrix to obtain an updated TLS resolving model; according to the embodiment of the invention, effective constraint on the design matrix error can be realized, and the clock error modeling precision is improved.

The application provides a semi-sphere adaptive grid division method for MHGM multi-path error modeling, comprising the following steps: obtaining a high-resolution multi-path error prior model as prior information by using non-difference residuals, and obtaining the spatial distribution characteristics of the multi-path error at a survey station; establishing a fixed grid division MHGM model on the survey station, extracting an AMR initial grid, obtaining the prior model value in the grid, setting to-be-estimated parameters at the corner points of the grid, and obtaining the relationship between the prior model value and the coordinates by using a bilinear interpolation method; setting the grid corner points as a to-be-estimated parameter matrix, the corresponding bilinear interpolation coefficient matrix as a design matrix, and the prior model value as an observation value matrix, so as to obtain the estimated value of the parameter matrix and the corresponding residual vector; traversing the residual vector, and considering that the grid can be divided when the absolute value is greater than the corresponding threshold value; stopping the division when the preset condition is met for any grid, or taking the grid as four congruent grids; and outputting the semi-sphere adaptive grid division result after the division is completed.

The invention relates to the technical field of electrical variable measurement, in particular to a voltage effective value rapid calculation method and device, and the method comprises the following steps: obtaining a voltage sampling sequence in any continuous quarter period time window; converting the voltage sampling sequence signal into a linear model; constructing a design matrix and an observation vector according to the sampling time sequence and the voltage sampling sequence, and obtaining a regular equation according to the design matrix and the observation vector; fitting each coefficient of the linear model by solving a regular equation through a least square method; and calculating a voltage amplitude according to each coefficient obtained by fitting, and calculating a voltage effective value according to the voltage amplitude. According to the method and the device provided by the invention, the voltage effective value can be quickly calculated at any initial phase in an extremely short data window, and the precision is relatively high.

The invention discloses a method and a device for preprocessing industrial generated data containing high-dimensional noise, and relates to the field of data preprocessing, and the method comprises the following steps: outputting a sampling time point set and a multi-dimensional observation data set by collecting multi-dimensional function type observation data in a set time interval; and representing the real function of each dimension observation value as a primary function linear combination, extracting effective features, and outputting a primary function set and an expansion coefficient. And constructing a design matrix, and establishing association between the multi-dimensional observation data and the effective features. A combined objective function is constructed by combining multivariable synchronous processing requirements and signal importance differences, and a penalty matrix is constructed through an inner product of a second derivative of a primary function. And selecting a smoothing parameter by minimizing a generalized cross validation criterion, solving a target function to obtain an estimation expansion coefficient, and constructing and outputting a smoothing function as input data of a statistical process control or fault diagnosis model. The method solves the problems that in the prior art, effective features are prone to being lost, multi-dimensional collaboration is not considered, and smooth parameter selection lacks self-adaption.

The invention discloses a test design method for determining test repetition times by giving a test efficacy value, which comprises the following steps of: 1, determining influence factors of response variables, constructing an initial test design scheme, and setting constraint conditions for a factor test efficacy threshold value; step 2, extracting non-repeated test schemes from the test design schemes; 3, setting different repetition times for each row of tests of the non-repeated test scheme, and constructing a test design matrix; and step 4, considering a target optimization problem, optimizing a target function, and determining the minimum number of repetitions of each row of tests conforming to the factor test efficacy threshold. By adopting the technical scheme provided by the invention, the optimal repeated test times meeting the test efficacy limitation can be determined, so that the uncertainty of the test repeated times is reduced.

The invention discloses a nacelle molded line optimization method and system based on CST parameterization and an intelligent algorithm and a storage medium, and the method comprises the steps: carrying out the parameterization modeling of an external molded line of a nacelle through employing a shape-like function method (CST), and taking a weight factor of a Bernstein polynomial as a design variable; setting a value range of a weight factor, and generating a test design matrix through a Latin hypercube sampling method; performing flow field simulation on the nacelle molded line corresponding to each group of weight factors based on ANSYS FLUENT, and calculating a resistance coefficient; constructing a back propagation neural network model, and performing training by taking the weight factor as input and the resistance coefficient as output; predicting an extended database by using the trained neural network, and optimizing by using a genetic algorithm to obtain an optimal weight factor combination; and generating a nacelle external molded line according to the optimal weight factor. According to the invention, through the weight factor based on the linear fitting polynomial, the optimization space is ensured under the condition that the optimization dimension is less, so that the nacelle scheme design efficiency is greatly improved.

The application discloses a GNSS and leveling fusion ground deformation monitoring method and system with dynamic optimization weight, and relates to the technical field of geodesy and deformation monitoring.The method comprises the following steps: analyzing leveling and GNSS rate observation data; setting the elevation correction number and subsidence rate parameter of a monitoring point as unknown parameters, constructing adjustment observation equations coupled with observation time and subsidence rate parameters, forming a design matrix, an observation vector and an initial weight matrix; performing dynamic weight optimization, introducing a global weight factor for adaptive scanning, and on the basis of the optimal global weight ratio, calculating a weight reduction factor by using robust estimation according to the standardized residual error of GNSS observation values, and obtaining the optimal weight matrix; and finally solving the optimal estimation value of unknown parameters based on the optimal weight matrix.The application realizes two-stage dynamic optimization of the weight, objectively optimizes the weight by data driving, effectively suppresses the influence of gross errors, and significantly improves the precision and reliability of multi-source data fusion deformation monitoring.

The present application belongs to the field of color correction, and discloses a multi-classification color correction method based on spectral shape driving, which comprises the following steps: obtaining standard tristimulus values of a plurality of standard color panels, collecting spectral reflectance data of the standard color panels and performing smoothing and normalization processing; extracting a group of spectral shape features from the processed spectral reflectance data, and performing standardization processing on the feature vectors composed of the spectral shape features; dividing all the standard color panels into multiple categories, and determining the centroid of each category; constructing a design matrix and a target matrix for each category, designing a corresponding loss function, solving to obtain the calibration coefficient matrix and the regularization hyperparameter of each category, and packaging them into a calibration model for deployment to a color difference meter; predicting samples by using the calibration model of each category, and performing weighted fusion according to the similarity value to output corrected tristimulus values. While maintaining the measurement accuracy of the color difference meter, the color calibration stability of the high and low reflectivity regions is significantly improved.

The invention relates to a random test design and robust optimization method and system for a complex equipment system. The method comprises the following steps: generating an initial test design matrix; according to the initial test design matrix, obtaining system response variable data; identifying key test factors according to system response variable data, and establishing an agent model; calculating an estimation result of a random error term according to the proxy model, and establishing a joint multi-parameter distribution model; coupling the agent model and the joint multi-parameter distribution model, and establishing a prediction model of system response variables; and analyzing a prediction result of the prediction model to obtain a robustness metric value, and if the robustness metric value does not reach a preset threshold value or does not meet a preset convergence criterion, optimizing the prediction model of the system response variable by newly adding data until a preset condition is met, obtaining the optimized prediction model, and outputting a final robust test design scheme. According to the invention, the robustness and reliability of the equipment system test can be obviously improved in a complex environment.

A GNSS data processing method based on single observation value filtering comprises the following steps that a design matrix, observation vectors and a covariance matrix are decomposed into a plurality of row vectors or scalar quantities, then one observation value is processed each time, and after all observation values of a current epoch are processed through multiple times of circulation, all observation values of the current epoch are processed; obtaining a recursively updated state vector and covariance matrix of the current epoch; dividing GNSS parameters in the state vector into common parameters and non-common parameters, updating the common parameters when processing each observation value, and then gradually adding new parameters into the state vector, that is, processing the observation values one by one to obtain an extended state vector and a covariance matrix; 3, when the expanded state vector and the covariance matrix are adopted for data processing, single epoch processing and multi-epoch processing are included; and outputting the state estimation of the current epoch as a GNSS positioning result. The method is high in efficiency when processing the high-dimensional observation data.

The invention discloses an asphalt pavement performance multivariable grey prediction method of a sparrow optimization regular term, which takes PCI sequences of a plurality of detection units as system behavior variables, constructs a novel discrete multivariable grey model NSMGM (1, 6, 1), weakens data randomness through grey accumulation generation and adjacent mean value generation, and improves the performance of an asphalt pavement. A model structure is perfected by introducing a linear correction term and a gray action quantity, and the problem of non-homology of parameters is solved; a regularization item is introduced, model deviation and variance are balanced through an Euclidean norm of a penalty parameter vector, and the ill-conditioned problem of a design matrix under a small sample is improved; a sparrow search algorithm is adopted to simulate a "explorer-follower-alerter" population behavior, regularization parameters are adaptively optimized in a preset search space, and subjective trial and error are avoided. The three components organically cooperate to form an integrated prediction framework of variable correlation capture, parameter stability estimation and global optimization, and a quantitative basis is provided for pavement maintenance planning and engineering decision.

The invention belongs to the field of color correction, and discloses a multi-classification color correction method based on spectral shape driving, and the method comprises the steps: obtaining the standard tristimulus values of a plurality of standard color palettes, collecting the spectral reflectivity data of the standard color palettes, and carrying out the smoothing and normalization processing; extracting a group of spectral shape features from the processed spectral reflectivity data, and carrying out standardization processing on a feature vector formed by the spectral shape features; dividing all the standard color plates into a plurality of categories, and determining the centroid of each category; constructing a design matrix and a target matrix for each category, designing a corresponding loss function, solving to obtain a calibration coefficient matrix and a regularization hyper-parameter of each category, and packaging the calibration coefficient matrix and the regularization hyper-parameter into a calibration model to be deployed to a colorimeter; and predicting the sample by using the calibration model of each category, performing weighted fusion according to the similarity value, and outputting a corrected tristimulus value. While the measurement precision of the colorimeter is maintained, the color calibration stability of high and low reflectivity areas is significantly improved.

The application discloses a kind of exploitation subsidence surface three-dimensional deformation estimation method, device, equipment, medium and product, is related to surface three-dimensional deformation estimation field, which comprises determining observation type according to the source and feature of different observation in subsidence monitoring mining area;Different observation includes the ascending track and descending track calculated by InSAR, and the vertical direction, coal seam strike and coal seam tendency simulated by PIM;According to observation error and observation type, construct observation matrix;Based on observation matrix, combine design matrix, according to the three-dimensional deformation variable to be solved and design matrix product error, construct real model;Based on real model, determine the variance matrix of observation error;According to variance matrix, construct observation equation;Based on observation matrix, the optimal estimation criterion of total least square is used to update weight matrix of the observation matrix, to determine the three-dimensional deformation estimation result of the three-dimensional deformation variable to be solved, and the north-south direction displacement is accurately estimated.