Search - c program for covariance matrix

Search - c program for covariance matrix - List

[Special Effects] generate_mean_covariance DL : 0: 本程序编程语言为C，主要用来对遥感训练数据进行处理，得到covariance矩阵。-This program is used to generate 3 files:mean file,covariance matrix of the training set, and inverse covariance matrix for training set.
Update : 2025-02-19 Size : 4kb Publisher : 李会利
[OpenGL program] maximum_likelihood_classification DL : 0: 经典的最大似然法分类法的C语言实现，有助于深入了解遥感分类原理。-This program implements the maximum likelihood classification procedure. ouput:1.classified image, and 2. probability file. Note: For constructong variance-covariance matrix must be generic binary file.
Update : 2025-02-19 Size : 4kb Publisher : 李会利
[Algorithm] CMatrix DL : 0: 对称矩阵相关元算，主成分分析(PCA)， fisher discriminant analysis(FDA).，-Introduction ============ This is a class for symmetric matrix related computations. It can be used for symmetric matrix diagonalization and inversion. If given the covariance matrix, users can utilize the class for principal component analysis(PCA) and fisher discriminant analysis(FDA). It can also be used for some elementary matrix and vector computations. Usage ===== It s a C++ program for symmetric matrix diagonalization, inversion and principal component anlaysis(PCA). To use it, you need to define an instance of CMatrix class, initialize matrix, call the public funtions, and finally, free the matrix. For example, for PCA, CMarix theMat // define CMatrix instance float** C // define n*n matrix C = theMat.allocMat( n ) Calculate the matrix (e.g., covariance matrix from data) float*phi,*lambda // eigenvectors and eigenvalues int vecNum // number of eigenvectors (<=n) phi = new float [n*vecNum] lambda = new float [vecNum] the
Update : 2025-02-19 Size : 62kb Publisher : 朱
[Internet-Network] maximum_likelihood_classification DL : 0: 经典的最大似然法分类法的C语言实现，有助于深入了解遥感分类原理。-This program implements the maximum likelihood classification procedure. ouput:1.classified image, and 2. probability file.Note: For constructong variance-covariance matrix must be generic binary file.
Update : 2025-02-19 Size : 3kb Publisher : whicme
[e-language] AOA3DLocBias DL : 0: SensorPositons: (Dim x M) matrix, each column is a sensor position and first column is the reference sensor the sensors should not lie in one plane or line r: a (M-1) x 1 vector of TDOA measurements times signal propagation speed M is the number of sensors and should be at least Dim+2 Q: the covariance matrix of the r vector SourceLocation: estimated source location Note: W1 is updated 3 times (RptCnt=3) in Stage-1, however in most cases updating W1 once (RptCnt=1) is sufficient. The program can be used for 2D(Dim=2) or 3D(Dim=3) localization Ming Sun, K. C. Ho 08-01-2009 10-01-2010, revised Copyright (C) 2009 Computational Intelligence Signal Processing Laboratory University of Missouri Columbia, MO 65211, USA. hod@missouri.edu- SensorPositons: (Dim x M) matrix, each column is a sensor position and first column is the reference sensor the sensors should not lie in one plane or line r: a (M-1) x 1 vector of TDOA measurements times signal propagation speed M is the number of sensors and should be at least Dim+2 Q: the covariance matrix of the r vector SourceLocation: estimated source location Note: W1 is updated 3 times (RptCnt=3) in Stage-1, however in most cases updating W1 once (RptCnt=1) is sufficient. The program can be used for 2D(Dim=2) or 3D(Dim=3) localization Ming Sun, K. C. Ho 08-01-2009 10-01-2010, revised Copyright (C) 2009 Computational Intelligence Signal Processing Laboratory University of Missouri Columbia, MO 65211, USA. hod@missouri.edu
Update : 2025-02-19 Size : 1kb Publisher : marcelonog29
[e-language] TDOALoc DL : 0: SensorPositons: (Dim x M) matrix, each column is a sensor position and first column is the reference sensor the sensors should not lie in one plane or line r: a (M-1) x 1 vector of TDOA measurements times signal propagation speed M is the number of sensors and should be at least Dim+2 Q: the covariance matrix of the r vector SourceLocation: estimated source location Note: W1 is updated 3 times (RptCnt=3) in Stage-1, however in most cases updating W1 once (RptCnt=1) is sufficient. The program can be used for 2D(Dim=2) or 3D(Dim=3) localization Ming Sun, K. C. Ho 08-01-2009 10-01-2010, revised Copyright (C) 2009 Computational Intelligence Signal Processing Laboratory University of Missouri Columbia, MO 65211, USA. hod@missouri.edu- SensorPositons: (Dim x M) matrix, each column is a sensor position and first column is the reference sensor the sensors should not lie in one plane or line r: a (M-1) x 1 vector of TDOA measurements times signal propagation speed M is the number of sensors and should be at least Dim+2 Q: the covariance matrix of the r vector SourceLocation: estimated source location Note: W1 is updated 3 times (RptCnt=3) in Stage-1, however in most cases updating W1 once (RptCnt=1) is sufficient. The program can be used for 2D(Dim=2) or 3D(Dim=3) localization Ming Sun, K. C. Ho 08-01-2009 10-01-2010, revised Copyright (C) 2009 Computational Intelligence Signal Processing Laboratory University of Missouri Columbia, MO 65211, USA. hod@missouri.edu
Update : 2025-02-19 Size : 1kb Publisher : marcelonog29