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Normal matrix
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91	➠ ➡ IMPROVED COVARIANCE MODELING FOR MAXIMUM LIKELIHOOD MULTIPLE SUBSPACE TRANSFORMATIONS Xi Zhou1, Ye Tian2, Jian-lai Zhou2, Bei-qian Dai1 Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2009-08-10 10:41:28 Data analysis Matrices Estimation theory Covariance matrix Linear discriminant analysis Covariance Normal distribution Matrix Maximum likelihood Statistics Covariance and correlation Multivariate statistics
92	ON THE DESIGN OF OPTIMIZED PROJECTIONS FOR SENSING SPARSE SIGNALS IN OVERCOMPLETE DICTIONARIES Wei Chen† Miguel R. D. Rodrigues⋆ Add to Reading List Source URL: www.cl.cam.ac.uk Language: English - Date: 2012-01-10 09:24:09 Estimation theory Multivariate statistics Information theory Overcompleteness Matrix Mean squared error Matching pursuit Normal distribution Orthogonal matrix Statistics Linear algebra Signal processing
93	MATHPartial solutions for practice problems for weeks 10 and 11 These are practice problems for the material discussed in lectures on Wednesday, Nov. 19 and Wednesday, Nov. 26, 2014. These problems will not be Add to Reading List Source URL: hkumath.hku.hk Language: English - Date: 2014-11-30 21:20:35 Matrix theory Eigenvalues and eigenvectors Diagonalizable matrix Minimal polynomial Jordan normal form Characteristic polynomial Generalized eigenvector Jordan matrix Matrix Algebra Linear algebra Mathematics
94	g01 – Simple Calculations on Statistical Data g01dcc NAG C Library Function Document nag_normal_scores_var (g01dcc) Add to Reading List Source URL: www.softintegration.com Language: English - Date: 2004-10-25 19:49:06 Matrices Algebra of random variables Summary statistics Variance Covariance Normal distribution Matrix Linear discriminant analysis Multivariate normal distribution Statistics Covariance and correlation Data analysis
95	g01 – Simple Calculations on Statistical Data g01nbc NAG C Library Function Document nag_moments_ratio_quad_forms (g01nbc) Add to Reading List Source URL: www.softintegration.com Language: English - Date: 2004-10-25 19:49:07 Regression analysis Probability and statistics Matrices Matrix Normal distribution Multivariate normal distribution Least squares Symmetric matrix Statistics Mathematical analysis Mathematical optimization
96	This is page 365 Printer: Opaque this Chapter 15 Cluster-Weighted Modeling: Probabilistic Time Series Prediction, Characterization Add to Reading List Source URL: www.cba.mit.edu Language: English - Date: 2011-12-13 18:32:02 Estimation theory Regression analysis Statistical theory Cluster-weighted modeling Expectation–maximization algorithm Gaussian function Normal distribution Covariance matrix Generalized linear model Statistics Multivariate statistics Data analysis
97	MATHPartial solutions for practice problems for week 9 These are practice problems for the material discussed in lecture on Wednesday, Nov. 12, 2014. These problems will not be collected. 1. For each of the fo Add to Reading List Source URL: hkumath.hku.hk Language: English - Date: 2014-11-13 19:46:42 Matrix theory Eigenvalues and eigenvectors Generalized eigenvector Characteristic polynomial Jordan normal form Vector space Matrix Jordan matrix Cayley–Hamilton theorem Algebra Linear algebra Mathematics
98	EE103 (FallQR factorization • solving the normal equations • QR factorization Add to Reading List Source URL: www.seas.ucla.edu Language: English - Date: 2011-10-14 12:42:11 Numerical linear algebra QR decomposition Cholesky decomposition Factorization Kernel Triangular matrix Algebra Linear algebra Mathematics
99	Muscas et al. EURASIP Journal on Advances in Signal Processing:17 DOIs13634RE SE A RCH Open Access Add to Reading List Source URL: asp.eurasipjournals.com Language: English Estimation theory Parametric statistics Signal processing Linear least squares Matrix Ordinary least squares Topology Covariance Normal distribution Statistics Regression analysis Least squares
100	Diagonal and Low-Rank Decompositions and Fitting Ellipsoids to Random Points James Saunderson, Pablo A. Parrilo, Alan S. Willsky Abstract— Identifying a subspace containing signals of interest in additive noise is a ba Add to Reading List Source URL: www.mit.edu Language: English - Date: 2014-08-14 16:44:12 Singular value decomposition Matrix theory Operator theory Ellipsoid Positive-definite matrix Matrix Eigenvalues and eigenvectors Rank Normal distribution Algebra Mathematics Linear algebra

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