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Normal matrix
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21	cs281: Computer Organization Lab3 Prelab Our objective in this prelab is to lay the groundwork for simplifying boolean expressions in order to minimize the complexity of the resultant digital logic circuit. We saw in La Add to Reading List Source URL: personal.denison.edu Language: English - Date: 2015-11-10 08:26:31 Boolean algebra Canonical normal form Karnaugh map Distributive property Truth table Equivalence of categories Integer Boolean function Equality Matrix Addition Negation
22	Incremental Learning for Robust Visual Tracking ∗ David A. Ross∗ Jongwoo Lim† Ruei-Sung Lin‡ Ming-Hsuan Yang† University of Toronto † Honda Research Institute, USA ‡ Motorola Labs Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2007-08-14 20:46:19 Linear algebra Multivariate statistics Matrix theory Dimension reduction Numerical linear algebra Singular value decomposition Covariance Principal component analysis Normal distribution Kalman filter Linear discriminant analysis Eigenvalues and eigenvectors
23	161 Documenta Math. C ∗ -Algebras Add to Reading List Source URL: documenta.sagemath.org Language: English - Date: 2008-08-03 09:00:13 C-algebras Operator theory Approximately finite-dimensional C-algebra Bratteli diagram Von Neumann algebra Linear algebra Matrix theory -ring Jordan normal form
24	JMLR: Workshop and Conference Proceedings vol 40:1–40, 2015 28th Annual Conference on Learning Theory Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-07-20 20:08:36 Probability distributions Clique problem Expected value Planted clique Matrix Markov chain Normal distribution
25	A Semiparametric Model for Heterogeneous Panel Data with Fixed Effects Lena K¨orber∗ London School of Economics and Bank of England Oliver Linton† Add to Reading List Source URL: www.statistik.uni-bonn.de Language: English - Date: 2015-10-23 03:54:08 Regression analysis Estimation theory Statistical theory Econometrics Parametric statistics Instrumental variable Linear regression Matrix Fixed effects model Degrees of freedom Normal distribution Covariance
26	Iowa End-of-Course Assessment Programs Spring 2010 Results Iowa End-of-Course Assessments (IEOC) Ten end-of-course assessments in Algebra 1, Algebra 2, Biology, Chemistry, Geometry, Matrix Add to Reading List Source URL: itp.education.uiowa.edu Language: English - Date: 2016-08-17 11:02:44 Algebra Polynomial Normal distribution
27	arXiv:0806.3188v1 [math.PR] 19 JunExistence of a critical point for the infinite divisibility of squares of Gaussian vectors in R2 with non–zero mean Michael B. Marcus Jay Rosen Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-01-07 21:06:47 Probability distributions Normal distribution Infinite divisibility NC Matrix
28	Affine invariant analysis of multivariate shape variation, with an example from human craniofacial growth Philipp Mitteroecker Department of Theoretical Biology, University of Vienna While the variation of observations a Add to Reading List Source URL: theoretical.univie.ac.at Language: English - Date: 2015-07-12 11:12:09 Probability distributions Stable distributions Covariance and correlation Multivariate statistics Eigenvalues and eigenvectors Linear algebra Principal component analysis Multivariate normal distribution Covariance matrix Variance Morphometrics Invariant
29	Spectral Properties of Random Unitary Band Matrices by Brian Z. Simanek Mihai Stoiciu, Advisor Add to Reading List Source URL: sites.williams.edu Language: English - Date: 2012-08-22 10:38:25 Operator theory Linear algebra Matrices Unitary operators Matrix theory Spectral theorem Unitary matrix Self-adjoint operator Matrix Hilbert space Circular ensemble Normal matrix
30	Measuring correlation risk Roza Galeeva, Jiri Hoogland, Alexander Eydeland CMG, Morgan Stanley January 11, 2007 Contents Add to Reading List Source URL: www.bbk.ac.uk Language: English - Date: 2007-03-27 13:47:21 Covariance and correlation Correlation and dependence Cholesky decomposition Multivariate normal distribution Covariance Eigenvalues and eigenvectors Matrix Bootstrapping Pearson product-moment correlation coefficient Partial correlation