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1 Matrix Algebra and Random Vectors Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication/ Graduate Institute of Networking and Multimedia
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2 General Statistical Distance
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4 Quadratic Form
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5 Statistical Distance under Rotated Coordinate System
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6 Rotated Coordinate System
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7 Coordinate Transformation
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8 Quadratic Form in Transformed Coordinate Systems
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9 Diagonalized Quadratic Form
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10 Orthogonal Matrix
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11 Diagonalization
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12 Concept of Mapping x
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13 Eigenvalues
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14 Eigenvectors
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15 Spectral Decomposition
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16 Positive Definite Matrix Matrix A is non-negative definite if for all x ’ =[ x 1, x 2, …, x k ] for all x ’ =[ x 1, x 2, …, x k ] Matrix A is positive definite if for all non-zero x for all non-zero x
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17 Positive Definite Matrix
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18 Inverse and Square-Root Matrix
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19 Random Vectors and Random Matrices Random vector –Vector whose elements are random variables Random matrix –Matrix whose elements are random variables
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20 Expected Value of a Random Matrix
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21 Population Mean Vectors
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22 Covariance
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23 Statistically Independent
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24 Population Variance-Covariance Matrices
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25 Population Correlation Coefficients
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26 Standard Deviation Matrix
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27 Correlation Matrix from Covariance Matrix
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28 Partitioning Covariance Matrix
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29 Partitioning Covariance Matrix
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30 Linear Combinations of Random Variables
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31 Example of Linear Combinations of Random Variables
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32 Linear Combinations of Random Variables
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33 Sample Mean Vector and Covariance Matrix
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34 Partitioning Sample Mean Vector
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35 Partitioning Sample Covariance Matrix
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36 Cauchy-Schwarz Inequality
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37 Extended Cauchy-Schwarz Inequality
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38 Maximization Lemma
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39 Maximization of Quadratic Forms for Points on the Unit Sphere
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40 Maximization of Quadratic Forms for Points on the Unit Sphere
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41 Maximization of Quadratic Forms for Points on the Unit Sphere
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42 Maximization of Quadratic Forms for Points on the Unit Sphere
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