Subgaussian Random Variables and Symmetric Matrices
Nonuniform sparse recovery with subgaussian matrices
... -minimization. Random matrices have become a popular choice for the measurement ...such matrices. In this note we focus on nonuniform recovery using subgaussian random matrices ...
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Distributions of Ratios: From Random Variables to Random Matrices
... chi-square variables, which are special cases of the gamma ...two random matrices, and also the ratio of their determinants, so that some inference using a statistic based on the latter ratio, can be ...
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Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables
... Throughout the sections 2 and 3 we suppose that { X n , n ≥ 1 } is a sequence of ND subgaussian random variables. Since some proofs are the same as Mikosch [7], we abbreviate them. In fact we obtain ...
5
Exact Random Generation of Symmetric and Quasi-symmetric Alternating-sign Matrices
... generate random ASMs with prescribed symmetry conditions, and some results with moderate size are presented in Figure ...uniform random ASMs, though Colomo and Pronko [2] recently announced a partial proof ...
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Arithmetic Operations Of Symmetric Trapezoidal Fuzzy Random Variables
... term symmetric trapezoidal fuzzy random variable with mean μ and standard deviation σ respectively and that we discuss about the membership functions of arithmetic operations between two symmetric ...
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Inference for Eigenvalues and Eigenvectors in Exponential Families of Random Symmetric Matrices.
... of symmetric random matrix using MLE and LRT, since this assumption has all the convenience of parametric models in terms of analytic expressions and can be efficiently applied to each of tens of thou- ...
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Random projections on manifolds of Symmetric Positive Definite matrices for image classification
... through Symmetric Positive Definite (SPD) matrices and then inter- preting such matrices as points on Riemannian manifolds can lead to increased classification ...SPD matrices to be used with ...
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Random projections on manifolds of symmetric positive definite matrices for image classification
... through Symmetric Positive Definite (SPD) matrices and then inter- preting such matrices as points on Riemannian manifolds can lead to increased classification ...SPD matrices to be used with ...
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Statistical Analysis of Random Symmetric Positive Definite Matrices Via Eigen-Decomposition
... SPD matrices X and Y is defined as the minimal amount of rotation of axes and scaling of axis lengths necessary to defom the ellipsoid associated with X into the ellipsoid associated with Y ...
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Approximations for sums of three-valued 1-dependent symmetric random variables
... 1-dependent variables, total variation norm, local norm, nonuniform ...dependent random variables (rvs), it is typical to assume their nonnegativeness, for example, see [4, 14, 19, ...
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Finite size effects in the averaged eigenvalue density of Wigner random-sign real symmetric matrices
... Wigner random sign real symmetric N x N matrices to order 1/N are in fine obtained ...size matrices numerical diagonalization results exhibits an excellent agreement, confirming the ...
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VARIATIONS ON A THEME OF SYMMETRIC TROPICAL MATRICES
... x i,p x j,q x k,r + x i,q x j,r x k,p + x i,r x j,p x k,q − x i,p x j,r x k,q − x i,q x j,p x k,r − x i,r x j,q x k,p . Suppose, given the symmetry of the n × n matrix of variables, that two of these monomials are ...
141
The spectrum of random permutation matrices
... Example 4.1.4. If f is in the Sobolev space H s , for s > 1, and if one assumes that the even part of f is not a constant, then the conclusions of Theorem 2.1.1 hold. Remark 4.1.4.1. In a recent work by Hughes, ...
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On Polynomial Symmetric and Polynomial Skew Symmetric Matrices
... of symmetric and skew symmetric matrices are extended to polynomial symmetric and polynomial skew symmetric ...polynomial symmetric and polynomial skew symmetric ...
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k Kernel Symmetric Matrices
... kernel symmetric matrices. It is shown that k-symmetric implies k-Kernel symmetric but the converse need not be ...-Kernel symmetric fuzzy ...
8
Random Correlation Matrices
... Given a bijective vectorial Boolean function Z~ -1- Z~, define the cor- relation matrix P as an N x N matrix, N = 2 n - 1, whose entries are given as the squar[r] ...
10
Spectra of random matrices
... It has been used “small” matrices of S = 40 size and the spectral density has been obtained averaging over 20 samples. 900 points have been used to build the bi-dimensional surface of fig. 3.2a. In fig.3.2b is ...
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Binomial Random Variables. Binomial Distribution. Examples of Binomial Random Variables. Binomial Random Variables
... experiment n times independently and observing the number x of times that one of the two outcomes occurs This x is a Binomial Random Variable We can exploit this by using known?.[r] ...
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Random Variables. Chapter 2. Random Variables 1
... Roulette and Random Variables A Roulette wheel has 38 pockets. 18 of them are red and 18 are black; these are numbered from 1 to 36. The two remaining pockets are green and are numbered 0 and 00. The wheel ...
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Computing eigenvalues of normal matrices via complex symmetric matrices
... the symmetric singular value decomposition (SSVD), also called Autonne-Takagi factorization [12, 18], of this complex symmetric ...normal matrices [9, 17, 19] is used, in order to annihilate the last ...
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