random matrices
Properties of sparse random matrices over finite fields
... Random matrices are ubiquitous in many branches of the natural sciences and mathematics ranging from biology to computer science, nuclear physics and quantum ...real matrices, while the restriction ...
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Typical kernel size and number of sparse random matrices over Galois fields: a statistical physics approach
... Random matrices are a well studied topic in the physics community where they are important in a range of applications from classical physics to quantum ...the matrices. Also, in most cases, the ...
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On Marginal Distributions of the Ordered Eigenvalues of Certain Random Matrices
... important random matrices, especially those in the summary above, share a common structure on the joint distributions of their (nonzero) ...pseudo-Wishart matrices with only a single ...
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Universal hypotrochoidic law for random matrices with cyclic correlations
... of random matrices with correlations between off-diagonal pairs of elements, having applications to a wide range of physical and biological ...to random matrices exhibiting higher-order cyclic ...
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Universal hypotrochoidic law for random matrices with cyclic correlations
... of random matrices with correlations between off-diagonal pairs of elements, having applications to a wide range of physical and biological ...to random matrices exhibiting higher-order cyclic ...
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Statistical properties of eigenvectors and eigenvalues of structured random matrices
... such random matrices have been studied recently and a number of very general results have been derived (see [5, 6] and references therein), however much less is known about their eigenvectors ...
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Neutrino mass priors for cosmology from random matrices
... Cosmological measurements of structure are placing increasingly strong constraints on the sum of the neutrino masses, Σ m ν , through Bayesian inference. Because these constraints depend on the choice for the prior ...
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Sparsity estimation from compressive projections via sparse random matrices
... In this paper, we have proposed an iterative algorithm for the estimation of the signal sparsity starting from compressive and noisy projections obtained via sparse random matrices. As a first theoretical ...
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On the distribution of the maximum value of the characteristic polynomial of GUE random matrices
... limiting random vari- able u above appears to be more complicated than its CUE ...for matrices of size N = 3000 and around 250 000 ...Hermitian random matrices with independent entries taken ...
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Central limit theorems for the real eigenvalues of large Gaussian random matrices
... In addition to being of instrinsic mathematical interest, the statistics of non-Hermitian ma- trices also have important applications. The earliest such application is probably due to May [26] who showed that real ...
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Concentration Inequalities of Random Matrices and Solving Ptychography with a Convex Relaxation
... self-adjoint random matrices under various ...the random matrices are bounded and is a matrix version of Hoeffding’s ...the random matrices, one can also use the matrix vari- ...
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Distributions of Ratios: From Random Variables to Random Matrices
... two random quantities is frequently encountered in probability and ...definite random matrices, this ratio can take various forms and its distribution, and even its defini- tion, can offer many ...
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Random matrices, large deviations and reflected Brownian motion
... to random matrix theory on the one hand and the study of the KPZ equa- tion [58], which was proposed to describe a class of surface growth models, on the ...
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Random Matrix Approach to Correlation Matrix of Financial Data (Mexican Stock Market Case)
... data matrices can be analyzed in the same way as for random ...and random matrices, lead us forward in the possible innovation of these tools inside a lot of knowledge ...
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Random discrete groups in the space of Möbius transformations : a thesis presented in partial fulfillment of the requirements for the degree of Master of Science in Mathematics at Massey University, Albany, New Zealand
... of random matrices in SL(2, R ) from multiple sets of 1, 000, 000 matri- ces in zero centred GL(2, R ) is considered ...of matrices in SL(2, R ) generated from matrices in GL(2, R ) having ...
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On the number of zeros of linear combinations of independent characteristic polynomials of random unitary matrices
... of random matrix theory and analytic number theory that can be considered as evidence for the zeros of the Riemann zeta function being statistically distributed as eigenvalues of large random ...
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Selection Criteria of Measurement Matrix for Compressive Sensing Based Medical Image Reconstruction
... Gaussian random matrices, Bernoulli random matrices, Partial orthogonal random matrices, Partial Hadamard matrices, Toeplitz matrices, and QC_LDPC matrices ...
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Compressive sensing for sparse approximations: constructions, algorithms, and analysis
... of random matrices used nowadays in compressive sensing, for example, random Gaussian matrices, random Bernoulli matrices, or random mi- nors of a discrete Fourier ...
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High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency
... The approach taken in this paper is to find rates which γ (as a function of n, p, k) can safely tend towards zero while maintaining the same statistical efficiency as dense random matrices. In various ...
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Secular determinants of random unitary matrices
... Floquet matrices of the type (62), defined by a whole set of values for the various control parameters, is faithful to the prediction based on the circular ensemble of random matrices of the same ...
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