We study the limiting spectral measure of large symmetric random matrices of linear
algebraic structure. For Hankel and Toeplitz matrices generated by iid random variables X k …

The author presents a unified treatment of this highly interdisciplinary topic to help define the
notion of cognitive radio. The book begins with addressing issues such as the fundamental …

Harmonic decompositions of multivariate time series are considered for which we adopt an
integral operator approach with periodic semigroup kernels. Spectral decomposition …

Consider the ensemble of real symmetric Toeplitz matrices whose entries are iid random
variable from a fixed probability distribution p of mean 0, variance 1, and finite moments of …

Large dimensional random matrices (LDRM) with specific patterns arise in econometrics,
computer science, mathematics, physics, and statistics. This book provides an easy initiation …

Suppose that T_n is a Toeplitz matrix whose entries come from a sequence of independent
but not necessarily identically distributed random variables with mean zero. Under some …

Circulant matrices have been around for a long time and have been extensively used in
many scientific areas. This book studies the properties of the eigenvalues for various types …

The methods to establish the limiting spectral distribution (LSD) of large dimensional
random matrices includes the well known moment method which invokes the trace formula …

Circulant matrices play an important role in solving ordinary and partial differential
equations. In this paper, by using the inverse factorization of polynomial of degree n, the …

We first discuss the convergence in probability and in distribution of the spectral norm of
scaled Toeplitz, circulant, reverse circulant, symmetric circulant, and a class of k-circulant …