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Toeplitz and Circulant Matrices: A Review
Toeplitz and Circulant Matrices: A review
t 0 t 1 t 2
···
t ( n− 1)
t 1 t 0 t 1
t 2 t 1 t 0
.
. . .
.
t n− 1
···
t 0
Robert M. Gray
Information Systems Laboratory
Department of Electrical Engineering
Stanford University
Stanford, California 94305
Revised March 2000
This document available as an
Adobe portable document format (pdf) file at
http://www-isl.stanford.edu/~gray/toeplitz.pdf
c
Robert M. Gray, 1971, 1977, 1993, 1997, 1998, 2000.
The preparation of the original report was financed in part by the National
Science Foundation and by the Joint Services Program at Stanford. Since then it
has been done as a hobby.
ii
Abstract
In this tutorial report the fundamental theorems on the asymptotic be-
havior of eigenvalues, inverses, and products of “finite section”Toeplitz ma-
trices and Toeplitz matrices with absolutely summable elements are derived.
Mathematical elegance and generality are sacrificed for conceptual simplic-
ity and insight in the hopes of making these results available to engineers
lacking either the background or endurance to attack the mathematical lit-
erature on the subject. By limiting the generality of the matrices considered
the essential ideas and results can be conveyed in a more intuitive manner
without the mathematical machinery required for the most general cases. As
an application the results are applied to the study of the covariance matrices
and their factors of linear models of discrete time random processes.
Acknowledgements
The author gratefully acknowledges the assistance of Ronald M. Aarts of
the Philips Research Labs in correcting many typos and errors in the 1993
revision, Liu Mingyu in pointing out errors corrected in the 1998 revision,
Paolo Tilli of the Scuola Normale Superiore of Pisa for pointing out an in-
correct corollary and providing the correction, and to David Neuhoff of the
University of Michigan for pointing out several typographical errors and some
confusing notation.
Contents
1 Introduction
3
2 The Asymptotic Behavior of Matrices
5
3 Circulant Matrices
15
4 Toeplitz Matrices 19
4.1 Finite Order Toeplitz Matrices . . ................ 23
4.2 Toeplitz Matrices ......................... 28
4.3 Toeplitz Determinants . ..................... 45
5 Applications to Stochastic Time Series 47
5.1 Moving Average Sources ..................... 48
5.2 Autoregressive Processes ..................... 51
5.3 Factorization . . ......................... 54
5.4 Differential Entropy Rate of Gaussian Processes ........ 57
Bibliography
58
1
2
CONTENTS
Chapter 1
Introduction
A toeplitz matrix is an n
×
n matrix T n = t k,j where t k,j = t k−j , i.e., a matrix
of the form
t 0 t 1 t 2
···
t ( n− 1)
t 1 t 0 t 1
t 2 t 1 t 0
T n =
.
.
.
(1.1)
. . .
t n− 1
···
t 0
Examples of such matrices are covariance matrices of weakly stationary
stochastic time series and matrix representations of linear time-invariant dis-
crete time filters. There are numerous other applications in mathematics,
physics, information theory, estimation theory, etc. A great deal is known
about the behavior of such matrices — the most common and complete ref-
erences being Grenander and Szego [1] and Widom [2]. A more recent text
devoted to the subject is Bottcher and Silbermann [15]. Unfortunately, how-
ever, the necessary level of mathematical sophistication for understanding
reference [1] is frequently beyond that of one species of applied mathemati-
cian for whom the theory can be quite useful but is relatively little under-
stood. This caste consists of engineers doing relatively mathematical (for an
engineering background) work in any of the areas mentioned. This apparent
dilemma provides the motivation for attempting a tutorial introduction on
Toeplitz matrices that proves the essential theorems using the simplest possi-
ble and most intuitive mathematics. Some simple and fundamental methods
that are deeply buried (at least to the untrained mathematician) in [1] are
here made explicit.
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