Generating Totally Positive Toeplitz Matrix from an Upper Bidiagonal Matrix ()
Received 17 September 2015; accepted 29 November 2015; published 2 December 2015


1. Introduction
Total positive matrices arise in many areas in mathematics, and there has been considerable interest lately in the study of these matrices. For background information see the most important survey in this field by T. Ando [1] . See also [2] .
A matrix A is said to be totally positive, if every square submatrix has positive minors and A is said to be totally nonnegative, and if every square submatrix has nonnegative minors. While it is well known that many of the nontrivial examples of totally positive matrices are obtained by restricting certain kernels to appropriate finite subsets of R (see, for example, Ando ( [1] , p. 212) or Pinkus ( [3] , p. 2). For Toeplitz matrices, that is, ma-
trices of the form
a complete characterization of the total positivity, in terms of certain entire
functions, has been studied in a series of references by Ando [1] , Pinkus [3] and S.M. Fallat, C.R. Johnson [4] .
Expressing a matrix as a product of lower triangle matrix L and an upper triangle matrix U is called a LU factorization. Such factorization is typically obtained by reducing a matrix to an upper triangular matrix from via row operation, that is, Gaussian elimination.
The primary purpose of this paper is to provide a new totally positive matrix generated from a totally nonnegative one and to construct its factorization.
The organization of our paper is as follows. In Section 2, we introduce our notation and give some auxiliary results which we use in the subsequent sections. In Section 3, we recall from [3] the Toeplitz matrices speci-
fied for the case
, on which our proofs heavily rely. In Section 4, we present the proofs of our main
results. In last section, we present the factorization of this resulted matrix.
2. Notation and Auxiliary Results
2.1. Notations
In this subsection we introduce the notation that will be used in developing the paper. For
we denote by
the set of all strictly increasing sequences of k integers chosen from
. For
, we denote by
the
submatrix of A contained in the rows indexed by
and columns indexed by
. A matrix A is called totally positive (abbreviated TP henceforth) and totally nonnegative (abbreviated TN) if
and
, respectively, for all
. If a totally nonnegative matrix is also nonsingular, we write NsTN.
Definition 2.1.1 [3]
A square lower (upper) triangular matrix A is called lower (upper) triangular positive matrix, denoted LTP (UTP), if for all
and for
with the property that
(
) for
, then
.
Let I be the square identity matrix of order n, and for
, we let
be the square standard basis matrix whose only nonzero entry is 1 that occurs in the
position.
A tridiagonal matrix that is also upper (lower) triangular is called an upper (lower) bidiagonal matrix. Statements referring to just triangular or bidiagonal matrices without the adjectives “upper” or “lower” may be applied to either case.
2.2. Auxiliary Results
We use the following classic formula known as Cauchy-Binet formula and stated in the theorem below.
Theorem 2.2.1 (Cauchy-Binet formula) ( [4] , p. 27). Let A be an
matrix and B be an
matrix then for each pair of indexed sets
and
of cardinality k, where
, we have
![]()
The following remarkable result is one of the most important and useful results in the study of TN matrices. This result first appeared in [5] see also [1] for another proof of this fact.
Theorem 2.2.2. Let
be a square matrix of order n. Then A is NsTN if and only if A has an LU
factorization, such that both L and U are NsTN square matrices.
Using this theorem and Cauchy-Binet formula we have the following corollary.
Corollary 2.2.3 [6] . Let
be a square matrix of order n. Then A is TP if and only if A has an LU
factorization, such that both L and U are TP square matrices.
We have the following theorem to prove both L and U are totally positive.
Theorem 2.2.4. Let
be an upper triangular square matrix of order n satisfying
for,
Then U is UTP (upper totally positive). Similarly, if
is an lower triangular square matrix of order
n satisfying
for
,
. Then L is LTP (lower totally positive).
In the sequel we will make use the the following lemma, see, e.g. [7] .
Lemma 2.2.5 (Sylvester Identity)
Partition square matrix T of order n,
, as:
,
where
square matrix of order
and
and
are scalars. Define the submatrices
![]()
Then if
is non singular
![]()
3. Toeplitz Matrices
Assuming we are given a finite sequence
of distinct real numbers, the associated To-
eplitz matrix is defined by
or
. If we are given a one-sided finite sequence
,
then we understand this to mean that
in the above definition. Sequences that give rise to totally positive Toeplitz matrices have been totally characterized in terms of their generating functions, i.e. re-
presentations of
.
In our case, the normalization
, the sequence
gives rise to a totally positive Toeplitz matrix
if and only if
has the form
![]()
where
.
Now consider the polynomial
, the upper triangular Toeplitz matrix
![]()
is TP.
4. Generating New Form of Toeplitz Matrix
4.1. Main Result
Now we formalize the structure of our result by the following theorem.
Theorem 4.1.1. Assume that we are given the sequence
of
distinct positive real numbers.
Define the upper bidiagonal matrix
by
![]()
That is the sequence
lies on the superdiagonal. Then the matrix T defined as
![]()
is TP.
Proof
To prove this result we must note that
![]()
where
is upper triangular matrix and
is lower triangular matrix. By corollary 2.2.3 A is TP if both U and L are TP.
So, want to prove
is upper TP.
![]()
By Theorem 2.2.4 U is TP if
![]()
where
which is positive and
![]()
Since its submatrix of Toeplitz matrix.
Illustrative Example
Let we have the following sequence of distinct positive real numbers 1, 4, 3.
Define the matrix A as:
![]()
Then the matrix function
![]()
is TP.
4.2. Properties
1) Note that
since
and
![]()
Using this property we prove the following lemma
Lemma 4.2.1. The matrix T, as defined above has the following property
![]()
where
and
are defined in Lemma 2.2.5.
Proof
The statement follows by Lemma 2.2.5 and the idea of
.
2) Let P denote the square matrix of order n permutation matrix by the permutation
,
, and suppose T is a square TP Toeplitz matrix. Then
is TP too (see
[7] ). Moreover,
is TP, where S is diagonal matrix with diagonal entries alternately 1 and -1.
3) The Hadamrd product of two TP toeplitz matrices is TP matrix too, that is if we are given two square TP
matrices
and
of order n. Then the Hadamard product
is TP.
5. Factorization
5.1. Construct New Factorization
Our aim is to write the new TP Toeplitz matrix T as a product of elementary matrices of a special form. For any
, we let
to be the elementary lower matrix whose entries are defined by
![]()
Note that
can be written as
, where I is square identity matrix of order n and
is square matrix of order n whose non-zero entry is a 1 in the
position n. Also, notice that
.
We use the elementary matrices
to reduce Lower diagonal matrix to identity matrix.
For example, we can consider the following
Lower diagonal matrix L
![]()
It can be factorized as
![]()
5.2. General Characterization
We begin a definition and a result that characterize the TP Toeplitz matrix T in terms of the elementary matrices
.
Theorem 5.2.1. Any square Toeplitz matrix of oreder n,
can be written as
![]()
That is, ![]()
Illustrative Example
Let
![]()
The matrix in this example can be factorized as
![]()
Note that the number of the factored matrices equal
![]()