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On Some Matrix Trace Inequalities
Journal of Inequalities and Applications volume 2010, Article number: 201486 (2010)
Abstract
We first present an inequality for the Frobenius norm of the Hadamard product of two any square matrices and positive semidefinite matrices. Then, we obtain a trace inequality for products of two positive semidefinite block matrices by using block matrices.
1. Introduction and Preliminaries
Let denote the space of
complex matrices and write
. The identity matrix in
is denoted
. As usual,
denotes the conjugate transpose of matrix
. A matrix
is Hermitian if
. A Hermitian matrix
is said to be positive semidefinite or nonnegative definite, written as
, if


is further called positive definite, symbolized , if the strict inequality in (1.1) holds for all nonzero
. An equivalent condition for
to be positive definite is that
is Hermitian and all eigenvalues of
are positive real numbers. Given a positive semidefinite matrix
and
,
denotes the unique positive semidefinite
power of
.
Let and
be two Hermitian matrices of the same size. If
is positive semidefinite, we write

Denote and
eigenvalues and singular values of matrix
, respectively. Since
is Hermitian matrix, its eigenvalues are arranged in decreasing order, that is,
and if
is any matrix, its singular values are arranged in decreasing order, that is,
The trace of a square matrix
(the sum of its main diagonal entries, or, equivalently, the sum of its eigenvalues) is denoted by
.
Let be any
matrix. The Frobenius (Euclidean) norm of matrix
is

It is also equal to the square root of the matrix trace of that is,

A norm on
is called unitarily invariant
for all
and all unitary
.
Given two real vectors and
in decreasing order, we say that
is weakly log majorized by
, denoted
, if
, and we say that
is weakly majorized by
, denoted
, if
. We say
is majorized by
denoted by
, if

As is well known, yields
(see, e.g., [1, pages 17–19]).
Let be a square complex matrix partitioned as

where is a square submatrix of
. If
is nonsingular, we call

the Schur complement of in
(see, e.g., [2, page 175]). If
is a positive definite matrix, then
is nonsingular and

Recently, Yang [3] proved two matrix trace inequalities for positive semidefinite matrices and
,

for
Also, authors in [4] proved the matrix trace inequality for positive semidefinite matrices and
,

where is a positive integer.
Furthermore, one of the results given in [5] is

for and
positive definite matrices, where
is any positive integer.
2. Lemmas
Lemma 2.1 (see, e.g., [6]).
For any and
.
Lemma 2.2 (see, e.g., [7]).
Let then

Lemma 2.3 (Cauchy-Schwarz inequality).
Let and
be real numbers. Then,

Lemma 2.4 (see, e.g., [8, page 269]).
If and
are poitive semidefinite matrices, then,

Lemma 2.5 (see, e.g., [9, page 177]).
Let and
are
matrices. Then,

Lemma 2.6 (see, e.g., [10]).
Let and
are positive semidefinite matrices. Then,

where is a positive integer.
3. Main Results
Horn and Mathias [11] show that for any unitarily invariant norm on

Also, the authors in [12] show that for positive semidefinite matrix , where

for all and all unitarily invariant norms
.
By the following theorem, we present an inequality for Frobenius norm of the power of Hadamard product of two matrices.
Theorem 3.1.
Let and
be
-square complex matrices. Then

where is a positive integer. In particular, if
and
are positive semidefinite matrices, then

Proof.
From definition of Frobenius norm, we write

Also, for any and
, it follows that (see, e.g., [13])


Since for
and from inequality (3.7), we write

From Lemma 2.1 and Cauchy-Schwarz inequality, we write

By combining inequalities (3.7), (3.8), and (3.9), we arrive at

Thus, the proof is completed. Let and
be positive semidefinite matrices. Then

where .
Theorem 3.2.
Let be positive semidefinite matrices. For positive real numbers

Proof.
Let

We know that , then by using the definition of Frobenius norm, we write

Thus, by using Theorem 3.1, the desired is obtained.
Now, we give a trace inequality for positive semidefinite block matrices.
Theorem 3.3.
Let

then,

where is an integer.
Proof.
Let

with . Then
(see, e.g., [14]). Let

with ,
,
. Then
(see, e.g., [14]). We know that

By using Lemma 2.2, it follows that

Therefore, we get

As result, we write

Example 3.4.
Let

Then From inequality (1.11), for
we get

Also, for , since
and
, we get

Thus, according to this example from (3.24) and (3.25), we get

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Acknowledgment
This study was supported by the Coordinatorship of Selçuk University's Scientific Research Projects (BAP).
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Ulukök, Z., Türkmen, R. On Some Matrix Trace Inequalities. J Inequal Appl 2010, 201486 (2010). https://doi.org/10.1155/2010/201486
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DOI: https://doi.org/10.1155/2010/201486