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volume 7, issue 5, article 195, 2006.

Received 21 July, 2005;

accepted 10 May, 2006.

Communicated by:F. Zhang

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Journal of Inequalities in Pure and Applied Mathematics

ON THE BOUNDS FOR THE SPECTRAL AND `_p NORMS OF THE KHATRI-RAO PRODUCT OF CAUCHY-HANKEL MATRICES

HACI CIVCIV AND RAMAZAN TÜRKMEN

Department of Mathematics Faculty of Art and Science, Selcuk University

42031 Konya, Turkey

EMail:hacicivciv@selcuk.edu.tr EMail:rturkmen@selcuk.edu.tr

c

2000Victoria University ISSN (electronic): 1443-5756 223-05

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On the Bounds for the Spectral and`pNorms of the Khatri-Rao

Product of Cauchy-Hankel Matrices

Hacı Civciv and Ramazan Türkmen

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J. Ineq. Pure and Appl. Math. 7(5) Art. 195, 2006

Abstract

In this paper we first establish a lower bound and an upper bound for the

`_p norms of the Khatri-Rao product of Cauchy-Hankel matrices of the form Hn=[1/(g+ (i+j)h)]ⁿ_i,j=1forg= 1/2 andh= 1partitioned as

H_n=





H_n⁽¹¹⁾ H_n⁽¹²⁾ Hn⁽²¹⁾ Hn⁽²²⁾





whereHn^(ij)is theijth submatrix of ordermi×njwithHn⁽¹¹⁾=Hn−1. We then present a lower bound and an upper bound for the spectral norm of Khatri-Rao product of these matrices.

2000 Mathematics Subject Classification:15A45, 15A60, 15A69.

Key words: Cauchy-Hankel matrices, Kronecker product, Khatri-Rao product, Tracy- Singh product, Norm.

The authors thank Professor Fuzhen Zhang for his suggestions and the referee for his helpful comments and suggestions to improve our manuscript.

1. Introduction and Preliminaries

A Cauchy-Hankel matrix is a matrix that is both a Cauchy matrix (i.e. (1/(x_i− yj))ⁿ_i,j=1, xi 6=yj) and a Hankel matrix (i.e.(hi+j)ⁿ_i,j=1) such that

(1.1) H_n =

1 g+ (i+j)h

n i,j=1

,

wheregandh6= 0are arbitrary numbers andg/his not an integer.

Recently, there have been several papers on the norms of Cauchy-Toeplitz matrices and Cauchy-Hankel matrices [2,3,12,21]. Turkmen and Bozkurt [20]

have established bounds for the spectral norms of the Cauchy-Hankel matrix in the form (1.1) by taking g = 1/k and h = 1. Solak and Bozkurt [17]

obtained lower and upper bounds for the spectral norm and Euclidean norm of the Hn matrix that has given (1.1). Liu [9] established a connection between the Khatri-Rao and Tracy-Singh products, and present further results including matrix equalities and inequalities involving the two products and also gave two statistical applications. Liu [10] obtained new inequalities involving Khatri- Rao products of positive semidefinite matrices. Neverthless, we know that the Hadamard and Kronecker products play an important role in matrix methods for statistics, see e.g. [18,11,8], also these products are studied and applied widely in matrix theory and statistics; see, e.g., [18], [11], [1, 5, 22]. For partitioned matrices the Khatri-Rao product, viewed as a generalized Hadamard product, is discussed and used in [8], [6], [13, 14, 15] and the Tracy-Singh product, as a generalized Kronecker product, is discussed and applied in [7], [19].

The purpose of this paper is to study the bounds for the spectral and the`_p norms of the Khatri-Rao product of twon×n Cauchy-Hankel matrices of the

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form(1.1).In this section, we give some preliminaries. In Section2, we study the spectral norm and the`pnorms of Khatri-Rao product of twon×nCauchy- Hankel matrices of the form(1.1)and obtain lower and upper bounds for these norms.

LetAbe anym×nmatrix. The`_p norms of the matrixAare defined as

(1.2) kAk_p =

m

X

i=1 n

X

j=1

|a_ij|^p

!¹_p

1≤p < ∞ and also the spectral norm of matrixAis

kAk_s =q

1≤i≤nmaxλ_i,

where the matrix A ism×n andλ_i are the eigenvalues ofA^HA andA^H is a conjugate transpose of matrixA. In the casep = 2, the`₂ norm of the matrix A is called its Euclidean norm. ThekAk_s andkAk₂ norms are related by the following inequality

(1.3) 1

√nkAk₂ ≤ kAk_s. The Riemann Zeta function is defined by

ζ(s) =

∞

X

n=1

1 n^s

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for complex values of s. While converging only for complex numbers s with Res > 1, this function can be analytically continued on the whole complex plane (with a single pole ats= 1).

The Hurwitz’s Zeta functionζ(s, a)is a generalization of the Riemann’s Zeta functionζ(s)that also known as the generalized Zeta function. It is defined by the formula

ζ(s, a)≡

∞

X

k=0

1 (k+a)^s

for R[s] > 1 , and by analytic continuation to other s 6= 1, where any term with k +a = 0 is excluded. For a > −1, a globally convergent series for ζ(s, a)(which, for fixeda, gives an analytic continuation ofζ(s, a)to the entire complexs- plane except the points= 1) is given by

ζ(s, a) = 1 s−1

∞

X

n=0

1 n+ 1

n

X

k=0

(−1)^k n

k

(a+k)^1−s, see Hasse [4]. The Hurwitz’s Zeta function satisfies

ζ

s,1 2

=

∞

X

k=0

k+ 1

2 −s

= 2^s

∞

X

k=0

(2k+ 1)^−s

= 2^s

"

ζ(s)−

∞

X

k=1

(2k)^−s

#

= 2^s(1−2^−s)ζ(s) ζ

s,1

2

= (2^s−1)ζ(s).

(1.4)

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The gamma function can be given by Euler’s integral form Γ(z)≡

Z ∞ 0

t^z−1e^−tdt.

The digamma function is defined as a special function which is given by the logarithmic derivative of the gamma function (or, depending on the defini- tion, the logarithmic derivative of the factorial). Because of this ambiguity, two different notations are sometimes (but not always) used, with

Ψ(z) = d

dz ln [Γ(z)] = Γ^p(z) Γ(z)

defined as the logarithmic derivative of the gamma functionΓ(z), and F(z) = d

dz ln (z!)

defined as the logarithmic derivative of the factorial function. Thenth derivative Ψ(z)is called the polygamma function, denotedΨ(n, z). The notationΨ(n, z) is therefore frequently used as the digamma function itself. Ifa > 0andb any number andn ∈Z⁺ is positive integer, then

(1.5) lim

n→∞Ψ (a, n+b) = 0.

Consider matricesA = (a_ij)andC = (c_ij)of orderm×n andB = (b_kl) of order p ×q. Let A = (A_ij) be partitioned with A_ij of order m_i × n_j as the(i, j)th block submatrix and letB = (Bkl)be partitioned withBkl of order

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p_k×q_las the(k, l)th block submatrix (P

m_i = m,P

n_j = n,P

p_k = pand Pql =q). Four matrix products ofAandB, namely the Kronecker, Hadamard, Tracy-Singh and Khatri-Rao products, are defined as follows.

The Kronecker product, also known as tensor product or direct product, is defined to be

A⊗B = (a_ijB),

wherea_ij is theijth scalar element ofA= (a_ij), a_ijB is theijth submatrix of orderp×qandA⊗B is of ordermp×nq.

The Hadamard product, or the Schur product, is defined as AC = (aijcij),

wherea_ij, c_ij anda_ijc_ij are theijth scalar elements ofA= (a_ij), C = (c_ij)and AC respectively, andA, CandACare of orderm×n.

The Tracy-Singh product is defined to be

A◦B = (A_ij ◦B) with A_ij◦B = (A_ij ⊗B_kl)

whereA_ij is theijth submatrix of orderm_i×n_j, B_kl is theklth submatrix of orderp_k×q_l, A_ij ⊗B_klis theklth submatrix of orderm_ip_k×n_jq_l, A_ij ◦B is theijth submatrix of orderm_ip×n_jqandA◦B is of ordermp×nq.

The Khatri-Rao product is defined as

A∗B = (A_ij ⊗B_ij)

where A_ij is the ijth submatrix of orderm_i ×n_j, B_ij is the ijth submatrix of orderp_i×q_j, A_ij⊗B_ij is theijth submatrix of orderm_ip_i×n_jq_j andA∗Bis of order(P

mipi)×(P njqj).

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2. The spectral and `

_p

norms of the Khatri-Rao product of two n × n Cauchy-Hankel matrices

If we substituteg = 1/2andh= 1into theH_nmatrix(1.1), then we have

(2.1) H_n=

1

2 + (i+j) n

i,j=1

Theorem 2.1. Let the matrixH_n(n≥2)given in(2.1)be partitioned as

(2.2) H_n= Hn⁽¹¹⁾ Hn⁽¹²⁾

Hn⁽²¹⁾ Hn⁽²²⁾

!

whereHn^(ij)is theijth submatrix of ordermi ×nj withHn⁽¹¹⁾ =Hn−1. Then kH_n∗H_nk^p_p ≤2^2p

2 +

1 2 −2^−p

ζ(p−1)

−3

2 1−2^−p

ζ(p)−ln 2 2

+ 2^2p−3[1−ln 2]²+ 2

9 2p

. and

kHn∗Hnk^p_p

≥2^2p−4 1

2 −2^−p

ζ(p−1) −3

2 1−2^−p

ζ(p) + 1 2

+ 2 2

7 2p

. is valid wherek·k_p (3≤p < ∞)is`_p norm and the operation “∗” is a Khatri- Rao product.

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Proof. LetH_nbe defined by(2.1)partitioned as in(2.2). H_n∗H_n, Khatri-Rao product of twoHnmatrices, is obtained as

Hn∗Hn =





Hn⁽¹¹⁾⊗Hn⁽¹¹⁾ Hn⁽¹²⁾⊗Hn⁽¹²⁾

Hn⁽²¹⁾⊗Hn⁽²¹⁾ Hn⁽²²⁾⊗Hn⁽²²⁾



.

Using the`_pnorm and Khatri-Rao definitions one may easily computekH_n∗H_nk_p relative to the above

Hn^(ij⁾⊗Hn^(ij)

p

as shown in(2.3)

(2.3) kH_n∗H_nk^p_p =

2

X

i,j=1

H_n^(ij)⊗H_n^(ij⁾

p p

We may use the equality(1.2)to write H_n⁽¹¹⁾⊗H_n⁽¹¹⁾

p p =

"_n−1 X

i,j=1

1

2 +i+jp

#2

= 2^2p

"_n−1 X

k=1

k (2k+ 3)^p +

n−2

X

k=1

n−k−1 (2n+ 2k+ 1)^p

#2

= 2^2p

" _n X

k=2

k−1 (2k+ 1)^p +

n−2

X

k=1

n−k−1 (2n+ 2k+ 1)^p

!#2

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= 2^2p

"

1 2

n

X

k=1

1

(2k+ 1)^p−1 − 1 (2k+ 1)^p

(2.4)

−

n

X

k=1

1 (2k+ 1)^p +

n−2

X

k=1

n−k−1

(2n+ 2k+ 1)^p + 1

#2

. From(1.4), we obtain

∞

X

k=0

1

(2k+ 1)^p−1 − 1 (2k+ 1)^p

= 2^1−pζ

p−1,1 2

−2^−pζ

p,1 2

= (1−2^1−p)ζ(p−1)−(1−2^−p)ζ(p) (2.5)

Also, since

(2.6) lim

n→∞

n−2

X

k=1

n−k−1 (2n+ 2k+ 1)^p =







0, p >2

1

4(1−ln 2), p= 2 and from (1.4), (2.4), (2.5), (2.6), we have

(2.7)

H_n⁽¹¹⁾⊗H_n⁽¹¹⁾

p p

≤2^2p 1

2 −2^−p

ζ(p−1) −3

2 1−2^−p

ζ(p) + 2−ln 2 2

.

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Using(2.3)and(2.7)we can write kH_n∗H_nk^p_p

≤2^2p

2 + 1

2 −2^−p

ζ(p−1)−3

2 1−2^−p

ζ(p)−ln 2 2

+ 2

"_n−1 X

i=1

1

2 +i+np

#2

+

"

1

2 + 2np

#2

≤2^2p

2 + 1

2 −2^−p

ζ(p−1) −3

2 1−2^−p

ζ(p)−ln 2 2

(2.8)

+ 2^2p+1

"_n−1 X

i=1

n−i (2n+ 2i+ 1)^p

#2

+ 1

1

2 + 2n2p.

Thus, from(2.6)and(2.8)we obtain an upper bound forkH_n∗H_nk^p_psuch that (2.9) kH_n∗H_nk^p_p

≤2^2p

2 + 1

2−2^−p

ζ(p−1) −3

2 1−2^−p

ζ(p)−ln 2 2

+ 2^2p−3[1−ln 2]²+ 2

9 2p

. For the lower bound, if we consider inequality

H_n⁽¹¹⁾⊗H_n⁽¹¹⁾

p p ≥

"

2^p−2

n−1

X

k=1

k (2k+ 3)^p

#2

=

"

2^p−2

n

X

k=2

k−1 (2k+ 1)^p

#2

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= 2^2p−4 1

2 −2^−p

ζ(p−1)− 3

2 1−2^−p

ζ(p) + 1 2

and equalities (2.3), (2.5), then we have (2.10) kH_n∗H_nk^p_p ≥2^2p−4

1 2−2^−p

ζ(p−1)

−3

2 1−2^−p

ζ(p) + 1 2

+ 2 2

7 2p

. This is a lower bound forkHn∗Hnk^p_p. Thus, the proof of the theorem is com- pleted using(2.9)and(2.10).

Example 2.1. Let

α = 2^2p

2 + 1

2 −2^−p

ζ(p−1)

−3

2 1−2^−p

ζ(p)−ln 2 2

+ 2^2p−3[1−ln 2]² + 2

9 2p

β = 2^2p−4 1

2 −2^−p

ζ(p−1)− 3

2 1−2^−p

ζ(p) + 1 2

+ 2 2

7 2p

and order of H_n∗H_nmatrix isN.Thus, we have the following values:

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N β kH_n∗H_nk₃ α

2 0.1932680901 0.1943996774 2.034031369 5 0.1932680901 0.2486967434 2.034031369 10 0.1932680901 0.2949003201 2.034031369 17 0.1932680901 0.3250545239 2.034031369 26 0.1932680901 0.3460881969 2.034031369 37 0.1932680901 0.3615449198 2.034031369 50 0.1932680901 0.3733657155 2.034031369 65 0.1932680901 0.3826914230 2.034031369 81 0.1932680901 0.3902333553 2.034031369

N β kH_n∗H_nk₄ α

2 0.1347849117 0.1654942693 2.294793856 5 0.1347849117 0.2041337591 2.294793856 10 0.1347849117 0.2215153273 2.294793856 17 0.1347849117 0.2305342653 2.294793856 26 0.1347849117 0.2357826204 2.294793856 37 0.1347849117 0.2390987777 2.294793856 50 0.1347849117 0.2413257697 2.294793856 65 0.1347849117 0.2428929188 2.294793856 81 0.1347849117 0.2440372508 2.294793856

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N β kH_n∗H_nk₅ α

2 0.1218381759 0.1622386787 2.554705355 5 0.1218381759 0.1845312641 2.554705355 10 0.1218381759 0.1920519007 2.554705355 17 0.1218381759 0.1952045459 2.554705355 26 0.1218381759 0.1967458182 2.554705355 37 0.1218381759 0.1975855071 2.554705355 50 0.1218381759 0.1980810422 2.554705355 65 0.1218381759 0.1983919845 2.554705355 81 0.1218381759 0.1985968085 2.554705355

Now, we will obtain a lower bound and an upper bound for spectral norm of the Khatri-Rao product of twoH_nas in(2.1)and partitioned as in(2.2).

To minimize the numerical round-off errors in solving systemAx =b, it is normally convenient that the rows of Abe properly scaled before the solution procedure begins. One way is to premultiply by the diagonal matrix

(2.11) D= diag

α1

r₁(A), α2

r₂(A), . . . , αn

r_n(A)

,

where ri(A)is the Euclidean norm of theith row of Aand α1, α2, . . . , αn are positive real numbers such that

(2.12) α₁²+α₂²+· · ·+α²_n=n.

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Clearly, the euclidean norm of the coefficient matrix B = DA of the scaled system is equal to√

nand ifα1 =α2 =· · ·=αn = 1then each row ofB is a unit vector in the Euclidean norm. Also, we can defineB =AD,

(2.13) D= diag

α₁

c1(A), α₂

c2(A), . . . , α_n cn(A)

,

wherec_i(A)is the Euclidean norm of theith column ofA. Again,kBk₂ =√ n and ifα₁ = α₂ = · · · =α_n = 1then each column ofB is a unit vector in the Euclidean norm.

We now that

(2.14) kBk₂ ≤ kDk₂· kAk₂

forB matrix above (see O. Rojo [16]).

Theorem 2.2. Let the matrixH_n(n >2)given in(2.1)be partitioned as H_n= Hn⁽¹¹⁾ Hn⁽¹²⁾

Hn⁽²¹⁾ Hn⁽²²⁾

!

whereHn^(ij)is theijth submatrix of ordermi×nj withHn⁽¹¹⁾=Hn−1 andαi’s (i= 1, . . . , n)be as in(2.12). Then,

kH_n∗H_nk_s ≤π²+ 32 1

8π²− 259 225

2

+ 16 6561

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kH_n∗H_nk_s ≥

n−1

X

i=1

α²_i

−Ψ(1, n+ ¹₂ −i) + Ψ(1,³₂ +i)

!⁻²

+ 32 1

8π²−259 225

2

+ 16 6561

is valid where k·k_s is spectral norm and the operation “∗” is a Khatri-Rao product.

Proof. Let H_n be defind by (2.1) and partitioned as in (2.2). H_n ∗ H_n, the Khatri-Rao product of twoH_nmatrices, is obtained as

H_n∗H_n =





Hn⁽¹¹⁾⊗Hn⁽¹¹⁾ Hn⁽¹²⁾⊗Hn⁽¹²⁾

Hn⁽²¹⁾⊗Hn⁽²¹⁾ Hn⁽²²⁾⊗Hn⁽²²⁾



.

Using the`_pnorm and Khatri-Rao definitions one may easily computekH_n∗H_nk_p relative to the above

Hn^(ij⁾⊗Hn^(ij)

p

as shown in(2.3)

kH_n∗H_nk^p_p =

2

X

i,j=1

H_n^(ij)⊗H_n^(ij⁾

p p

First of all, we must establish a functionf(x)such that h_s = 1

2π Z π

−π

f(x)e^−isxdx= 1

1

2 +s, s= 2,3, . . . ,2n.

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whereh_sare the entries of the matrixH_n. Hence, we must find values ofcsuch

that 1

2π Z π

−π

ce((1/2)+s)ixe^−isxdx= 1

1 2 +s. Thus, we have

c 2π

Z π

−π

e^(1/2)+se^−isxdx= 2c π and

c= π 2 ¹₂ +s. Hence, we have

f(x) = π

2 ¹₂ +se((1/2)+s)ix

. The functionf(x)can be writtten as

f(x) =f₁(x)f₂(x),

wheref₁(x)is a real-valued function andf₂(x)is a function with period2πand

|f₂(x)|= 1.Thus, we have

f₁(x) = π 2 ¹₂ +s and

f₂(x) =e((1/2)+s)ix.

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SincekHn−1k_s≤supf₁(x),

n−1

X

k=1

1

(2k+ 5)² =−1 4Ψ

1, n+5 2

+ 1

8π²− 259 225

and from(2.3),we have kH_n∗H_nk_s≤π²+ 32

−1 4Ψ

1, n+5 2

+1

8π² −259 225

2

+ 16 6561. Thus, from (1.5) and (2.12) we obtain an upper bound for the spectral norm Khatri-Rao product of two H_n(n > 2)as in (2.1)partitioned as in(2.2) such that

kH_n∗H_nk_s≤π²+ 32 1

8π²− 259 225

2

+ 16 6561. Also, we have

kDk₂ =

n−1

X

i=1

α²_i

−Ψ(1, n+ ¹₂ −i) + Ψ(1,³₂ +i)

!¹₂

forDa matrix as defined by(2.13).SincekBk₂ =√

n−1forB matrix above and from(1.3), we have a lower bound for spectral norm Khatri-Rao product of twoH_n(n > 2)as in(2.1)and partitioned as in(2.2)such that

kH_n∗H_nk_s ≥

n−1

X

i=1

α²_i

−Ψ 1, n+¹₂ −i

+ Ψ 1,³₂ +i

!⁻²

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+ 32 1

8π²− 259 225

2

+ 16 6561. This completes the proof.

Example 2.2. Let

a=π²+ 32 1

8π²− 259 225

2

+ 16 6561, α₁ =α₂ =· · ·=αn−1 = 1, β =

n−1

X

i=1

1

−Ψ(1, n+¹₂ −i) + Ψ(1,³₂ +i)

!⁻² + 32

1

8π²− 259 225

2

+ 16 6561 and order of H_n∗H_n matrix isN. We have known that the bounds forα₁ = α₂ = · · · = αn−1 = 1are better than those for α_i’s (i = 1, . . . , n)such that α²₁+α²₂ +· · ·+α²_n = n. Thus, we have the following values for the spectral norm ofH_n∗H_n:

N β kHn∗Hnk_s a

5 0.2279281696 0.3909209269 10,09031555 10 0.2234942988 0.5703160868 10,09031555 17 0.2220047678 0.7282096597 10,09031555 26 0.2213922974 0.8664326411 10,09031555 37 0.2211033668 0.9883803285 10,09031555 50 0.2209527402 1.097039615 10,09031555

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References

[1] T. ANDO, Concavity of certain maps on positive definite matrices and applications to Hadamard products, Linear Algebra Appl., 26 (1979), 203–

241.

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