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. 2016 Oct 19;2016(1):254. doi: 10.1186/s13660-016-1200-3

A new S-type eigenvalue inclusion set for tensors and its applications

Zheng-Ge Huang 1,, Li-Gong Wang 1, Zhong Xu 1, Jing-Jing Cui 1
PMCID: PMC5181102  PMID: 28077920

Abstract

In this paper, a new S-type eigenvalue localization set for a tensor is derived by dividing N={1,2,,n} into disjoint subsets S and its complement. It is proved that this new set is sharper than those presented by Qi (J. Symb. Comput. 40:1302-1324, 2005), Li et al. (Numer. Linear Algebra Appl. 21:39-50, 2014) and Li et al. (Linear Algebra Appl. 481:36-53, 2015). As applications of the results, new bounds for the spectral radius of nonnegative tensors and the minimum H-eigenvalue of strong M-tensors are established, and we prove that these bounds are tighter than those obtained by Li et al. (Numer. Linear Algebra Appl. 21:39-50, 2014) and He and Huang (J. Inequal. Appl. 2014:114, 2014).

Keywords: tensor eigenvalue, nonsingular M-tensor, minimum H-eigenvalue, nonnegative tensor, spectral radius, positive definite

Introduction

Eigenvalue problems of higher order tensors have become an important topic in the applied mathematics branch of numerical multilinear algebra, and they have a wide range of practical applications, such as best-rank one approximation in data analysis [5], higher order Markov chains [6], molecular conformation [7], and so forth. In recent years, tensor eigenvalues have caused concern of lots of researchers [1, 3, 4, 820].

One of many practical applications of eigenvalues of tensors is that one can identify the positive (semi-)definiteness for an even-order real symmetric tensor by using the smallest H-eigenvalue of a tensor, consequently, one can identify the positive (semi-)definiteness of the multivariate homogeneous polynomial determined by this tensor; for details, see [1, 21, 22].

However, as mentioned in [21, 23, 24], it is not easy to compute the smallest H-eigenvalue of tensors when the order and dimension are very large, we always try to give a set including all eigenvalues in the complex. Some sets including all eigenvalues of tensors have been presented by some researchers [13, 2124]. In particular, if one of these sets for an even-order real symmetric tensor is in the right-half complex plane, then we can conclude that the smallest H-eigenvalue is positive, consequently, the corresponding tensor is positive definite. Therefore, the main aim of this paper is to study the new eigenvalue inclusion set for tensors called the new S-type eigenvalue inclusion set, which is sharper than some existing ones.

For a positive integer n, N denotes the set N={1,2,,n}. The set of all real numbers is denoted by R, and C denotes the set of all complex numbers. Here, we call A=(ai1im) a complex (real) tensor of order m dimension n, denoted by C[m,n](R[m,n]), if ai1imC(R), where ijN for j=1,2,,m [23].

Let AR[m,n], and xCn. Then

Axm1:=(i2,,im=1naii2imxi2xim)1in,

a pair (λ,x)C×(Cn/{0}) is called an eigenpair of A [18] if

Axm1=λx[m1],

where x[m1]=(x1m1,x2m1,,xnm1)T [25]. Furthermore, we call (λ,x) an H-eigenpair, if both λ and x are real [1].

A real tensor of order m dimension n is called the unit tensor [21], denoted by I, if its entries are δi1im for i1,,imN, where

δi1im={1,if i1==im,0,otherwise.

An m-order n-dimensional tensor A is called nonnegative [9, 10, 13, 14, 26], if each entry is nonnegative. We call a tensor A a Z-tensor, if all of its off-diagonal entries are non-positive, which is equivalent to writing A=sIB, where s>0 and B is a nonnegative tensor (B0), denoted by Z the set of m-order and n-dimensional Z-tensors. A Z-tensor A=sIB is an M-tensor if sρ(B), and it is a nonsingular (strong) M-tensor if s>ρ(B) [20, 27].

The tensor A is called reducible if there exists a nonempty proper index subset JN such that ai1i2im=0, i1J, i2,,imJ. If A is not reducible, then we call A is irreducible [19]. The spectral radius ρ(A) [14] of the tensor A is defined as

ρ(A)=max{|λ|:λ is an eigenvalue of A}.

Denote by τ(A) the minimum value of the real part of all eigenvalues of the nonsingular M-tensor A [4]. A real tensor A=(ai1im) is called symmetric [13, 13, 22, 23] if

ai1im=aπ(i1im),πΠm,

where Πm is the permutation group of m indices.

Let A=(ai1im)R[m,n]. For i,jN, ji, denote

Ri(A)=i2,,im=1naii2im,Rmax(A)=maxiNRi(A),Rmin(A)=miniNRi(A),ri(A)=δii2im=0|aii2im|,rij(A)=δii2im=0,δji2im=0|aii2im|=ri(A)|aijj|.

Recently, much literature has focused on the bounds of the spectral radius of nonnegative tensor in [2, 3, 14, 15, 1719, 24, 28]. In addition, in [4], He and Huang obtained the upper and lower bounds for the minimum H-eigenvalue of nonsingular M-tensors. Wang and Wei [16] presented some new bounds for the minimum H-eigenvalue of nonsingular M-tensors, and they showed those are better than the ones in [4] in some cases. As applications of the new S-type eigenvalue inclusion set, the other main results of this paper is to provide sharper bounds for the spectral radius of nonnegative tensors and the minimum H-eigenvalue of nonsingular M-tensors, which improve some existing ones.

Before presenting our results, we review the existing results that relate to the eigenvalue inclusion sets for tensors. In 2005, Qi [1] generalized the Geršgorin eigenvalue inclusion theorem from matrices to real supersymmetric tensors, which can be easily extended to general tensors [2, 13].

Lemma 1.1

[1]

Let A=(ai1im)C[m,n], n2. Then

σ(A)Γ(A)=iNΓi(A),

where σ(A) is the set of all the eigenvalues of A and

Γi(A)={zC:|zaii|ri(A)}.

To get sharper eigenvalue inclusion sets than Γ(A), Li et al. [2] extended the Brauer eigenvalue localization set of matrices [29, 30] and proposed the following Brauer-type eigenvalue localization sets for tensors.

Lemma 1.2

[2]

Let A=(ai1im)C[m,n], n2. Then

σ(A)K(A)=i,jN,jiKi,j(A),

where

Ki,j(A)={zC:(|zaii|rij(A))|zajj||aijj|rj(A)}.

In addition, in order to reduce computations of determining the sets σ(A), Li et al. [2] also presented the following S-type eigenvalue localization set by breaking N into disjoint subsets S and , where is the complement of S in N.

Lemma 1.3

[2]

Let A=(ai1im)C[m,n], n2, and S be a nonempty proper subset of N. Then

σ(A)KS(A)=(iS,jS¯Ki,j(A))(iS¯,jSKi,j(A)),

where Ki,j(A) (iS, jS¯ or iS¯, jS) is defined as in Lemma  1.2.

Based on the results of [2], in the sequel, Li et al. [3] exhibited a new tensor eigenvalue inclusion set, which is proved to be tighter than the sets in Lemma 1.2.

Lemma 1.4

[3]

Let A=(ai1im)C[m,n], n2, and S be a nonempty proper subset of N. Then

σ(A)Δ(A)=i,jN,jiΔij(A),

where

Δij(A)={zC:|(zaii)(zajj)aijjajii||zajj|rij(A)+|aijj|rji(A)}.

In this paper, we continue this research on the eigenvalue inclusion sets for tensors; inspired by the ideas of [2, 3], we obtain a new S-type eigenvalue inclusion set for tensors. It is proved to be tighter than the tensor Geršgorin eigenvalue inclusion set Γ(A) in Lemma 1.1, the Brauer eigenvalue localization set K(A) in Lemma 1.2, the S-type eigenvalue localization set KS(A) in Lemma 1.3, and the set Δ(A) in Lemma 1.4. As applications, we establish some new bounds for spectral radius of nonnegative tensors and the minimum H-eigenvalue of strong M-tensors. Numerical examples are implemented to illustrate this fact.

The remainder of this paper is organized as follows. In Section 2, we recollect some useful lemmas on tensors which are utilized in the next sections. In Section 3.1, a new S-type eigenvalue inclusion set for tensors is given, and proved to be tighter than the existing ones derived in Lemmas 1.1-1.4. Based on the results of Section 3.1, we propose a new upper bound for the spectral radius of nonnegative tensors in Section 3.2; comparison results for this new bound and that derived in [2] are also investigated in this section. Section 3.3 is devoted to the exhibition of new upper and lower bounds for the minimum H-eigenvalue of strong M-tensors, which are proved to be sharper than the ones obtained by He and Huang [4]. Finally, some concluding remarks are given to end this paper in Section 4.

Preliminaries

In this section, we start with some lemmas on tensors. They will be useful in the following proofs.

Lemma 2.1

[16]

If AR[m,n] is irreducible nonnegative, then ρ(A) is a positive eigenvalue with an entrywise positive eigenvector x, i.e., x>0, corresponding to it.

Lemma 2.2

[2]

Let AR[m,n] be a nonnegative tensor. Then ρ(A)maxiN{aii}.

Lemma 2.3

[13]

Suppose that 0A<C. Then ρ(A)ρ(C).

Lemma 2.4

[4]

Let A be a strong M-tensor and denoted by τ(A) the minimum value of the real part of all eigenvalues of A. Then τ(A) is an eigenvalue of A with a nonnegative eigenvector. Moreover, if A is irreducible, then τ(A) is a unique eigenvalue with a positive eigenvector.

Lemma 2.5

[4]

Let A be an irreducible strong M-tensor. Then τ(A)miniN{aii}.

Lemma 2.6

[20]

A tensor A is semi-positive if and only if there exists x0 such that Axm1>0.

Lemma 2.7

[20]

A Z-tensor is a nonsingular M-tensor if and only if it is semi-positive.

Lemma 2.8

[4]

Let A,BZ, assume that A is an M-tensor and BA. Then B is an M-tensor, and τ(A)τ(B).

Main results

A new S-type eigenvalue inclusion set for tensors

In this section, we propose a new S-type eigenvalue set for tensors and establish the comparisons between this new set with those in Lemmas 1.1-1.4.

Theorem 3.1

Let A=(ai1im)C[m,n] with n2. And let S be a nonempty proper subset of N. Then

σ(A)ϒS(A):=(iS,jS¯ϒij(A))(iS¯,jSϒij(A)), 1

where

ϒij(A)={zC:|(zaii)(zajj)aijjajii||zajj|rij(A)+|aijj|rji(A)}.

Proof

For any λσ(A), let x=(x1,,xn)TCn/{0} be an eigenvector corresponding to λ, i.e.,

Axm1=λx[m1]. 2

Let |xp|=maxiS{|xi|} and |xq|=maxiS¯{|xi|}. Then, xp0 or xq0. Now, let us distinguish two cases to prove.

(i) |xp||xq|, so |xp|=maxiN{|xi|} and |xp|>0. For any jS¯, it follows from (2) that

{i2,,im=1napi2imxi2xim=λxpm1,i2,,im=1naji2imxi2xim=λxjm1.

Hence, we have

{δpi2im=0,δji2im=0api2imxi2xim+appxpm1+apjjxjm1=λxpm1,δji2im=0,δpi2im=0aji2imxi2xim+ajjxjm1+ajppxpm1=λxjm1,

i.e.,

{δpi2im=0,δji2im=0api2imxi2xim=(λapp)xpm1apjjxjm1,δji2im=0,δpi2im=0aji2imxi2xim=(λajj)xjm1ajppxpm1. 3

Premultiplying by (λajj) in the first equation of (3) results in

(λajj)δpi2im=0,δji2im=0api2imxi2xim=(λajj)(λapp)xpm1apjj(λajj)xjm1. 4

Combining (4) and the second equation of (3) one derives

(λajj)δpi2im=0,δji2im=0api2imxi2xim+apjjδji2im=0,δpi2im=0aji2imxi2xim=(λajj)(λapp)xpm1apjjajppxpm1=[(λajj)(λapp)apjjajpp]xpm1.

Taking absolute values and using the triangle inequality yield

|(λajj)(λapp)apjjajpp||xp|m1|λajj|rpj(A)|xp|m1+|apjj|rjp(A)|xp|m1.

Note that |xp|>0, thus

|(λajj)(λapp)apjjajpp||λajj|rpj(A)+|apjj|rjp(A), 5

which implies that λϒpj(A)iS,jS¯ϒij(A)ϒS(A).

(ii) |xp||xq|, so |xq|=maxiN{|xi|} and |xq|>0. For any iS, it follows from (2) that

{i2,,im=1naii2imxi2xim=λxim1,i2,,im=1naqi2imxi2xim=λxqm1.

Using the same method as the proof in (i), we deduce that

(λaii)δqi2im=0,δii2im=0aqi2imxi2xim+aqiiδii2im=0,δqi2im=0aii2imxi2xim=(λaqq)(λaii)xqm1aiqqaqiixqm1=[(λaqq)(λaii)aiqqaqii]xqm1.

Taking the modulus in the above equation and using the triangle inequality we obtain

|(λaqq)(λaii)aiqqaqii||xq|m1|λaii|rqi(A)|xq|m1+|aqii|riq(A)|xq|m1.

Note that |xq|>0, thus

|(λaqq)(λaii)aiqqaqii||λaii|rqi(A)+|aqii|riq(A). 6

This means that λϒqi(A)iS¯,jSϒij(A)ϒS(A). This completes our proof of Theorem 3.1. □

Remark 3.1

Note that |S|<n, where |S| is the cardinality of S. If n=2, then |S|=1 and n(n1)=2|S|(n|S|)=2, which implies that

ϒS(A)=(ϒ12(A)ϒ21(A))=Δ(A).

Besides, if n3, 2|S|(n|S|)<n(n1), then ϒS(A)Δ(A) if Δi1j1(A)Δi2j2(A)= for any i1,i2,j1,j2N, i1i2 or j1j2. Furthermore, how to choose S to make ϒS(A) as sharp as possible is very interesting and important. However, this work is difficult especially the dimension of the tensor A is large. At present, it is very difficult for us to research this problem, we will continue to study this problem in the future.

Next, we establish a comparison theorem for the new S-type eigenvalue inclusion set derived in this paper and those in Lemmas 1.1-1.4.

Theorem 3.2

Let A=(ai1im)C[m,n] with n2. Then

ϒS(A)KS(A)K(A)Γ(A),ϒS(A)Δ(A). 7

Proof

According to Remark 3.1, it is obvious that ϒS(A)Δ(A). By Theorem 2.3 in [2], we know that KS(A)K(A)Γ(A). Hence, we only prove ϒS(A)KS(A). Let zϒS(A), then

ziS,jS¯ϒij(A)orziS¯,jSϒij(A).

Without loss of generality, we assume that ziS,jS¯ϒij(A) (we can prove it similarly if ziS¯,jSϒij(A)). Then there exist pS and qS¯ such that zϒpq(A), that is,

|(zapp)(zaqq)apqqaqpp||zaqq|rpq(A)+|apqq|rqp(A).

Inasmuch as

|(zapp)(zaqq)||apqqaqpp||(zapp)(zaqq)apqqaqpp|,

z satisfies

|(zapp)(zaqq)||apqqaqpp||zaqq|rpq(A)+|apqq|rqp(A),

which yields

|zaqq|(|zapp|rpq(A))|apqq|(rqp(A)+|aqpp|)=|apqq|rq(A).

This means that

zKp,q(A)iS,jS¯Ki,j(A)KS(A),

which implies that

ϒS(A)KS(A).

This proof is completed. □

A new upper bound for the spectral radius of nonnegative tensors

Based on the results of Section 3.1, we discuss the spectral radius of nonnegative tensors, and we give their upper bounds, which are better than those of Theorem 3.4 in [2].

Theorem 3.3

Let AR[m,n] be an irreducible nonnegative tensor with n2. And let S be a nonempty proper subset of N. Then

ρ(A)ηs(A)=max{ηS(A),ηS¯(A)},

where

ηS(A)=12maxiSminjS¯{aii+ajj+rij(A)+Φi,j12(A)}, 8

with

Φi,j(A)=(aiiajj+rij(A))2+4aijjrj(A).

Proof

Since A is an irreducible nonnegative tensor, by Lemma 2.1, there exists x=(x1,,xn)T>0 such that

Axm1=ρ(A)x[m1]. 9

Let xp=maxiS{xi} and xq=maxiS¯{xi}. Below we distinguish two cases to prove.

(i) xpxq>0, so xp=maxiN{xi}. For any jS¯, it follows from (9) that

{i2,,im=1napi2imxi2xim=ρ(A)xpm1,i2,,im=1naji2imxi2xim=ρ(A)xjm1.

Hence, we have

{δpi2im=0,δji2im=0api2imxi2xim=(ρ(A)app)xpm1apjjxjm1,δji2im=0,δpi2im=0aji2imxi2xim=(ρ(A)ajj)xjm1ajppxpm1. 10

Premultiplying by (ρ(A)ajj) in the first equation of (10) results in

(ρ(A)ajj)δpi2im=0,δji2im=0api2imxi2xim=(ρ(A)ajj)(ρ(A)app)xpm1apjj(ρ(A)ajj)xjm1. 11

It follows from (11) and the second equation of (10) that

(ρ(A)ajj)δpi2im=0,δji2im=0api2imxi2xim+apjjδji2im=0,δpi2im=0aji2imxi2xim=(ρ(A)ajj)(ρ(A)app)xpm1apjjajppxpm1=[(ρ(A)ajj)(ρ(A)app)apjjajpp]xpm1.

Note that xpxj for any jS¯ and by Lemma 2.2, we deduce that

[(ρ(A)ajj)(ρ(A)app)apjjajpp](ρ(A)ajj)rpj(A)+apjjrjp(A),

i.e.,

ρ(A)2(app+ajj+rpj(A))ρ(A)+ajj(app+rpj(A))apjjrj(A)0. 12

Solving the quadratic inequality (12) yields

ρ(A)12{app+ajj+rpj(A)+Φp,j12(A)}. 13

It is not difficult to verify that (13) can be true for any jS¯. Thus

ρ(A)12minjS¯{app+ajj+rpj(A)+Φp,j12(A)},

which implies that

ρ(A)12maxiSminjS¯{aii+ajj+rij(A)+Φi,j12(A)}. 14

(ii) xqxp>0, so xq=maxiN{xi}. For any iS, it follows from (9) that

{i2,,im=1naii2imxi2xim=ρ(A)xim1,i2,,im=1naqi2imxi2xim=ρ(A)xqm1.

So we obtain

{δii2im=0,δqi2im=0aii2imxi2xim=(ρ(A)aii)xim1aiqqxqm1,δqi2im=0,δii2im=0aqi2imxi2xim=(ρ(A)aqq)xqm1aqiixim1. 15

In a similar manner to the proof of (i)

[(ρ(A)aqq)(ρ(A)aii)aiqqaqii](ρ(A)aii)rqi(A)+aqiiriq(A),

i.e.,

ρ(A)2(aii+aqq+rqi(A))ρ(A)+aii(aqq+rqi(A))aqiiri(A)0, 16

which yields

ρ(A)12{aqq+aii+rqi(A)+Φq,i12(A)}. 17

It is easy to see that (17) can be true for any jS. Thus

ρ(A)12minjS{aqq+ajj+rqj(A)+Φq,j12(A)},

which implies that

ρ(A)12maxiS¯minjS{aii+ajj+rij(A)+Φi,j12(A)}. 18

This completes our proof in this theorem. □

Next, we extend the results of Theorem 3.3 to general nonnegative tensors; without the condition of irreducibility, compare with Theorem 3.3.

Theorem 3.4

Let AR[m,n] be a nonnegative tensor with n2. And let S be a nonempty proper subset of N. Then

ρ(A)ηs=max{ηS(A),ηS¯(A)}, 19

where

ηS(A)=12maxiSminjS¯{aii+ajj+rij(A)+Φi,j12(A)},

with

Φi,j(A)=(aiiajj+rij(A))2+4aijjrj(A).

Proof

Let Ak=A+1kε, where k=1,2, , and ε denotes the tensor with every entry being 1. Then Ak is a sequence of positive tensors satisfying

0A<<Ak+1<Ak<<A1.

By Lemma 2.3, {ρ(Ak)} is a monotone decreasing sequence with lower bound ρ(A). So ρ(Ak) has a limit. Let

limk+ρ(Ak)=λρ(A). 20

By Lemma 2.1, we see that ρ(Ak) is the eigenvalue of Ak with a positive eigenvector yk, i.e., Akykm1=ρ(Ak)yk[m1]. In a manner similar to Theorem 2.3 in [13], we have

limk+ρ(Ak)=ρ(A).

And we denote Ψi,j(A)=12{aii+ajj+rij(A)+Φi,j12(A)} (iS, jS¯ or iS¯, jS). Then

Ψi,j(Ak)=12{aii+ajj+2k+rij(A)+nm12k+Φi,j12(Ak)},

where

Φi,j(Ak)=(aiiajj+rij(A)+nm12k)2+4(aijj+1k)(rj(A)+nm11k).

As m and n are finite numbers, then by the properties of the sequence, it is easy to see that

limk+Ψi,j(Ak)=Ψi,j(A).

Furthermore, since Ak is an irreducible nonnegative tensor, it follows from Theorem 3.3 that

ρ(Ak)max{ηS(Ak),ηS¯(Ak)}.

Letting k+ results in

ρ(A)max{ηS(A),ηS¯(A)},

from which one may get the desired bound (19). □

Remark 3.2

Now, we compare the upper bound in Theorem 3.4 with that in Theorem 3.4 in [2]. It is not difficult to see that

ηS(A)=12maxiSminjS¯{aii+ajj+rij(A)+Φi,j12(A)}12maxiS,jS¯{aii+ajj+rij(A)+Φi,j12(A)}

and

ηS¯(A)=12maxiS¯minjS{aii+ajj+rij(A)+Φi,j12(A)}12maxiS¯,jS{aii+ajj+rij(A)+Φi,j12(A)}.

This shows that the upper bound in Theorem 3.4 improves the corresponding one in Theorem 3.4 of [2].

We have showed that our bound is sharper than the existing one in [2]. Now we take an example to show the efficiency of the new upper bound established in this paper.

Example 3.1

Let A=(aijk)R[3,3] be nonnegative with entries defined as follows: a111=a122=a222=a233=a312=a322=a333=1, a123=a133=a211=2, a213=3, a311=20, and the other aijk=0. It is easy to compute

r1(A)=5,r12(A)=4,r13(A)=3;r2(A)=6,r21(A)=4,r23(A)=5;r3(A)=22,r31(A)=2,r32(A)=21.

We choose S={1,2}. Evidently, S¯={3}. By Theorem 3.4 of [2], we have

ρ(A)22.2819.

By Theorem 3.4, we obtain

ρ(A)12.0499,

which means that the upper bound in Theorem 3.4 is much better than that in Theorem 3.4 of [2].

New upper and lower bounds for the minimum H-eigenvalue of nonsingular M-tensors

In this section, by making use of the results in Section 3.1, we investigate the bounds for the minimum H-eigenvalue of strong M-tensors and derive sharper bounds for that. This bounds are proved to be tighter than those in Theorem 2.2 of [4].

Theorem 3.5

Let AR[m,n] be an irreducible nonsingular M-tensor with n2. And let S be a nonempty proper subset of N. Then

min{ϕS(A),ϕS¯(A)}τ(A)max{χS(A),χS¯(A)},

where

χS(A)=12maxiSminjS¯{aii+ajjrij(A)Θi,j12(A)} 21

and

ϕS(A)=12miniSmaxjS¯{aii+ajjrij(A)Θi,j12(A)}, 22

with

Θi,j(A)=(aiiajjrij(A))24aijjrj(A).

Proof

Since A is an irreducible nonsingular M-tensor, by Lemma 2.4, there exists x=(x1,,xn)T>0 such that

Axm1=τ(A)x[m1]. 23

Let xp=maxiS{xi} and xq=maxiS¯{xi}. We distinguish two cases to prove.

(i) xpxq>0, so xp=maxiN{xi}. For any jS¯, it follows from (23) that

{i2,,im=1napi2imxi2xim=τ(A)xpm1,i2,,im=1naji2imxi2xim=τ(A)xjm1.

Hence, we have

{δpi2im=0,δji2im=0api2imxi2xim=(appτ(A))xpm1+apjjxjm1,δji2im=0,δpi2im=0aji2imxi2xim=(ajjτ(A))xjm1+ajppxpm1. 24

Premultiplying by (ajjτ(A)) in the first equation of (24) results in

(ajjτ(A))δpi2im=0,δji2im=0api2imxi2xim=(ajjτ(A))(appτ(A))xpm1+apjj(ajjτ(A))xjm1. 25

It follows from (25) and the second equation of (24) that

(ajjτ(A))δpi2im=0,δji2im=0api2imxi2xim+apjjδji2im=0,δpi2im=0aji2imxi2xim=(ajjτ(A))(appτ(A))xpm1apjjajppxpm1=[(ajjτ(A))(appτ(A))apjjajpp]xpm1.

Combining xpxj for any jS¯ with Lemma 2.5 results in

[(ajjτ(A))(appτ(A))apjjajpp](ajjτ(A))rpj(A)apjjrjp(A),

i.e.,

τ(A)2(app+ajjrpj(A))τ(A)+ajj(apprpj(A))+apjjrj(A)0. 26

Solving the quadratic inequality (26) yields

τ(A)12{app+ajjrpj(A)Θp,j12(A)}. 27

It is not difficult to verify that (27) can be true for any jS¯. Thus

τ(A)12maxjS¯{app+ajjrpj(A)Θp,j12(A)},

and therefore

τ(A)12miniSmaxjS¯{aii+ajjrij(A)Θi,j12(A)}. 28

(ii) xqxp>0, so xq=maxiN{xi}. For any iS, it follows from (23) that

{i2,,im=1naii2imxi2xim=τ(A)xim1,i2,,im=1naqi2imxi2xim=τ(A)xqm1.

So we obtain

{δii2im=0,δqi2im=0aii2imxi2xim=(aiiτ(A))xim1+aiqqxqm1,δqi2im=0,δii2im=0aqi2imxi2xim=(aqqτ(A))xqm1+aqiixim1. 29

Using the same technique as the proof of (i), we have

[(aqqτ(A))(aiiτ(A))aiqqaqii](aiiτ(A))rqi(A)aqiiriq(A),

which is equivalent to

τ(A)2(aqq+aiirqi(A))τ(A)+aii(aqqrqi(A))+aqiiri(A)0, 30

which results in

τ(A)12{aqq+aiirqi(A)Θq,i12(A)}. 31

It is not difficult to verify that (31) can be true for any jS. Thus

τ(A)12maxjS{aqq+ajjrqj(A)Θq,j12(A)},

which implies that

τ(A)12miniS¯maxjS{aii+ajjrij(A)Θi,j12(A)}.

Let xk=miniS{xi} and xl=miniS¯{xi}. With a strategy quite similar to the one utilized in the above proof, we can prove that

τ(A)max{χS(A),χS¯(A)},

which implies this theorem. □

Remark 3.3

We next prove the bounds in Theorem 3.5 are sharper than those of Theorem 2.2 in [4]; it is easy to see that

ϕS(A)=12miniSmaxjS¯{aii+ajjrij(A)Θi,j12(A)}12miniS,jS¯{aii+ajjrij(A)Θi,j12(A)}=ψS(A)

and

ϕS¯(A)=12miniS¯maxjS{aii+ajjrij(A)Θi,j12(A)}12miniS¯,jS{aii+ajjrij(A)Θi,j12(A)}=ψS¯(A),

which implies that

min{ϕS(A),ϕS¯(A)}min{ψS(A),ψS¯(A)}12mini,jN,ij{aii+ajjrij(A)Θi,j12(A)}.

In the same manner as applied in the above proof, we can deduce the following results:

max{χS(A),χS¯(A)}max{θS(A),θS¯(A)}12maxi,jN,ij{aii+ajjrij(A)Θi,j12(A)},

where θS(A)=12maxiS,jS¯{aii+ajjrij(A)Θi,j12(A)}. Therefore, the conclusions follow from the above discussions.

Example 3.2

Consider the following irreducible nonsingular M-tensor:

A=[A(1,:,:),A(2,:,:),A(3,:,:)]R[3,3],

where

A(1,:,:)=(70000.52012),A(2,:,:)=(15.820120000.5),A(3,:,:)=(1200130350).

We compare the results derived in Theorem 3.5 with those in Theorem 2.1 of [4] and Theorem 4.5 of [16] in the correct forms. Let S={1,2}, then S¯={3}. By Theorem 2.1 of [4], we have

1.5548τ(A)11.6828.

By Theorem 4.5 of [16], we get

1.7350τ(A)11.3923.

By Theorem 3.5, we obtain

3.0738τ(A)6.8390.

This shows that the upper and lower bounds in Theorem 3.5 are sharper than those in Theorem 2.1 of [4] and Theorem 4.5 of [16].

In the sequel, we extend the results of Theorem 3.5 to a more general case, which needs a weaker condition compared with Theorem 3.5.

Theorem 3.6

Let AR[m,n] be a nonsingular M-tensor with n2. And let S be a nonempty proper subset of N. Then

min{ϕS(A),ϕS¯(A)}τ(A)max{χS(A),χS¯(A)},

where

χS(A)=12maxiSminjS¯{aii+ajjrij(A)Θi,j12(A)}, 32

and

ϕS(A)=12miniSmaxjS¯{aii+ajjrij(A)Θi,j12(A)}, 33

with

Θi,j(A)=(aiiajjrij(A))24aijjrj(A).

Proof

Since A is a nonsingular M-tensor, AZ, by Lemma 2.7 and Lemma 2.6, there exists x=(x1,,xn)T0 such that Axm1>0, that is, for any i1N,

i2,,im=1nai1imxi2xim>0.

Let

g=mini1Ni2,,im=1nai1imxi2xim,xmax=maxiNxi.

So xmax>0 by x0. By replacing the zero entries of A with 1k, where k is a positive integer, we see that the Z-tensor Ak is irreducible. Here, we use ai1im(1k) to denote the entries of Ak. We choose k>[(nm11)xmaxm1g]+1, then, for any i1N, we have

i2,,im=1nai1im(1k)xi2ximmini1Ni2,,im=1nai1imxi2xim(nm11)xmaxm1k=g(nm11)xmaxm1k>0,

which implies that Akxm1>0 and, by Lemma 2.6 and Lemma 2.7, we infer that Ak is an irreducible nonsingular M-tensor if k>[(nm11)xmaxm1g]+1. It follows from the above discussions that Ak (k>[(nm11)xmaxm1g]+1) is a sequence of irreducible nonsingular M-tensors satisfying

A>>Ak+1>Ak.

By Lemma 2.8, {τ(Ak)} is a monotone increasing sequence with upper bound τ(A) so that τ(Ak) has a limit. Let

limk+τ(Ak)=λτ(A). 34

By Lemma 2.4, we see that τ(Ak) is the eigenvalue of Ak with a positive eigenvector yk, i.e., Akykm1=τ(Ak)yk[m1]. As homogeneous multivariable polynomials, we can restrict yk to a ball; that is, yk=1. Then {yk} is a bounded sequence, so it has a convergent subsequence. Without loss of generality, we can suppose it is the sequence itself. Let yky as k+, we get y0 and y=1. By Akykm1=τ(Ak)yk[m1] and letting k+, we have Ay=λy[m1]. Thus λ is an eigenvalue of A, thus λτ(A). Together with (34) this results in λ=τ(A), which means that

limk+τ(Ak)=τ(A).

Besides, for iS, jS¯ (for iS¯, jS, we can define Mij and Mj similarly), we define the following sets:

Mij={aii2im|aii2im=0,δii2im=0 and δji2im=0,i2,,imN},Mj={aji2im|aji2im=0 and δji2im=0,i2,,imN}.

Let the numbers of entries in Mij and Mj be nij and nj, respectively, and we denote Λi,j(A)=12{aii+ajjrij(A)Θi,j12(A)}. Then

Λi,j(Ak)=12{aii+ajjrij(A)nijkΘi,j12(Ak)},

where

Θi,j(Ak)=(aiiajjrij(A)nijk)24(aijjεi,jk)(rj(A)+njk),

with

εi,j={1,if aijj=0,0,if aijj0.

By the properties of the sequence, it is not difficult to verify that

limk+χS(Ak)=χS(A),limk+ϕS(Ak)=ϕS(A).

Furthermore, since Ak is an irreducible nonsingular M-tensor for k>[(nm11)xmaxm1g]+1, by Theorem 3.5, we have

min{ϕS(Ak),ϕS¯(Ak)}τ(Ak)max{χS(Ak),χS¯(Ak)}.

Letting k+ results in

min{ϕS(A),ϕS¯(A)}τ(A)max{χS(A),χS¯(A)}.

This completes our proof of Theorem 3.6. □

Concluding remarks

In this paper, a new S-type eigenvalue inclusion set for tensors is presented, which is proved to be sharper than the ones in [2, 3]. As applications, we give new bounds for the spectral radius of nonnegative tensors and the minimum H-eigenvalue of strong M-tensors, these bounds improve some existing ones obtained by Li et al. [2] and He and Huang [4]. In addition, we extend these new bounds to more general cases.

However, the new S-type eigenvalue inclusion set and the derived bounds depend on the set S. How to choose S to make ϒS(A) and the bounds exhibited in this paper as tight as possible is very important and interesting, while if the dimension of the tensor A is large, this work is very difficult. Therefore, future work will include numerical or theoretical studies for finding the best choice for S.

Acknowledgements

This work is supported by the National Natural Science Foundations of China (No. 11171273) and sponsored by Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University (No. CX201628).

Footnotes

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

All authors contributed equally to this work. All authors read and approved the final manuscript.

Contributor Information

Zheng-Ge Huang, Email: ZhenggeHuang@mail.nwpu.edu.cn.

Li-Gong Wang, Email: ZhenggeHuang@163.com.

Zhong Xu, Email: zhongxu@nwpu.edu.cn.

Jing-Jing Cui, Email: 1097003024@qq.com.

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