• No results found

A new S type upper bound for the largest singular value of nonnegative rectangular tensors

N/A
N/A
Protected

Academic year: 2020

Share "A new S type upper bound for the largest singular value of nonnegative rectangular tensors"

Copied!
12
0
0

Loading.... (view fulltext now)

Full text

(1)

R E S E A R C H

Open Access

A new

S

-type upper bound for the largest

singular value of nonnegative rectangular

tensors

Jianxing Zhao

*

and Caili Sang

*Correspondence:

[email protected] College of Data Science and Information Engineering, Guizhou Minzu University, Guiyang, Guizhou 550025, P.R. China

Abstract

By breakingN={1, 2,. . .,n}into disjoint subsetsSand its complement, a newS-type upper bound for the largest singular value of nonnegative rectangular tensors is given and proved to be better than some existing ones. Numerical examples are given to verify the theoretical results.

MSC: 15A18; 15A42; 15A69

Keywords: nonnegative tensor; rectangular tensor; singular value

1 Introduction

Singular value problems of rectangular tensors have become an important topic in applied mathematics and numerical multilinear algebra, and it has a wide range of practical appli-cations, such as the strong ellipticity condition problem in solid mechanics [, ] and the entanglement problem in quantum physics [, ].

LetR(respectively,C) be the real (respectively, complex) field. Assume thatp,q,m,n are positive integers,m,n≥,l=p+q, andN={, , . . . ,n}. A real (p,q)th orderm× ndimensional rectangular tensor (or simply a real rectangular tensor)Ais defined as follows:

A= (ai···ipj···jq), ai···ipj···jq∈R, ≤i, . . . ,ipm, j, . . . ,jqn.

A real rectangular tensorAis called nonnegative if ai···ipj···jq ≥ forik= , . . . ,m,k=

, . . . ,p, andjv= , . . . ,n,v= , . . . ,q.

For vectorsx= (x, . . . ,xm)T,y= (y, . . . ,yn)Tand a real numberα, letx[α]= (xα,, . . . ,

m)T,y[α]= (yα,, . . . ,yαn)T,Axp–yqbe anmdimension real vector whoseith component

is

Axp–yq i=

m

i,...,ip=

n

j,...,jq=

aii···ipj···jqxi· · ·xipyj· · ·yjq,

(2)

andAxpyq–be anndimension real vector whosejth component is

Axpyq–

j= m

i,...,ip=

n

j,...,jq=

ai···ipjj···jqxi· · ·xipyj· · ·yjq.

Ifλ∈C,x∈Cm\{}, andyCn\{}are solutions of

⎧ ⎨ ⎩

Axp–yq=λx[l–], Axpyq–=λy[l–],

then we say thatλis a singular value ofA,xandyare a left and a right eigenvectors ofA, associated withλ. Ifλ∈R,x∈Rm, andyRn, then we say thatλis an H-singular value

ofA,xandyare a left and a right H-eigenvectors ofA, associated with H-singular value

λ[]. Here,

λ=max

|λ|:λis a singular value ofA

is called the largest singular value [].

The definition of singular values for tensors was first introduced in []. Note here that whenlis even, the definitions in [] is the same as in [], and whenlis odd, the definition in [] is slightly different from that in [], but parallel to the definition of eigenvalues of square matrices []; see [] for details.

Recently, many people focus on bounding the largest singular value for nonnegative rect-angular tensors [, , ]. For convenience, we first give some notation. Given a nonempty proper subsetSofN, we denote

N:=(i, . . . ,ip,j, . . . ,jq) :i, . . . ,ip,j, . . . ,jqN ,

S:=(i, . . . ,ip,j, . . . ,jq) :i, . . . ,ip,j, . . . ,jqS ,

N:=(i, . . . ,ip,j, . . . ,jq) :i, . . . ,ip,j, . . . ,jqN ,

S:=(i, . . . ,ip,j, . . . ,jq) :i, . . . ,ip,j, . . . ,jqS ,

and then

S=N\S, S=N\S.

This implies that, for a nonnegative rectangular tensorA= (ai···ipj···jq), we have, fori,jS,

ri(A) =

i,...,ip,j,...,jqN δii···ipj···jq=

aii···ipj···jq=r S

i (A) +r

S

i (A), r j

i(A) =ri(A) –aij···jj···j,

cj(A) =

i,...,ip,j,...,jqN δi···ipjj···jq=

ai···ipjj···jq=c S

j (A) +c

S

(3)

where

δi···ipj···jq=

⎧ ⎨ ⎩

, ifi=· · ·=ip=j=· · ·=jq,

, otherwise,

and

rS

i (A) =

(i,...,ip,j,...,jq)∈S δii

···ipj···jq=

aii···ipj···jq, r S

i (A) =

(i,...,ip,j,...,jq)∈S

aii···ipj···jq,

cjS(A) = (i,...,ip,j,...,jq)∈S

δi···ipjj···jq=

ai···ipjj···jq, c S

j (A) =

(i,...,ip,j,...,jq)∈S

ai···ipjj···jq.

In [], Yang and Yang gave the following bound for the largest singular value of a non-negative rectangular tensorA.

Theorem ([], Theorem ) LetAbe a(p,q)th order m×n dimensional nonnegative rectangular tensor.Then

λ≤ max ≤im,≤jn

Ri(A),Cj(A) ,

where

Ri(A) = m

i,...,ip=

n

j,...,jq=

aii···ipj···jq, Cj(A) =

m

i,...,ip=

n

j,...,jq=

ai···ipjj···jq.

Whenm=n, Heet al.[] have given an upper bound which is lower than that in Theo-rem .

Theorem ([], Theorem .) LetAbe a(p,q)th order n×n dimensional nonnegative rectangular tensor.Then

λ≤(A) =max

(A),(A),(A),(A) ,

where

(A) = max

i,jN,i=j

 

ai···ii···i+aj···jj···j+rji(A)

+ai···ii···iaj···jj···j+rji(A)

+ aij···jj···jrj(A)

  ,

(A) = max

i,jN,i=j

 

ai···ii···i+aj···jj···j+cji(A)

+ai···ii···iaj···jj···j+cji(A)

+ aj···jij···jcj(A)

  ,

(A) = max

i,jN,i=j

 

ai···ii···i+aj···jj···j+rji(A)

+ai···ii···iaj···jj···j+rji(A)

+ aij···jj···jcj(A)

(4)

(A) = max

i,jN,i=j

 

ai···ii···i+aj···jj···j+cji(A)

+ai···ii···iaj···jj···j+cji(A)

+ aj···jij···jrj(A)

  .

Similarly, under the condition ofm=n, by breakingN={, , . . . ,n}into disjoint subsets S and its complement S, Zhao and Sang [] provided an¯ S-type upper bound for the largest singular value of nonnegative rectangular tensors.

Theorem ([], Theorem .) LetAbe a(p,q)th order n×n dimensional nonnegative rectangular tensor,S be a nonempty proper subset of N,S be the complement of S in N.¯ Then

λ≤US(A) =max

US(A),US¯(A),US(A),U¯S(A) , where

US(A) = max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

j (A)

+ai···ii···iaj···jj···jr

S

j (A)

+ maxri(A),ci(A) r

S

j (A)

  ,

US¯(A) = max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+r

¯

S

j (A)

+ai···ii···iaj···jj···jr

¯

S

j (A)

+ maxri(A),ci(A) r

¯

S

j (A)

  ,

US

(A) = max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+c

S

j (A)

+ai···ii···iaj···jj···jc

S

j (A)

+ maxri(A),ci(A) c

S

j (A)

  ,

US¯

(A) = max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+c

¯

S

j (A)

+ai···ii···iaj···jj···jc

¯

S

j (A)

+ maxri(A),ci(A) c

¯

S

j (A)

  .

In this paper, we continue this research, and give a newS-type upper bound for the largest singular value of nonnegative rectangular tensors. It is proved that the new upper bound is better than those in Theorems -.

2 Main results

Theorem  LetAbe a(p,q)th order n×n dimensional nonnegative rectangular tensor,S be a nonempty proper subset of N,S be the complement of S in N.¯ Then

λ≤S(A) =max

S(A),S¯(A),S(A),S¯(A),S(A),¯S(A),S(A),S¯(A) , where

S(A) = max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

i (A) +r

S

j (A)

+ai···ii···iaj···jj···j+r

S

i (A) –r

S

j (A)

(5)

¯S(A) = max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+r

¯

S

i (A) +r

¯S

j (A)

+ai···ii···iaj···jj···j+r

¯

S

i (A) –r

S¯

j (A)

+ riS¯(A)rjS¯(A) ,

S(A) = max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+c

S

i (A) +c

S

j (A)

+ai···ii···iaj···jj···j+c

S

i (A) –c

S

j (A)

+ ciS(A)cjS(A) ,

¯S(A) = max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+c

¯

S

i (A) +c

S¯

j (A)

+ai···ii···iaj···jj···j+c

¯

S

i (A) –c

S¯

j (A)

+ ciS¯(A)cjS¯(A)   ,

S(A) = max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

i (A) +c

S

j (A)

+ai···ii···iaj···jj···j+r

S

i (A) –c

S

j (A)

+ riS(A)cjS(A)   ,

¯S(A) = max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+r

¯

S

j (A) +c

S¯

i (A)

+ai···ii···iaj···jj···jr

¯

S

j (A) +c

S¯

i (A)

+ rjS¯(A)ci¯S(A)   ,

S(A) = max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

j (A) +c

S

i (A)

+ai···ii···iaj···jj···jr

S

j (A) +c

S

i (A)

+ rjS(A)ciS(A)   ,

¯S(A) = max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+r

¯

S

i (A) +c

¯

S

j (A)

+ai···ii···iaj···jj···j+r

¯

S

i (A) –c

S¯

j (A)

 + rS¯

i (A)c

¯S

j (A)

  .

Proof Becauseλis the largest singular value ofA, from Theorem  in [], there are non-negative nonzero vectorsx= (x,x, . . . ,xn)Tandy= (y,y, . . . ,yn)T, such that

Axp–yq=λ

x[l–], ()

Axpyq–=λ

y[l–]. ()

Let

xt=max{xi:iS}, xh=max{xi:i∈ ¯S};

yf=max{yi:iS}, yg=max{yi:i∈ ¯S};

wi=max{xi,yi}, iN, wS=max{wi:iS}, wS¯=max{wi:i∈ ¯S}.

Then at least one ofxtandxhis nonzero, and at least one ofyf andygis nonzero. We next

divide into four cases to prove.

Case I: IfwS=xt,wS¯ =xh, thenxtyt,xhyh.

(i) Ifxhxt, thenxh=max{wi:iN}. From () of Theorem . in [], we have

λ–ah···hh···hr

S

h (A)

(6)

Ifxt= , byxh> , we haveλ–ah···hh···hr

S

h (A)≤. Thenλ≤ah···hh···h+r

S

h (A)≤

S

(A). Otherwise,xt> . From (), we have

(λ–at···tt···t)xlt–≤λxlt––at···tt···txpt–y q t

=

(i,...,ip,j,...,jq)∈S δti

···ipj···jq=

ati···ipj···jqxi· · ·xipyj· · ·yjq

+

(i,...,ip,j,...,jq)∈S

ati···ipj···jqxi· · ·xipyj· · ·yjq

(i,...,ip,j,...,jq)∈S δti···ipj···jq=

ati···ipj···jqx

l–

t +

(i,...,ip,j,...,jq)∈S

ati···ipj···jqx

l–

h

=rtS(A)xlt–+rtS(A)xlh–, i.e.,

λ–at···tt···tr

S

t (A)

xlt–≤rt S(A)xlh–. () Ifλ–at···tt···tr

S

t (A)≤, thenλ≤at···tt···t+r

S

t (A)≤S(A). Ifλ–at···tt···t–r

S

t (A) > ,

multiplying () with () and noting thatxl–

t xlh–> , we have

λ–at···tt···tr

S

t (A)

λ–ah···hh···hr

S

h (A)

rt S(A)rhS(A). ()

Solvingλin () gives

λ≤  

at···tt···t+ah···hh···h+r

S

t (A) +r

S

h (A)

+at···tt···t+r

S

t (A) –ah···hh···hr

S

h (A)

+ rtS(A)rhS(A)  

≤ max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

i (A) +r

S

j (A)

+ai···ii···iaj···jj···j+r

S

i (A) –r

S

j (A)

+ riS(A)rjS(A)  

=S(A).

(ii) Ifxtxh, similar to the proof of (i), we have

λ–ah···hh···hr

¯

S

h (A)

λ–at···tt···tr

¯

S

t (A)

rh¯S(A)rtS¯(A),

and

λ≤  

ah···hh···h+at···tt···t+r

¯

S

h (A) +r

¯

S

t (A)

+ah···hh···hat···tt···t+r

¯

S

h (A) –r

¯

S

t (A)

 + rS¯

h (A)r

¯

S

t (A)

 

≤ max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+r

¯

S

i (A) +r

¯

S

(7)

+ai···ii···iaj···jj···j+r

¯

S

i (A) –r

S¯

j (A)

+ riS¯(A)rjS¯(A)  

=S¯(A).

Case II: Assume thatwS=yf,wS¯=yg. Ifygyf, similar to the proof of (i), we have

λ–af······fc

S

f (A)

λ–ag···gg···gc

S

g (A)

cfS(A)cgS(A),

and

λ≤  

af······f+ag···gg···g+c

S

f (A) +c

S

g (A)

+af······fag···gg···g+c

S

f (A) –c

S

g (A)

+ cfS(A)cgS(A)  

≤ max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+c

S

i (A) +c

S

j (A)

+ai···ii···iaj···jj···j+c

S

i (A) –c

S

j (A)

+ ciS(A)cjS(A)  

=S(A).

Ifyfyg, similarly, we have

λ–ag···gg···gc

¯

S

g (A)

λ–af······fc

¯

S

f (A)

cS¯

g (A)c

¯

S

f (A)

and

λ≤  

ag···gg···g+af······f+c

¯

S

g (A) +c

¯

S

f (A)

+ag···g···gaf······f+c

¯

S

g (A) –c

S¯

f (A)

+ cgS¯(A)cf¯S(A)

≤ max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+c

¯

S

i (A) +c

S¯

j (A)

+ai···ii···iaj···jj···j+c

¯

S

i (A) –c

S¯

j (A)

+ ciS¯(A)cjS¯(A)  

=S¯(A).

Case III: Assume thatwS=xt,wS¯=yg. Ifygxt, similar to the proof of (i), we have

λ–at···tt···tr

S

t (A)

λ–ag···gg···gc

S

g (A)

rt S(A)cgS(A)

and

λ≤  

at···tt···t+ag···gg···g+r

S

t (A) +c

S

g (A)

+at···tt···tag···gg···g+r

S

t (A) –c

S

g (A)

+ rtS(A)cgS(A)  

≤ max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

i (A) +c

S

j (A)

+ai···ii···iaj···jj···j+r

S

i (A) –c

S

j (A)

+ riS(A)cjS(A)  

(8)

Ifxtyg, similarly, we have

λ–ag···gg···gc

¯

S

g (A)

λ–at···tt···tr

¯

S

t (A)

cgS¯(A)rtS¯(A)

and

λ≤  

at···tt···t+ag···gg···g+r

¯

S

t (A) +c

¯S

g (A)

+at···tt···tag···gg···g+r

¯

S

t (A) –c

S¯

g (A)

+ rtS¯(A)cg¯S(A)  

≤ max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+r

¯

S

j (A) +c

¯

S

i (A)

+ai···ii···iaj···jj···jr

¯

S

j (A) +c

S¯

i (A)

+ rjS¯(A)ci¯S(A)  

=S¯(A).

Case IV: Assume thatwS=yf,wS¯=xh. Ifxhyf, similar to the proof of (i), we have

λ–af······fc

S

f (A)

λ–ah···hh···hr

S

h (A)

cfS(A)rhS(A)

and

λ≤  

af······f+ah···hh···h+r

S

h (A) +c

S

f (A)

+af······fah···hh···hr

S

h (A) +c

S

f (A)

 + cS

f (A)r S h (A)   ≤ max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

j (A) +c

S

i (A)

+ai···ii···iaj···jj···jr

S

j (A) +c

S

i (A)

 + cS

i (A)r

S

j (A)

 

=S(A).

Ifyfxh, similarly, we have

λ–ah···hh···hr

¯

S

h (A)

λ–af······fc

¯

S

f (A)

rh¯S(A)cS¯

f (A)

and

λ≤  

ah···hh···h+af······f+r

¯

S

h (A) +c

S¯

f (A)

+ah···hh···haf······f+r

¯

S

h (A) –c

S¯

f (A)

+ rhS¯(A)cfS¯(A)  

≤ max

i∈¯S,jS

 

ai···ii···i+aj···jj···j+r

¯

S

i (A) +c

S¯

j (A)

+ai···ii···iaj···jj···j+r

¯

S

i (A) –c

¯

S

j (A)

 + rS¯

i (A)c ¯ S j (A)  

=S¯(A).

(9)

We next give the following comparison theorem for these upper bounds in Theorems -.

Theorem  LetAbe a(p,q)th order n×n dimensional nonnegative rectangular tensor, S be a nonempty proper subset of N,S be the complement of S in N.¯ Then

S(A)≤US(A)≤(A)≤max

i,jN

Ri(A),Cj(A) .

Proof I. By Remark . in [],(A)≤maxi,jN{Ri(A),Cj(A)}holds.

II. Next, we proveUS(A)(A). Here, we only proveUS

(A)≤(A). Similarly, we can proveUS¯

(A),US(A),U

¯

S

(A)≤(A), respectively. (i) Suppose that

US(A) = max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

j (A)

+ai···ii···iaj···jj···jr

S

j (A)

+ ri(A)r

S

j (A)

  .

From the proof of Theorem . in [], we can see that the boundUS(A) is obtained by solvingλfrom

(λ–ai···ii···i)

λ–aj···jj···jr

S

j (A)

ri(A)r

S

j (A). ()

From the proof of Theorem . in [], we can see that the bound

(A) = max

i,jN,i=j

 

ai···ii···i+aj···jj···j+rij(A)

+ai···ii···iaj···jj···jrij(A)

+ aji···ii···iri(A)

 

is obtained by solvingλfrom

(λ–ai···ii···i)

λ–aj···jj···jrij(A)

aji···ii···iri(A). ()

TakingiS,j∈ ¯Sin (), by the proof of Theorem  in [], we know that ifλsatisfies (), thenλsatisfies (), which implies that

(A)≥ max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+rij(A)

+ai···ii···iaj···jj···jrji(A)

+ aji···ii···iri(A)

 

US(A).

Obviously,US

(A)≤(A). (ii) Suppose that

US(A) = max

iS,j∈¯S

 

ai···ii···i+aj···jj···j+r

S

j (A)

+ai···ii···iaj···jj···jr

S

j (A)

+ ci(A)r

S

j (A)

(10)

Similar to the proof of (i), we can obtainUS(A)≤(A)≤(A).

III. Finally, we prove thatS(A)≤US(A). Here, we only proveS(A)≤US(A). Simi-larly, we can proveS¯(A),S(A),S¯(A),S(A),S¯(A),S(A),¯S(A)≤US(A),

respec-tively.

LetiSandj∈ ¯S. From the proof of Theorem , we can see that the boundS

(A) is obtained by solvingλfrom

λ–ai···ii···ir

S

i (A)

λ–aj···jj···jr

S

j (A)

riS(A)rjS(A). ()

(i) Suppose thatrS

i (A)r

S

j (A) = . Ifλ–ai···ii···ir

S

i (A) > ,i.e.,λ>ai···ii···i+r

S

i (A),

thenλ–aj···jj···jr

S

j (A)≤, and for anyiS,

(λ–ai···ii···i)

λ–aj···jj···jr

S

j (A)

≤≤ri(A)r

S

j (A).

That is to say, ifλsatisfies (), thenλsatisfies (), which implies thatS(A)≤US(A)≤ US(A).

Ifλ–ai···ii···ir

S

i (A)≤, thenλ–aj···jj···jr

S

j (A)≥,i.e.,λ≥aj···jj···j+r

S

j (A). From

(), we can obtainλ–aj···jj···jr

S

j (A)≤r

S

j (A),i.e.,

λ–aj···jj···jrj(A). ()

Byλ–ai···ii···ir

S

i (A)≤≤r

S

i (A),i.e.,λ–ai···ii···iri(A), we have

λ–ai···ii···ir

¯

S

i (A)≤r

¯S

i (A). ()

Multiplying () with (), we can obtain

(λ–aj···jj···j)

λ–ai···ii···ir

¯

S

i (A)

riS¯(A)rj(A), ()

which implies that ifλsatisfies (), thenλsatisfies (), consequently,S(A)≤U

¯

S

(A)≤ US(A).

(ii) Suppose thatrS

i (A)r

S

j (A) > . Then dividing () byr

S

i (A)r

S

j (A), we have

(λ–ai···ir

S

i (A))

rS

i (A)

(λ–aj···jr

S

j (A))

rS

j (A)

≤. ()

Furthermore, ifλ–ai···ir S i (A)

riS(A) ≥

, then by Lemma . in [] and (), we have

(λ–ai···i)

ri(A)

(λ–aj···jr

S

j (A))

rS

j (A)

≤(λ–ai···ir

S

i (A))

rS

i (A)

(λ–aj···jr

S

j (A))

rS

j (A)

≤.

Thus, () holds, which implies that ifλsatisfies (), thenλsatisfies (), consequently,

S(A)≤US(A). And ifλ–ai···ir S i (A)

riS(A)

≤, then () holds, which leads to () from (). This

implies that ifλsatisfies (), thenλsatisfies (), consequently,S(A)≤U

¯

S

(11)

3 Numerical examples

Example  LetA= (aijkl) be a (, )th order × dimensional nonnegative rectangular

tensor with entries defined as follows:

A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥

⎦, A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥ ⎦,

A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥ ⎦,

A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥

⎦, A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥ ⎦,

A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥ ⎦,

A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥

⎦, A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥ ⎦,

A(:, :, , ) =

⎡ ⎢ ⎣

        

⎤ ⎥ ⎦.

By Theorem , we have

λ≤.

By Theorem , we have

λ≤..

TakingS={, },S¯={}, by Theorem , we have

λ≤.;

by Theorem , we have

λ≤..

In fact,λ= .. This example shows that the upper bound in Theorem  is smaller than those in Theorems -.

Example  LetA= (aijkl) be a (, )th order × dimensional nonnegative rectangular

tensor with entries defined as follows:

(12)

the otheraijkl= . By Theorem , we have

λ≤.

In fact,λ= . This example shows that the upper bound in Theorem  is sharp.

4 Conclusions

In this paper, a newS-type upper boundS(A) of the largest singular value for a

nonneg-ative rectangular tensorAwithm=nis obtained by breakingNinto disjoint subsetsS and its complement. It is proved that the boundS(A) is better than those in [, , ].

Note here that whenn= ,(A) =US(A) =S(A), and whenn≥,(A)≥US(A)≥

S(A) always holds. How to pickSto makeS(A) as small as possible is an interesting

problem, but difficult whennis large. We will research this problem in the future.

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.

Acknowledgements

The authors are very indebted to the reviewers for their valuable comments and corrections, which improved the original manuscript of this paper. This work is supported by Natural Science Programs of Education Department of Guizhou Province (Grant No. [2016]066), Foundation of Guizhou Science and Technology Department (Grant No. [2015]2073) and National Natural Science Foundation of China (No. 11501141).

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Received: 25 December 2016 Accepted: 25 April 2017

References

1. Knowles, JK, Sternberg, E: On the ellipticity of the equations of non-linear elastostatics for a special material. J. Elast.5, 341-361 (1975)

2. Wang, Y, Aron, M: A reformulation of the strong ellipticity conditions for unconstrained hyperelastic media. J. Elast.44, 89-96 (1996)

3. Dahl, D, Leinass, JM, Myrheim, J, Ovrum, E: A tensor product matrix approximation problem in quantum physics. Linear Algebra Appl.420, 711-725 (2007)

4. Einstein, A, Podolsky, B, Rosen, N: Can quantum-mechanical description of physical reality be considered complete? Phys. Rev.47, 777-780 (1935)

5. Chang, KC, Qi, LQ, Zhou, GL: Singular values of a real rectangular tensor. J. Math. Anal. Appl.370, 284-294 (2010) 6. Yang, YN, Yang, QZ: Singular values of nonnegative rectangular tensors. Front. Math. China6(2), 363-378 (2011) 7. Lim, LH: Singular values and eigenvalues of tensors: a variational approach. In: Proceedings of the IEEE International

Workshop on Computational Advances in Multi-Sensor Adaptive Processing. CAMSAP, vol. 05, pp. 129-132 (2005) 8. Chang, KC, Pearson, K, Zhang, T: On eigenvalue problems of real symmetric tensors. J. Math. Anal. Appl.350, 416-422

(2009)

9. He, J, Liu, YM, Hua, K, Tian, JK, Li, X: Bound for the largest singular value of nonnegative rectangular tensors. Open Math.14, 761-766 (2016)

10. Zhao, JX, Sang, CL: AnS-type upper bound for the largest singular value of nonnegative rectangular tensors. Open Math.14, 925-933 (2016)

11. Li, CQ, Jiao, AQ, Li, YT: AnS-type eigenvalue localization set for tensors. Linear Algebra Appl.493, 469-483 (2016) 12. Li, CQ, Li, YT: An eigenvalue localization set for tensor with applications to determine the positive (semi-)definiteness

References

Related documents

Although MOOC automated programme evaluation subsystem is capable of assessing source programme fi les that are in learning management systems, in MOOC systems there is a grader that

Laboratory Evaluation of Novaluron as a Development Site Laboratory Evaluation of Novaluron as a Development Site Treatment for Controlling Larval Horn Flies, House Flies, and

Thus, an additional effort (beyond those of the program) was necessary to enable a long-term, sustained project-focused team alignment process that resulted in shared goals,

Several QSAR models in different combination of descriptors have been tried and five models were chosen from best five equations, whose correlation coefficients

In the present investigation, after the surface sterilization of leaves, stems and roots of the plant, different bacterial and fungal endophytes from Mentha

Energy Density in Dipole Waves: The above insights into the grav field also have implications for any Planck amplitude dipole wave in spacetime, not just the rotating dipoles

Orthogonal Frequency Division Multiplexing (OFDM) is a modulation technique for transmission of communication through recent wireless and optical channel.. The OFDM

The writer contrasts Laurence with other characters and harmoniously combines the character with the nature and the universe: “Incense fallen leaves penetrate the open