Bounds for eigenvalues of nonsingular H-tensor
|
|
- Eustacia Boone
- 6 years ago
- Views:
Transcription
1 Electronc Journal of Lnear Algebra Volume 9 Specal volume for Proceedngs of the Internatonal Conference on Lnear Algebra and ts Applcatons dedcated to Professor Ravndra B. Bapat Artcle 05 Bounds for egenvalues of nonsngular H-tensor Xue-Zhong Wang School of Mathematcs and Statstcs, Hex Unversty, xuezhong-wang@6.com Ymn We School of Mathematcs and Computer Scence, Guzhou Normal Unversty, ymwe_cn@yahoo.com Follow ths and addtonal works at: Recommended Ctaton Wang, Xue-Zhong and We, Ymn. (05), "Bounds for egenvalues of nonsngular H-tensor", Electronc Journal of Lnear Algebra, Volume 9, pp DOI: Ths Artcle s brought to you for free and open access by Wyomng Scholars Repostory. It has been accepted for ncluson n Electronc Journal of Lnear Algebra by an authorzed edtor of Wyomng Scholars Repostory. For more nformaton, please contact scholcom@uwyo.edu.
2 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 BOUNDS FOR EIGENVALUES OF NONSINGULAR H-TENSOR XUE-ZHONG WANG AND YIMIN WEI Abstract. The bounds for the Z-spectral radus of nonsngular H-tensor, the upper and lower bounds for the mnmum H-egenvalue of nonsngular (strong) M-tensor are studed n ths paper. Sharper bounds than known bounds are obtaned. Numercal examples llustrate that our bounds gve tghter bounds. Dedcated to Professor Ravndra B. Bapat on the occason of hs 60th brthday Key words. M-tensor, H-tensor, Z-spectral radus, Mnmum H-egenvalue. AMS subject classfcatons. 5A8, 5A69, 65F5, 65F0.. Introducton. Egenvalue problems of hgher order tensors have become an mportant topc n appled mathematcs branch, numercal multlnear algebra, and t has a wde range of practcal applcatons [, 3, 4,, 8,, 3, 4, 5, 6, 9, 0, ]. A tensor can be regarded as a hgher-order generalzaton of a matrx. Let C (respectvely, R) be the complex (respectvely, real) feld. An m-order n-dmensonal square tensor A wth n m entres can be defned as follows, A = (a... m ), a... m C,,,..., m n. Let A be an m-order n-dmensonal tensor, and x C n. Then (.) Ax m = n,,..., m= a... m x x...x m, and Ax m s a vector n C n, wth ts th component defned by (Ax m ) = n, 3,..., m= a... m x x 3 x m. Receved by the edtorson February 5, 05. Accepted forpublcaton onjuly 0, 05. Handlng Edtor: Manjunatha Prasad Karantha. School of Mathematcs and Statstcs, Hex Unversty, Zhangye, , P. R. Chna (xuezhongwang77@6.com ). Ths author s supported by the Natonal Natural Scence Foundaton of Chna under grant 737. School of Mathematcs and Computer Scence, Guzhou Normal Unversty, Guyang 55000, P.R. Chna (ymwe cn@yahoo.com). Ths author s supported by the Natonal Natural Scence Foundaton of Chna under grant
3 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 4 X.Z. Wang, and Y. We Let r be a postve nteger. Then x [r] = [x r,xr,...,xr n ] s a vector n C n, wth ts th component defned by x r. The followng two defntons were frst ntroduced and studed by Q and Lm, respectvely. Defnton.. ([8,, 4]) Let A be an m-order n-dmensonal real tensor. A par (λ,x) C (C n \0) s called an egenvalue-egenvector (or smply egenpar) of A, f t satsfes the equaton Ax m = λx [m ]. We call (λ,x) an H-egenpar, f both λ and x are real. Defnton.. ([8,, 4]) Let A be an m-order n-dmensonal real tensor. A par (λ,x) C (C n \0) s called an E-egenvalue and E-egenvector (or smply E-egenpar) of A, f they satsfy the equaton Ax m = λx, x x =. We call (λ,x) a Z-egenpar, f both λ and x real. Here x denotes the transpose of x. In [8], He and Huang presented the defnton of the Z-spectral radus of A as follows. Defnton.3. ([, 8]) Suppose that A s an m-order n-dmensonal real tensor. Let σ(a) denote the Z-spectrum of A by the set of all Z-egenvalues of A. Assume that σ(a). Then the Z-spectral radus of A s denoted by ρ(a) = sup λ : λ σ(a). Partcularly, f A s an m-order n-dmensonal nonnegatve tensor, then ρ(a) = max λ : λ σ(a). Recently, many contrbutons have been made on the bounds of the spectral radus of nonnegatve tensor n [, 0, 3, 4]. Smlarly, bounds for the Z-spectral radus were gven n [8] for the H-tensors. Also, n [7], He and Huang obtaned the upper and lower bounds for the mnmum H-egenvalue of nonsngular (strong) M-tensors. In ths paper, our purpose s to propose sharper bounds for the Z-spectral radus of nonsngular H-tensors and for the mnmum H-egenvalue of nonsngular (strong) M-tensors.
4 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 Bounds for Egenvalues of Nonsngular H-tensor 5. Prelmnares. We start ths secton wth some fundamental notons and propertes on tensors. An m-order n-dmensonal tensor A s called nonnegatve ([, 3,9,6, 0,]), feachentrysnonnegatve. SmlartoZ-matrces,wedenotetensors wth all non-postve off-dagonal entres by Z-tensors. The m-order n-dmensonal dentty tensor, denoted by I = (δ... m ), s the tensor wth entres, = δ... m = = = m, 0, otherwse. The tensor D = (d... m ) s the dagonal tensor of A = (a... m ), f d... m = a... m, = = = m, 0, otherwse. Defnton.. ([8]) Let A and B be two m-order n-dmensonal tensors. If there exsts matrces P and Q of n-order wth PIQ = I such that B = PAQ, then we say that the two tensors are smlar. Let the tensor F be assocated wth an undrected d-partte graph G(F) = (V,E(F)), the vertex set of whch s the dsjont unon V = d j= V j, wth V j = [m j ],j [d]. The edge ( k, l ) V k V l,k l belongs to E(F) f and only f f,,..., d > 0 for some d ndces,..., d \ k, l. The tensor F s called weakly rreducble f the graph G(F) s connected. We call F rreducble f for each proper nonempty subset I V, the followng condton holds: let J := V \I. Then there exsts k [d], k I V k and j J V j for each j [d]\k such that f,..., d > 0. Ths defnton of rreducblty agrees wth [, 3]. Fredland et al. [6] showed that f F s rreducble then F s weakly rreducble and presented the followng results. Lemma.. ([6]) If the nonnegatve tensor A s rreducble, then A s weakly rreducble. For m =, A s rreducble f and only f A s weakly rreducble. Lemma. llustrates that a nonnegatve rreducble tensor must be weakly rreducble. For a general tensor A = (a... m ), a... m C, we can draw the followng concluson. Lemma.3. If a tensor A s rreducble, then A s weakly rreducble. For m =, A s rreducble f and only f A s weakly rreducble. Proof. Let A = D E, where D s the dagonal tensor of A. If A s rreducble, t s equvalent that E s rreducble. Note that E s a nonnegatve tensor, by Lemma., E s weakly rreducble, and then A s weakly rreducble. Smlar to the proof of [6], we can get case m =.
5 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 6 X.Z. Wang, and Y. We Lemma.4. ([4]) The product of the egenvalues λ of tensor A s equal to det(a), that s, det(a) = n(m ) n = We call tensor A s nonsngular, f det(a) 0. Defnton.5. ([5, 3]) We call a tensor A an M-tensor, f there exst a nonnegatve tensor B and a postve real number η ρ(b) such that A = ηi B. If η > ρ(b) then A s called a nonsngular (strong) M-tensor. In [3], Zhang et al. obtaned the followng result for the H-egenvalues of a nonsngular (strong) M-tensor. Lemma.6. ([3]) Let A be a nonsngular (strong) M-tensor and τ(a) denote the mnmal value of the real part of all egenvalues of A. Then τ(a) > 0 s an H- egenvalue of A wth a nonnegatve egenvector. If A s weakly rreducble Z-tensor, then τ(a) > 0 s the unque egenvalue wth a postve egenvector. Yang and Yang [0], Yuan and You [] showed that f λ. (.) B = D (m ) AD (m ), where D s a dagonal nonsngular matrx, then A and B are smlar. It s easy to see that the smlarty relaton s an equvalent relaton, and smlar tensors have the same characterstc polynomals, and thus they have the same spectrum (as a mult-set). Now, we ntroduce the comparson tensor of any tensor A. Defnton.7. ([5]) Let A = (a... m ) be an m-order and n-dmensonal tensor. We call a tensor M(A) = (m... m ) the comparson tensor of A f m... m = a... m, (... m ) = (... ), a... m, (... m ) (... ). In the followng, some basc defntons are gven, whch wll be used n the subsequent dscusson. In [5], Dng et al. extended H-matrces to H-tensors as follows. Defnton.8. ([5]) We call a tensor A an H-tensor, f ts comparson tensor s an M-tensor; we call t as a nonsngular H-tensor, f ts comparson tensor s a nonsngular M-tensor.
6 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 Bounds for Egenvalues of Nonsngular H-tensor 7 Very recently, Kannan et al. [7] establshed some propertes of strong H-tensors and general H-tensors. Remark.9. It follows from defnton.8 that an M-tensor s an H-tensor and a nonsngular M-tensor s a nonsngular H-tensor. Defnton.0. ([5]) Let A be an m-order and n-dmensonal tensor. A s quas-dagonally domnant, f there exsts a postve vector x = (x,x,...,x n ) such that (.) a... x m ( 3... m) (...) a... m x x 3...x m, =,,...,n. If the strct nequalty holds n (.) for all, A s called quas-strctly dagonally domnant. Lemma.. ([5]) A tensor A s a nonsngular H-tensor f and only f t s quas-strctly dagonally domnant. 3. Bounds for the spectral radus of H-tensors. In ths secton, we present some bounds for the Z-spectral radus of H-tensors. For convenence, let N =,,...,n. We denote by R (A) and R(A) the sum of the th row and the maxmal row sum of A, respectvely,.e., R (A) = n, 3,..., m= a... m, R(A) = maxr (A). In [], Chang, Pearson, and Zhang have gven the followng bounds for the Z- egenvalues of an m-order n-dmensonal tensor A. Lemma 3.. ([]) Let A be an m-order and n-dmensonal tensor wth σ(a). Then ρ(a) n nmax a... m = nr(a). N, 3,..., m= For postvely homogeneous operators, Song and Q [9] establshed the relatonshp between the Gelfand formula and the spectral radus, as well as the upper bound of the spectral radus. Followng the Corollary 4.5 n [9], He and Huang [8] presented the followng lemma. Lemma 3.. ([8, 9]) Let A be an m-order and n-dmensonal tensor wth σ(a). Then n ρ(a) max a... m = R(A). N, 3,..., m=
7 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 8 X.Z. Wang, and Y. We Based on the above lemma, we obtan some upper bounds for the Z-spectral radus when A s a nonsngular H-tensor as follows. Theorem 3.3. Let A be an m-order and n-dmensonal nonsngular H-tensor wth σ(a). Then ρ(a) max N a.... Proof. Snce A s a nonsngular H-tensor, there exsts a postve dagonal matrx X =dag(x,x,...,x n ) such that AX (m ) s strctly dagonally domnant. Then s also strctly dagonally domnant,.e., a... > (, 3,...,m) (,,...,) X (m ) AX (m ), a... m x x 3...x m x m, N. Because X (m ) AX (m ) and A are smlar, t follows that ρ(a) = ρ(x (m ) AX (m ) ) R(X (m ) AX (m ) ) n = max, 3,..., m= = max( a... + < max a.... a...m x x 3...xm x m (, 3,...,m) (,,...,) a...m x x 3...xm ) x m By the above theorem, the followng corollary can be obtaned easly. Corollary 3.4. If A s an m-order and n-dmensonal nonsngular H-tensor wth σ(a), then ρ(a) mn R(A),max a.... N Corollary 3.5. If A s an m-order and n-dmensonal nonsngular M-tensor wth σ(a), then ρ(a) mn R(A),max a.... N
8 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 Bounds for Egenvalues of Nonsngular H-tensor 9 Remark 3.6. In fact, the bound of Theorem 3.3 s not better than the bound n Lemma 3. for dagonally domnant H-tensors. However, by Lemma. we know that H-tensors are not necessary dagonally domnant. Thus, the bound gven n Theorem 3.3 s sharper than the one gven n Lemma 3. for non-dagonally domnant H-tensors. The followng example llustrates the same. Example 3.7. Let A = (a jk ) be an 3-order -dmenson tensor wth the form, a =., a =, a =, a =, a =, a =, a =, a =.. It s easy to check that A s quas-strctly dagonally domnant and then A s an nonsngular H-tensor. By Lemma 3., we have, ρ(a) nr(a) = By Lemma 3., we obtan the upper bound, ρ(a) R(A) = 4.. Now from Theorem 3.3, we have the followng bound: ρ(a) max a =.. Obvously, the bound gven n Theorem 3.3 s sharper than those gven n Lemma 3. and Lemma Bounds for the mnmum egenvalue of M-tensors. In ths secton, we consder the mnmum H-egenvalue of M-tensors. We adopt the followng notaton throughout ths secton. We defne a nonnegatve matrx M(A), where (M(A)) j = r (A), = j, a j...j, j. r j (A) = δ...m =0 δ j...m =0 r (A) a j...j, and j (A) = [a... a jj...j +r j (A)] 4a j...j r j (A), wth r (M(A)) = M(A) j, r (A) = r (A) r (M(A)),
9 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 0 X.Z. Wang, and Y. We and j (A) = [a... a jj...j + r (A)] +4r (M(A))r j (A). Lemma 4.. Let A be a weakly rreducble M-tensor and t = k,j a k...k, N. () If 0 t [a... a jj...j +r j (A) r j(a)],,j N, then j (A) j (A). () If t [a... a jj...j +r j (A) r j(a)],,j N, then j (A) j (A). Proof. For convenence, denote a = a... a jj...j + r j (A), notce that r (A) = r j (A) t. Thus j (A) j (A) = a 4a j...j r j (A) (a t ) 4[(t a j...j )r j (A)] = t +[a r j(a)]t. The equaton t +[a r j(a)]t = 0 has two roots t = 0 and t = [a r j (A)]. Therefore, f 0 t [a r j (A)]. Thus j (A) j (A), and f t [a r j (A)], then j (A) j (A). In [7], He and Huang gave the followng bounds for the mnmum H-egenvalue of rreducble M-tensors. Lemma 4.. ([7]) Let A be an rreducble M-tensor. Then τ(a) mn N a... Lemma 4.3. ([7]) Let A = (a... m ) be an rreducble M-tensor. Then (4.) mn max a... +a jj...j r j (A) j (A) τ(a) a... +a jj...j r j (A) j (A). For the weakly rreducble M-tensor, we have a result smlar to that of Lemma 4. n the followng. Lemma 4.4. Let A be a weakly rreducble M-tensor. Then τ(a) mn N a... Proof. The proof s smlar to that of Theorem. n [7], and omt t. Based on the above lemma, we derve the bounds for the mnmum H-egenvalue of weakly rreducble M-tensors as follows.
10 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 Bounds for Egenvalues of Nonsngular H-tensor Theorem 4.5. Let A = (a... m ) be a weakly rreducble M-tensor. Then mn a... +a jj...j r (A) j (A) τ(a) (4.) a... +a jj...j r (A) j (A). max Proof. Let x > 0 be an egenvector of A correspondng to τ(a)..e., (4.3) Ax m = τ(a)x [m ]. Suppose that From (4.3), we have [τ(a) a tt...t ]x m t = x t x s max N x : t, s. δ...m =0 ( 3... m) (jj...j) a t... m x x 3...x m + j t a tj...j x m j. Takng modulus n the above equaton and usng the trangle nequalty gves, τ(a) a tt...t x m t a t... m x x 3...x m + a tj...j x m j δ...m =0 j t ( 3... m) (jj...j) a t... m x m t + a tj...j x m s j t Note that τ(a) a tt...t, and δ...m =0 ( 3... m) (jj...j) = r t (A)x m t +r t (M)x m s. Equvalently [a tt...t τ(a)]x m t r t (A)x m t (4.4) [a tt...t τ(a) r t (A)]x m t From (4.3), we also obtan (4.5) [a ss...s τ(a)]x m s Multplyng nequaltes (4.4) wth (4.5), we have +r t (M)x m s. r t (M)x m s. r s (A)x m t. [a tt...t τ(a) r t (A)][a ss...s τ(a)]x m t x m s r t (M)r s (A)x m s x m t.
11 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 X.Z. Wang, and Y. We Note that x m t x m s < 0, and (4.6) [a tt...t τ(a) r t (A)][a ss...s τ(a)] r t (M)r s (A). Ths s τ(a) [a tt...t +a ss...s r t (A)]τ(A) r t (M)r s (A)+[a tt...t r t (A)]a ss...s 0. Note that [a tt...t +a ss...s r t (A)] 4[a ss...s r t (A)]a tt...t = [a tt...t a ss...s + r t (A)]. Ths gves the followng bound for τ(a), On the other hand, let From (4.3), we have τ(a) a tt...t +a ss...s r t (A) ts (A) mn (4.7) (a uu...u τ(a))x m u = a... +a jj...j r (A) j (A). x l x u mn N x : t, s. l. δ u...m =0 a u... m x x 3...x m r u (A)x m and (a ll...l τ(a))x m l Then = δ l...m =0 ( 3... m) (jj...j) r l (A)x m l a l... m x x 3...x m a lj...j x m j j l +r l (M)x m u. (4.8) [a ll...l τ(a) r l (A)]x m l Multplyng nequaltes (4.7) wth (4.8), we have r l (M)x m u. (4.9) [a uu...u τ(a)][a ll...l τ(a) r l (A)] r l (M)r u (A). Inequalty (4.9) s equvalent to τ(a) [a ll...l +a uu...u r l (A)]τ(A) r l (M)r u (A)+[a ll...l r l (A)]a uu...u 0. Ths gves the followng bound for τ(a), τ(a) a ll...l +a uu...u r l (A) lu (A) a... +a jj...j r j (A) j (A) max.
12 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 Ths completes the proof. Bounds for Egenvalues of Nonsngular H-tensor 3 In what follows, we wll show the bounds n Theorem 4.5 are tghter and sharper than those of Lemma 4.3. Theorem 4.6. Under the condtons of Lemma 4.. If [ ] 0 t a... a jj...j +r j (A) r j(a),,j N, then mn mn a... +a jj...j r j (A) j (A) a... +a jj...j r (A) j (A). Proof. From the Lemma 4., f 0 t [a... a jj...j +r j (A) r j(a), then j (A) j (A). Note that r (A) = r j (A) t, and then a... +a jj...j r j (A) j (A) a... +a jj...j r (A) j (A),,j N, whch mples that mn mn a... +a jj...j r j (A) j (A) a... +a jj...j r (A) j (A). Remark 4.7. From Theorem 4.6, we can see that the lower bound of τ(a) n Theorem 4.5 s sharper than those of Lemma 4.3, f [ ] 0 t a... a jj...j +r j (A) r j(a),,j N. Theorem 4.8. Under the condtons of Lemma 4.. If [ ] t a... a jj...j +r j (A) r j(a) +,,j N, then max max a... +a jj...j r (A) j (A) a... +a jj...j r j (A) j (A).
13 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 4 X.Z. Wang, and Y. We Proof. From the proof of Lemma 4., we know that (4.0) j (A) j (A)+t = t +[(a r j (A))+]t. Because equaton (4.0) has two roots t = 0 and t = [a r j (A)]+. Therefore, f t (a r j (A))+, then Note that r (A) = r j (A) t, we have j (A) j (A) t. r (A)+ j (A) r j (A)+ j (A). Hence max max a... +a jj...j r (A) j (A) a... +a jj...j r j (A) j (A). Remark 4.9. From Theorem 4.8, we can see that the upper bound of τ(a) n Theorem 4.5 s sharper than those n Lemma 4.3, f t [a... a jj...j + r j (A) r j (A)]+,,j N. Remark 4.0. Snce t 0, f 0 t [a... a jj...j + r j (A) r j(a)] for some, and t [a... a jj...j +r j (A) r j(a)]+ for some other, we can see that the upper and lower bounds of τ(a) n Theorem 4.5 are tghter than those of Lemma 4.3. The followng example shows ths. Example 4.. Let A = (a jk ) be an 4-order 3-dmenson tensor wth the form, a = a = 5, a 333 = a 444 = 4, a jj =, j, a = 0.5, a =, a jk = 0, otherwse. By Lemma 4.3, we have the bound 0.64 τ(a) We have our new bounds from Theorem τ(a).769.
14 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 Bounds for Egenvalues of Nonsngular H-tensor 5 5. Concluson. In ths paper, the Z-spectral radus for nonsngular H-tensor and the mnmum H-egenvalue of nonsngular (strong) M-tensor are studed. Furthermore, we prove that the results of ths paper are sharper than those of [, 8] and [7]. Acknowledgement. The authors would lke to thank the Edtor, Prof. Manjunatha Prasad Karantha and the referee for ther valuable and detaled comments on our manuscrpt. We also thank Prof. L. Q for remndng us of the recent paper [7] durng our revson. REFERENCES [] K. C. Chang, K. J. Pearson, and Tan Zhang. Some varatonal prncples for Z-egenvalues of nonnegatve tensors. Lnear Algebra Appl., 438():466 48, 03. [] K. C. Chang, Kelly Pearson, and Tan Zhang. Perron-Frobenus theorem for nonnegatve tensors. Commun. Math. Sc., 6():507 50, 008. [3] K. C. Chang, Kelly Pearson, and Tan Zhang. On egenvalue problems of real symmetrc tensors. J. Math. Anal. Appl., 350():46 4, 009. [4] K. C. Chang, Kelly J. Pearson, and Tan Zhang. Prmtvty, the convergence of the NQZ method, and the largest egenvalue for nonnegatve tensors. SIAM J. Matrx Anal. Appl., 3(3):806 89, 0. [5] Weyang Dng, Lqun Q, and Ymn We. M-tensors and nonsngular M-tensors. Lnear Algebra Appl., 439(0): , 03. [6] S. Fredland, S. Gaubert, and L. Han. Perron-Frobenus theorem for nonnegatve multlnear forms and extensons. Lnear Algebra Appl., 438(): , 03. [7] Jun He and Tng-Zhu Huang. Inequaltes for M-tensors. Journal of Inequaltes and Applcatons, 04():4, 04. [8] Jun He and Tng-Zhu Huang. Upper bound for the largest Z-egenvalue of postve tensors. Appl. Math. Lett., 38:0 4, 04. [9] ShengLong Hu, ZhengHa Huang, and LQun Q. Strctly nonnegatve tensors and nonnegatve tensor partton. Sc. Chna Math., 57():8 95, 04. [0] Chaoqan L, Yaotang L, and Xu Kong. New egenvalue ncluson sets for tensors. Numercal Lnear Algebra wth Applcatons, ():39 50, 04. [] LH Lm. Sngular values and egenvalues of tensors: A varatonal approach. In IEEE CAMSAP 005: Frst Internatonal Workshop on Computatonal Advances n Mult-Sensor Adaptve Processng, pages 9 3. IEEE, 005. [] Yongjun Lu, Guanglu Zhou, and Nur Fadhlah Ibrahm. An always convergent algorthm for the largest egenvalue of an rreducble nonnegatve tensor. J. Comput. Appl. Math., 35():86 9, 00. [3] Mchael Ng, Lqun Q, and Guanglu Zhou. Fndng the largest egenvalue of a nonnegatve tensor. SIAM J. Matrx Anal. Appl., 3(3): , 009. [4] Lqun Q. Egenvalues of a real supersymmetrc tensor. J. Symbolc Comput., 40(6):30 34, 005. [5] Lqun Q. Egenvalues and nvarants of tensors. J. Math. Anal. Appl., 35(): , 007. [6] Lqun Q. Symmetrc nonnegatve tensors and copostve tensors. Lnear Algebra Appl., 439():8 38, 03. [7] M. Rajesh Kanan, N. Shaked-Monderer, and A. Berman. Some propertes of strong H-tensors and general H-tensors. Lnear Algebra Appl., 476:4 55, 05.
15 Electronc Journal of Lnear Algebra ISSN Volume 9, pp. 3-6, September 05 6 X.Z. Wang, and Y. We [8] Ja-Yu Shao. A general product of tensors wth applcatons. Lnear Algebra Appl., 439(8): , 03. [9] Ysheng Song and Lqun Q. Spectral propertes of postvely homogeneous operators nduced by hgher order tensors. SIAM J. Matrx Anal. Appl., 34(4):58 595, 03. [0] Qngzh Yang and Yunng Yang. Further results for Perron-Frobenus theorem for nonnegatve tensors II. SIAM J. Matrx Anal. Appl., 3(4):36 50, 0. [] Yunng Yang and Qngzh Yang. Further results for Perron-Frobenus theorem for nonnegatve tensors. SIAM J. Matrx Anal. Appl., 3(5):57 530, 00. [] Pngzh Yuan and Lhua You. On the smlarty of tensors. Lnear Algebra Appl., 458:534 54, 04. [3] Lpng Zhang, Lqun Q, and Guanglu Zhou. M-tensors and some applcatons. SIAM J. Matrx Anal. Appl., 35():437 45, 04.
arxiv: v1 [math.sp] 3 Nov 2011
ON SOME PROPERTIES OF NONNEGATIVE WEAKLY IRREDUCIBLE TENSORS YUNING YANG AND QINGZHI YANG arxv:1111.0713v1 [math.sp] 3 Nov 2011 Abstract. In ths paper, we manly focus on how to generalze some conclusons
More informationThe lower and upper bounds on Perron root of nonnegative irreducible matrices
Journal of Computatonal Appled Mathematcs 217 (2008) 259 267 wwwelsevercom/locate/cam The lower upper bounds on Perron root of nonnegatve rreducble matrces Guang-Xn Huang a,, Feng Yn b,keguo a a College
More informationPerron Vectors of an Irreducible Nonnegative Interval Matrix
Perron Vectors of an Irreducble Nonnegatve Interval Matrx Jr Rohn August 4 2005 Abstract As s well known an rreducble nonnegatve matrx possesses a unquely determned Perron vector. As the man result of
More informationThe Order Relation and Trace Inequalities for. Hermitian Operators
Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence
More informationAPPENDIX A Some Linear Algebra
APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,
More informationThe dominant eigenvalue of an essentially nonnegative tensor
NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS Numer. Lnear Algebra Appl. 2013; 00:1 13 Publshed onlne n Wley InterScence (www.nterscence.wley.com). The domnant egenvalue of an essentally nonnegatve tensor
More informationMATH Homework #2
MATH609-601 Homework #2 September 27, 2012 1. Problems Ths contans a set of possble solutons to all problems of HW-2. Be vglant snce typos are possble (and nevtable). (1) Problem 1 (20 pts) For a matrx
More informationTHE Hadamard product of two nonnegative matrices and
IAENG Internatonal Journal of Appled Mathematcs 46:3 IJAM_46_3_5 Some New Bounds for the Hadamard Product of a Nonsngular M-matrx and Its Inverse Zhengge Huang Lgong Wang and Zhong Xu Abstract Some new
More informationDiscrete Mathematics. Laplacian spectral characterization of some graphs obtained by product operation
Dscrete Mathematcs 31 (01) 1591 1595 Contents lsts avalable at ScVerse ScenceDrect Dscrete Mathematcs journal homepage: www.elsever.com/locate/dsc Laplacan spectral characterzaton of some graphs obtaned
More informationOn the energy of singular graphs
Electronc Journal of Lnear Algebra Volume 26 Volume 26 (2013 Artcle 34 2013 On the energy of sngular graphs Irene Trantafllou ern_trantafllou@hotmalcom Follow ths and addtonal works at: http://repostoryuwyoedu/ela
More informationOn the spectral norm of r-circulant matrices with the Pell and Pell-Lucas numbers
Türkmen and Gökbaş Journal of Inequaltes and Applcatons (06) 06:65 DOI 086/s3660-06-0997-0 R E S E A R C H Open Access On the spectral norm of r-crculant matrces wth the Pell and Pell-Lucas numbers Ramazan
More informationGeneral viscosity iterative method for a sequence of quasi-nonexpansive mappings
Avalable onlne at www.tjnsa.com J. Nonlnear Sc. Appl. 9 (2016), 5672 5682 Research Artcle General vscosty teratve method for a sequence of quas-nonexpansve mappngs Cuje Zhang, Ynan Wang College of Scence,
More informationGoogle PageRank with Stochastic Matrix
Google PageRank wth Stochastc Matrx Md. Sharq, Puranjt Sanyal, Samk Mtra (M.Sc. Applcatons of Mathematcs) Dscrete Tme Markov Chan Let S be a countable set (usually S s a subset of Z or Z d or R or R d
More informationRandić Energy and Randić Estrada Index of a Graph
EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS Vol. 5, No., 202, 88-96 ISSN 307-5543 www.ejpam.com SPECIAL ISSUE FOR THE INTERNATIONAL CONFERENCE ON APPLIED ANALYSIS AND ALGEBRA 29 JUNE -02JULY 20, ISTANBUL
More informationA CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS
Journal of Mathematcal Scences: Advances and Applcatons Volume 25, 2014, Pages 1-12 A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS JIA JI, WEN ZHANG and XIAOFEI QI Department of Mathematcs
More informationBinomial transforms of the modified k-fibonacci-like sequence
Internatonal Journal of Mathematcs and Computer Scence, 14(2019, no. 1, 47 59 M CS Bnomal transforms of the modfed k-fbonacc-lke sequence Youngwoo Kwon Department of mathematcs Korea Unversty Seoul, Republc
More informationA new eigenvalue inclusion set for tensors with its applications
COMPUTATIONAL SCIENCE RESEARCH ARTICLE A new egenvalue ncluson set for tensors wth ts applcatons Cal Sang 1 and Janxng Zhao 1 * Receved: 30 Deceber 2016 Accepted: 12 Aprl 2017 Frst Publshed: 20 Aprl 2017
More information2.3 Nilpotent endomorphisms
s a block dagonal matrx, wth A Mat dm U (C) In fact, we can assume that B = B 1 B k, wth B an ordered bass of U, and that A = [f U ] B, where f U : U U s the restrcton of f to U 40 23 Nlpotent endomorphsms
More informationBounds for Spectral Radius of Various Matrices Associated With Graphs
45 5 Vol.45, No.5 016 9 AVANCES IN MATHEMATICS (CHINA) Sep., 016 o: 10.11845/sxjz.015015b Bouns for Spectral Raus of Varous Matrces Assocate Wth Graphs CUI Shuyu 1, TIAN Guxan, (1. Xngzh College, Zhejang
More informationConvexity preserving interpolation by splines of arbitrary degree
Computer Scence Journal of Moldova, vol.18, no.1(52), 2010 Convexty preservng nterpolaton by splnes of arbtrary degree Igor Verlan Abstract In the present paper an algorthm of C 2 nterpolaton of dscrete
More informationA New Refinement of Jacobi Method for Solution of Linear System Equations AX=b
Int J Contemp Math Scences, Vol 3, 28, no 17, 819-827 A New Refnement of Jacob Method for Soluton of Lnear System Equatons AX=b F Naem Dafchah Department of Mathematcs, Faculty of Scences Unversty of Gulan,
More informationDIFFERENTIAL FORMS BRIAN OSSERMAN
DIFFERENTIAL FORMS BRIAN OSSERMAN Dfferentals are an mportant topc n algebrac geometry, allowng the use of some classcal geometrc arguments n the context of varetes over any feld. We wll use them to defne
More informationOn Finite Rank Perturbation of Diagonalizable Operators
Functonal Analyss, Approxmaton and Computaton 6 (1) (2014), 49 53 Publshed by Faculty of Scences and Mathematcs, Unversty of Nš, Serba Avalable at: http://wwwpmfnacrs/faac On Fnte Rank Perturbaton of Dagonalzable
More informationRandom Walks on Digraphs
Random Walks on Dgraphs J. J. P. Veerman October 23, 27 Introducton Let V = {, n} be a vertex set and S a non-negatve row-stochastc matrx (.e. rows sum to ). V and S defne a dgraph G = G(V, S) and a drected
More informationLecture 10: May 6, 2013
TTIC/CMSC 31150 Mathematcal Toolkt Sprng 013 Madhur Tulsan Lecture 10: May 6, 013 Scrbe: Wenje Luo In today s lecture, we manly talked about random walk on graphs and ntroduce the concept of graph expander,
More informationSL n (F ) Equals its Own Derived Group
Internatonal Journal of Algebra, Vol. 2, 2008, no. 12, 585-594 SL n (F ) Equals ts Own Derved Group Jorge Macel BMCC-The Cty Unversty of New York, CUNY 199 Chambers street, New York, NY 10007, USA macel@cms.nyu.edu
More information5 The Rational Canonical Form
5 The Ratonal Canoncal Form Here p s a monc rreducble factor of the mnmum polynomal m T and s not necessarly of degree one Let F p denote the feld constructed earler n the course, consstng of all matrces
More informationA property of the elementary symmetric functions
Calcolo manuscrpt No. (wll be nserted by the edtor) A property of the elementary symmetrc functons A. Esnberg, G. Fedele Dp. Elettronca Informatca e Sstemstca, Unverstà degl Stud della Calabra, 87036,
More informationChapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems
Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons
More informationLectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix
Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could
More information8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS
SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 493 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces you have studed thus far n the text are real vector spaces because the scalars
More informationSingular Value Decomposition: Theory and Applications
Sngular Value Decomposton: Theory and Applcatons Danel Khashab Sprng 2015 Last Update: March 2, 2015 1 Introducton A = UDV where columns of U and V are orthonormal and matrx D s dagonal wth postve real
More informationfor Linear Systems With Strictly Diagonally Dominant Matrix
MATHEMATICS OF COMPUTATION, VOLUME 35, NUMBER 152 OCTOBER 1980, PAGES 1269-1273 On an Accelerated Overrelaxaton Iteratve Method for Lnear Systems Wth Strctly Dagonally Domnant Matrx By M. Madalena Martns*
More informationFACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP
C O L L O Q U I U M M A T H E M A T I C U M VOL. 80 1999 NO. 1 FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP BY FLORIAN K A I N R A T H (GRAZ) Abstract. Let H be a Krull monod wth nfnte class
More informationSalmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2
Salmon: Lectures on partal dfferental equatons 5. Classfcaton of second-order equatons There are general methods for classfyng hgher-order partal dfferental equatons. One s very general (applyng even to
More informationMATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS
MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS These are nformal notes whch cover some of the materal whch s not n the course book. The man purpose s to gve a number of nontrval examples
More informationCOMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
More informationThe binomial transforms of the generalized (s, t )-Jacobsthal matrix sequence
Int. J. Adv. Appl. Math. and Mech. 6(3 (2019 14 20 (ISSN: 2347-2529 Journal homepage: www.jaamm.com IJAAMM Internatonal Journal of Advances n Appled Mathematcs and Mechancs The bnomal transforms of the
More informationDeriving the X-Z Identity from Auxiliary Space Method
Dervng the X-Z Identty from Auxlary Space Method Long Chen Department of Mathematcs, Unversty of Calforna at Irvne, Irvne, CA 92697 chenlong@math.uc.edu 1 Iteratve Methods In ths paper we dscuss teratve
More informationNorms, Condition Numbers, Eigenvalues and Eigenvectors
Norms, Condton Numbers, Egenvalues and Egenvectors 1 Norms A norm s a measure of the sze of a matrx or a vector For vectors the common norms are: N a 2 = ( x 2 1/2 the Eucldean Norm (1a b 1 = =1 N x (1b
More informationThe Degrees of Nilpotency of Nilpotent Derivations on the Ring of Matrices
Internatonal Mathematcal Forum, Vol. 6, 2011, no. 15, 713-721 The Degrees of Nlpotency of Nlpotent Dervatons on the Rng of Matrces Homera Pajoohesh Department of of Mathematcs Medgar Evers College of CUNY
More informationLecture 3. Ax x i a i. i i
18.409 The Behavor of Algorthms n Practce 2/14/2 Lecturer: Dan Spelman Lecture 3 Scrbe: Arvnd Sankar 1 Largest sngular value In order to bound the condton number, we need an upper bound on the largest
More information2 More examples with details
Physcs 129b Lecture 3 Caltech, 01/15/19 2 More examples wth detals 2.3 The permutaton group n = 4 S 4 contans 4! = 24 elements. One s the dentty e. Sx of them are exchange of two objects (, j) ( to j and
More informationThe Jacobsthal and Jacobsthal-Lucas Numbers via Square Roots of Matrices
Internatonal Mathematcal Forum, Vol 11, 2016, no 11, 513-520 HIKARI Ltd, wwwm-hkarcom http://dxdoorg/1012988/mf20166442 The Jacobsthal and Jacobsthal-Lucas Numbers va Square Roots of Matrces Saadet Arslan
More informationThe L(2, 1)-Labeling on -Product of Graphs
Annals of Pure and Appled Mathematcs Vol 0, No, 05, 9-39 ISSN: 79-087X (P, 79-0888(onlne Publshed on 7 Aprl 05 wwwresearchmathscorg Annals of The L(, -Labelng on -Product of Graphs P Pradhan and Kamesh
More informationU.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017
U.C. Berkeley CS94: Beyond Worst-Case Analyss Handout 4s Luca Trevsan September 5, 07 Summary of Lecture 4 In whch we ntroduce semdefnte programmng and apply t to Max Cut. Semdefnte Programmng Recall that
More informationAmusing Properties of Odd Numbers Derived From Valuated Binary Tree
IOSR Journal of Mathematcs (IOSR-JM) e-iss: 78-578, p-iss: 19-765X. Volume 1, Issue 6 Ver. V (ov. - Dec.016), PP 5-57 www.osrjournals.org Amusng Propertes of Odd umbers Derved From Valuated Bnary Tree
More informationLinear Algebra and its Applications
Lnear Algebra and ts Applcatons 4 (00) 5 56 Contents lsts avalable at ScenceDrect Lnear Algebra and ts Applcatons journal homepage: wwwelsevercom/locate/laa Notes on Hlbert and Cauchy matrces Mroslav Fedler
More informationCase Study of Markov Chains Ray-Knight Compactification
Internatonal Journal of Contemporary Mathematcal Scences Vol. 9, 24, no. 6, 753-76 HIKAI Ltd, www.m-har.com http://dx.do.org/.2988/cms.24.46 Case Study of Marov Chans ay-knght Compactfcaton HaXa Du and
More informationMore metrics on cartesian products
More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of
More informationDifference Equations
Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1
More informationSTAT 309: MATHEMATICAL COMPUTATIONS I FALL 2018 LECTURE 16
STAT 39: MATHEMATICAL COMPUTATIONS I FALL 218 LECTURE 16 1 why teratve methods f we have a lnear system Ax = b where A s very, very large but s ether sparse or structured (eg, banded, Toepltz, banded plus
More informationNeutrosophic Bi-LA-Semigroup and Neutrosophic N-LA- Semigroup
Neutrosophc Sets Systems, Vol. 4, 04 9 Neutrosophc B-LA-Semgroup Neutrosophc N-LA- Semgroup Mumtaz Al *, Florentn Smarache, Muhammad Shabr 3 Munazza Naz 4,3 Department of Mathematcs, Quad--Azam Unversty,
More informationEvaluation of a family of binomial determinants
Electronc Journal of Lnear Algebra Volume 30 Volume 30 2015 Artcle 22 2015 Evaluaton of a famly of bnomal determnants Charles Helou Pennsylvana State Unversty, cxh22@psuedu James A Sellers Pennsylvana
More informationValuated Binary Tree: A New Approach in Study of Integers
Internatonal Journal of Scentfc Innovatve Mathematcal Research (IJSIMR) Volume 4, Issue 3, March 6, PP 63-67 ISS 347-37X (Prnt) & ISS 347-34 (Onlne) wwwarcournalsorg Valuated Bnary Tree: A ew Approach
More informationA Simple Research of Divisor Graphs
The 29th Workshop on Combnatoral Mathematcs and Computaton Theory A Smple Research o Dvsor Graphs Yu-png Tsao General Educaton Center Chna Unversty o Technology Tape Tawan yp-tsao@cuteedutw Tape Tawan
More informationON SEPARATING SETS OF WORDS IV
ON SEPARATING SETS OF WORDS IV V. FLAŠKA, T. KEPKA AND J. KORTELAINEN Abstract. Further propertes of transtve closures of specal replacement relatons n free monods are studed. 1. Introducton Ths artcle
More informationGELFAND-TSETLIN BASIS FOR THE REPRESENTATIONS OF gl n
GELFAND-TSETLIN BASIS FOR THE REPRESENTATIONS OF gl n KANG LU FINITE DIMENSIONAL REPRESENTATIONS OF gl n Let e j,, j =,, n denote the standard bass of the general lnear Le algebra gl n over the feld of
More informationDeterminants Containing Powers of Generalized Fibonacci Numbers
1 2 3 47 6 23 11 Journal of Integer Sequences, Vol 19 (2016), Artcle 1671 Determnants Contanng Powers of Generalzed Fbonacc Numbers Aram Tangboonduangjt and Thotsaporn Thanatpanonda Mahdol Unversty Internatonal
More informationCSCE 790S Background Results
CSCE 790S Background Results Stephen A. Fenner September 8, 011 Abstract These results are background to the course CSCE 790S/CSCE 790B, Quantum Computaton and Informaton (Sprng 007 and Fall 011). Each
More informationYong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 )
Kangweon-Kyungk Math. Jour. 4 1996), No. 1, pp. 7 16 AN ITERATIVE ROW-ACTION METHOD FOR MULTICOMMODITY TRANSPORTATION PROBLEMS Yong Joon Ryang Abstract. The optmzaton problems wth quadratc constrants often
More informationP.P. PROPERTIES OF GROUP RINGS. Libo Zan and Jianlong Chen
Internatonal Electronc Journal of Algebra Volume 3 2008 7-24 P.P. PROPERTIES OF GROUP RINGS Lbo Zan and Janlong Chen Receved: May 2007; Revsed: 24 October 2007 Communcated by John Clark Abstract. A rng
More informationHADAMARD PRODUCT VERSIONS OF THE CHEBYSHEV AND KANTOROVICH INEQUALITIES
HADAMARD PRODUCT VERSIONS OF THE CHEBYSHEV AND KANTOROVICH INEQUALITIES JAGJIT SINGH MATHARU AND JASPAL SINGH AUJLA Department of Mathematcs Natonal Insttute of Technology Jalandhar 144011, Punab, INDIA
More informationA p-adic PERRON-FROBENIUS THEOREM
A p-adic PERRON-FROBENIUS THEOREM ROBERT COSTA AND PATRICK DYNES Advsor: Clayton Petsche Oregon State Unversty Abstract We prove a result for square matrces over the p-adc numbers akn to the Perron-Frobenus
More informationThe Pseudoblocks of Endomorphism Algebras
Internatonal Mathematcal Forum, 4, 009, no. 48, 363-368 The Pseudoblocks of Endomorphsm Algebras Ahmed A. Khammash Department of Mathematcal Scences, Umm Al-Qura Unversty P.O.Box 796, Makkah, Saud Araba
More informationOn Graphs with Same Distance Distribution
Appled Mathematcs, 07, 8, 799-807 http://wwwscrporg/journal/am ISSN Onlne: 5-7393 ISSN Prnt: 5-7385 On Graphs wth Same Dstance Dstrbuton Xulang Qu, Xaofeng Guo,3 Chengy Unversty College, Jme Unversty,
More informationNorm Bounds for a Transformed Activity Level. Vector in Sraffian Systems: A Dual Exercise
ppled Mathematcal Scences, Vol. 4, 200, no. 60, 2955-296 Norm Bounds for a ransformed ctvty Level Vector n Sraffan Systems: Dual Exercse Nkolaos Rodousaks Department of Publc dmnstraton, Panteon Unversty
More informationU.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016
U.C. Berkeley CS94: Spectral Methods and Expanders Handout 8 Luca Trevsan February 7, 06 Lecture 8: Spectral Algorthms Wrap-up In whch we talk about even more generalzatons of Cheeger s nequaltes, and
More informationHongyi Miao, College of Science, Nanjing Forestry University, Nanjing ,China. (Received 20 June 2013, accepted 11 March 2014) I)ϕ (k)
ISSN 1749-3889 (prnt), 1749-3897 (onlne) Internatonal Journal of Nonlnear Scence Vol.17(2014) No.2,pp.188-192 Modfed Block Jacob-Davdson Method for Solvng Large Sparse Egenproblems Hongy Mao, College of
More informationarxiv: v1 [math.co] 12 Sep 2014
arxv:1409.3707v1 [math.co] 12 Sep 2014 On the bnomal sums of Horadam sequence Nazmye Ylmaz and Necat Taskara Department of Mathematcs, Scence Faculty, Selcuk Unversty, 42075, Campus, Konya, Turkey March
More informationComplete subgraphs in multipartite graphs
Complete subgraphs n multpartte graphs FLORIAN PFENDER Unverstät Rostock, Insttut für Mathematk D-18057 Rostock, Germany Floran.Pfender@un-rostock.de Abstract Turán s Theorem states that every graph G
More informationProjective change between two Special (α, β)- Finsler Metrics
Internatonal Journal of Trend n Research and Development, Volume 2(6), ISSN 2394-9333 www.jtrd.com Projectve change between two Specal (, β)- Fnsler Metrcs Gayathr.K 1 and Narasmhamurthy.S.K 2 1 Assstant
More informationAffine transformations and convexity
Affne transformatons and convexty The purpose of ths document s to prove some basc propertes of affne transformatons nvolvng convex sets. Here are a few onlne references for background nformaton: http://math.ucr.edu/
More informationA FORMULA FOR COMPUTING INTEGER POWERS FOR ONE TYPE OF TRIDIAGONAL MATRIX
Hacettepe Journal of Mathematcs and Statstcs Volume 393 0 35 33 FORMUL FOR COMPUTING INTEGER POWERS FOR ONE TYPE OF TRIDIGONL MTRIX H Kıyak I Gürses F Yılmaz and D Bozkurt Receved :08 :009 : ccepted 5
More informationUniqueness of Weak Solutions to the 3D Ginzburg- Landau Model for Superconductivity
Int. Journal of Math. Analyss, Vol. 6, 212, no. 22, 195-114 Unqueness of Weak Solutons to the 3D Gnzburg- Landau Model for Superconductvty Jshan Fan Department of Appled Mathematcs Nanjng Forestry Unversty
More informationON THE JACOBIAN CONJECTURE
v v v Far East Journal of Mathematcal Scences (FJMS) 17 Pushpa Publshng House, Allahabad, Inda http://www.pphm.com http://dx.do.org/1.17654/ms1111565 Volume 11, Number 11, 17, Pages 565-574 ISSN: 97-871
More informationFinding Dense Subgraphs in G(n, 1/2)
Fndng Dense Subgraphs n Gn, 1/ Atsh Das Sarma 1, Amt Deshpande, and Rav Kannan 1 Georga Insttute of Technology,atsh@cc.gatech.edu Mcrosoft Research-Bangalore,amtdesh,annan@mcrosoft.com Abstract. Fndng
More informationBOUNDEDNESS OF THE RIESZ TRANSFORM WITH MATRIX A 2 WEIGHTS
BOUNDEDNESS OF THE IESZ TANSFOM WITH MATIX A WEIGHTS Introducton Let L = L ( n, be the functon space wth norm (ˆ f L = f(x C dx d < For a d d matrx valued functon W : wth W (x postve sem-defnte for all
More informationPower law and dimension of the maximum value for belief distribution with the max Deng entropy
Power law and dmenson of the maxmum value for belef dstrbuton wth the max Deng entropy Bngy Kang a, a College of Informaton Engneerng, Northwest A&F Unversty, Yanglng, Shaanx, 712100, Chna. Abstract Deng
More informationLecture 20: Lift and Project, SDP Duality. Today we will study the Lift and Project method. Then we will prove the SDP duality theorem.
prnceton u. sp 02 cos 598B: algorthms and complexty Lecture 20: Lft and Project, SDP Dualty Lecturer: Sanjeev Arora Scrbe:Yury Makarychev Today we wll study the Lft and Project method. Then we wll prove
More informationA Hybrid Variational Iteration Method for Blasius Equation
Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method
More informationMEM 255 Introduction to Control Systems Review: Basics of Linear Algebra
MEM 255 Introducton to Control Systems Revew: Bascs of Lnear Algebra Harry G. Kwatny Department of Mechancal Engneerng & Mechancs Drexel Unversty Outlne Vectors Matrces MATLAB Advanced Topcs Vectors A
More informationn-strongly Ding Projective, Injective and Flat Modules
Internatonal Mathematcal Forum, Vol. 7, 2012, no. 42, 2093-2098 n-strongly Dng Projectve, Injectve and Flat Modules Janmn Xng College o Mathematc and Physcs Qngdao Unversty o Scence and Technology Qngdao
More informationLinear Algebra and its Applications
Lnear Algebra and ts Applcatons 436 (2012) 4193 4222 Contents lsts avalable at ScVerse ScenceDrect Lnear Algebra and ts Applcatons ournal homepage: www.elsever.com/locate/laa Normalzed graph Laplacans
More informationA new Approach for Solving Linear Ordinary Differential Equations
, ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of
More informationInexact Newton Methods for Inverse Eigenvalue Problems
Inexact Newton Methods for Inverse Egenvalue Problems Zheng-jan Ba Abstract In ths paper, we survey some of the latest development n usng nexact Newton-lke methods for solvng nverse egenvalue problems.
More informationLinear convergence of an algorithm for computing the largest eigenvalue of a nonnegative tensor
NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS Numer Lnear Algebra Al 22; 9:83 84 Publshed onlne 8 October 2 n Wley Onlne Lbrary (wleyonlnelbrarycom) OI: 2/nla822 Lnear convergence of an algorthm for comutng
More informationMath 217 Fall 2013 Homework 2 Solutions
Math 17 Fall 013 Homework Solutons Due Thursday Sept. 6, 013 5pm Ths homework conssts of 6 problems of 5 ponts each. The total s 30. You need to fully justfy your answer prove that your functon ndeed has
More informationRoot Structure of a Special Generalized Kac- Moody Algebra
Mathematcal Computaton September 04, Volume, Issue, PP8-88 Root Structu of a Specal Generalzed Kac- Moody Algebra Xnfang Song, #, Xaox Wang Bass Department, Bejng Informaton Technology College, Bejng,
More informationON A DIOPHANTINE EQUATION ON TRIANGULAR NUMBERS
Mskolc Mathematcal Notes HU e-issn 787-43 Vol. 8 (7), No., pp. 779 786 DOI:.854/MMN.7.536 ON A DIOPHANTINE EUATION ON TRIANGULAR NUMBERS ABDELKADER HAMTAT AND DJILALI BEHLOUL Receved 6 February, 5 Abstract.
More informationErbakan University, Konya, Turkey. b Department of Mathematics, Akdeniz University, Antalya, Turkey. Published online: 28 Nov 2013.
Ths artcle was downloaded by: [Necmettn Erbaan Unversty] On: 24 March 2015, At: 05:44 Publsher: Taylor & Francs Informa Ltd Regstered n England and Wales Regstered Number: 1072954 Regstered offce: Mortmer
More informationU.C. Berkeley CS278: Computational Complexity Professor Luca Trevisan 2/21/2008. Notes for Lecture 8
U.C. Berkeley CS278: Computatonal Complexty Handout N8 Professor Luca Trevsan 2/21/2008 Notes for Lecture 8 1 Undrected Connectvty In the undrected s t connectvty problem (abbrevated ST-UCONN) we are gven
More informationY. Guo. A. Liu, T. Liu, Q. Ma UDC
UDC 517. 9 OSCILLATION OF A CLASS OF NONLINEAR PARTIAL DIFFERENCE EQUATIONS WITH CONTINUOUS VARIABLES* ОСЦИЛЯЦIЯ КЛАСУ НЕЛIНIЙНИХ ЧАСТКОВО РIЗНИЦЕВИХ РIВНЯНЬ З НЕПЕРЕРВНИМИ ЗМIННИМИ Y. Guo Graduate School
More informationA Note on \Modules, Comodules, and Cotensor Products over Frobenius Algebras"
Chn. Ann. Math. 27B(4), 2006, 419{424 DOI: 10.1007/s11401-005-0025-z Chnese Annals of Mathematcs, Seres B c The Edtoral Oce of CAM and Sprnger-Verlag Berln Hedelberg 2006 A Note on \Modules, Comodules,
More informationAli Omer Alattass Department of Mathematics, Faculty of Science, Hadramout University of science and Technology, P. O. Box 50663, Mukalla, Yemen
Journal of athematcs and Statstcs 7 (): 4448, 0 ISSN 5493644 00 Scence Publcatons odules n σ[] wth Chan Condtons on Small Submodules Al Omer Alattass Department of athematcs, Faculty of Scence, Hadramout
More informationBallot Paths Avoiding Depth Zero Patterns
Ballot Paths Avodng Depth Zero Patterns Henrch Nederhausen and Shaun Sullvan Florda Atlantc Unversty, Boca Raton, Florda nederha@fauedu, ssull21@fauedu 1 Introducton In a paper by Sapounaks, Tasoulas,
More informationDynamic Systems on Graphs
Prepared by F.L. Lews Updated: Saturday, February 06, 200 Dynamc Systems on Graphs Control Graphs and Consensus A network s a set of nodes that collaborates to acheve what each cannot acheve alone. A network,
More informatione - c o m p a n i o n
OPERATIONS RESEARCH http://dxdoorg/0287/opre007ec e - c o m p a n o n ONLY AVAILABLE IN ELECTRONIC FORM 202 INFORMS Electronc Companon Generalzed Quantty Competton for Multple Products and Loss of Effcency
More informationNon-negative Matrices and Distributed Control
Non-negatve Matrces an Dstrbute Control Yln Mo July 2, 2015 We moel a network compose of m agents as a graph G = {V, E}. V = {1, 2,..., m} s the set of vertces representng the agents. E V V s the set of
More informationDiscrete Mathematics
Dscrete Mathematcs 30 (00) 48 488 Contents lsts avalable at ScenceDrect Dscrete Mathematcs journal homepage: www.elsever.com/locate/dsc The number of C 3 -free vertces on 3-partte tournaments Ana Paulna
More information