Research Article An Extension of Stolarsky Means to the Multivariable Case

Size: px
Start display at page:

Download "Research Article An Extension of Stolarsky Means to the Multivariable Case"

Transcription

1 Internatonal Mathematcs and Mathematcal Scences Volume 009, Artcle ID 43857, 14 pages do: /009/43857 Research Artcle An Extenson of Stolarsky Means to the Multvarable Case Slavko Smc Mathematcal Insttute SANU, Kneza Mhala 36, Belgrade, Serba Correspondence should be addressed to Slavko Smc, Receved 10 July 009; Accepted 3 September 009 Recommended by Feng Q We gve an extenson of well-known Stolarsky means to the multvarable case n a smple and applcable way. Some basc nequaltes concernng ths matter are also establshed wth applcatons n Analyss and Probablty Theory. Copyrght q 009 Slavko Smc. Ths s an open access artcle dstrbuted under the Creatve Commons Attrbuton Lcense, whch permts unrestrcted use, dstrbuton, and reproducton n any medum, provded the orgnal work s properly cted. 1. Introducton There s a huge amount of papers nvestgatng propertes of the so-called Stolarsky or extended two-parametrc mean value, defned for postve values of x, y, as ) r x s y s) ) 1/ s r E r,s x, y : s x r y r), 1.1 rs r s x y ) / 0. E means can be contnuously extended on the doman { r, s; x, y ) r, s R; x, y R } 1.

2 Internatonal Mathematcs and Mathematcal Scences by the followng: r x s y s) ) 1/ s r rs r s / 0; ) E r,s x, y s x r y r) exp 1 s xs log x y s log y x s y s x s y s s log x log y ) ), r s / 0; ) 1/s, s/ 0, r 0; 1.3 xy, r s 0; x, y x>0, and n ths form are ntroduced by Keneth Stolarsky n 1. Most of the classcal two-varable means are specal cases of the class E. For example, E 1, x y / s the arthmetc mean, E 0,0 xy s the geometrc mean, E 0,1 x y / log x log y s the logarthmc mean, E 1,1 x x /y y 1/ x y /e s the dentrc mean, and so forth. More generally, the rth power mean x r y r / 1/r s equal to E r,r. Recently, several papers are produced tryng to defne an extenson of the class E to n, n > varables. Unfortunately, ths s done n a hghly artfcal mode cf. 4, wthout a practcal background. Here s an llustraton of ths pont; recently Merkowsk 4 has proposed the followng generalzaton of the Stolarsky mean E r,s to several varables: E r,s X : [ L X s ] 1/ s r L X r, r/ s, 1.4 where X x 1,...,x n s an n-tuple of postve numbers and L X s : n 1! E n 1 n x su 1 du 1 du n The symbol E n 1 stands for the Eucldean smplex whch s defned by E n 1 : { u 1,...,u n 1 : u 0, 1 n 1; u 1 u n 1 1}. 1.6 In ths paper, we gve another attempt to generalze Stolarsky means to the multvarable case n a smple and applcable way. The proposed task can be accomplshed by foundng a weghted varant of the class E, wherefrom the mentoned generalzaton follows naturally. In the sequel, we wll need notons of the weghted geometrc mean G G p, q; x, y and weghted rth power mean S r S r p, q; x, y, defned by G : x p y q ; S r : px r qy r) 1/r, 1.7

3 Internatonal Mathematcs and Mathematcal Scences 3 where p, q, x, y R ; p q 1; r R/{0}. 1.8 Note that S r r > G r for x / y, r / 0, and lm r 0 S r G Weghted Stolarsky Means We ntroduce here a class W of weghted two-parameters means whch ncludes the Stolarsky class E as a partcular case. Namely, for p, q, x, y R,p q 1,rs r s x y / 0, we defne ) ) r S s s G s 1/ s r ) r px s qy s x ps y qs 1/ s r W W r,s p, q; x, y : s S r r G r s px r qy r x pr y qr. 1.9 Varous propertes concernng the means W can be establshed; some of them are the followng: W r,s ) Ws,r ) ; W r,s ) Wr,s q, p; y, x ) ; Wr,s p, q; y, x ) xywr,s p, q; x 1,y 1) ; 1.10 W ar,as ) Wr,s p, q; x a,y a)) 1/a, a / 0. Note that 1 W r,s, 1 ) r ) ; x, y x s y s s )1/ s r xy s x r y r ) r xy r x s y s) ) 1/ s r xr y r) E r, s; x, y ). s 1.11 In the same manner, we get W r,s 3, 1 ) x 3 ; x3,y 3 s y s ) 1/ s r )) ; E r, s; x, y x r y r 3 W r,s 4, 1 ) 3x s 4 ; x4,y 4 xy ) s ) y s 1/ s r E 1.1 3x r xy ) )). r r, s; x, y y r The weghted means from the class W can be extended contnuously to the doman D { r, s; x, y ) r, s R; x, y R }. 1.13

4 4 Internatonal Mathematcs and Mathematcal Scences Ths extenson s gven by W r,s ) r s px s qy s x ps y qs px r qy r x pr y qr ) 1/ s r, rs r s x y ) / 0; ) pxs qy s x ps y qs 1/s pqs log x/y ), s x y ) / 0, r 0; ) ) exp s pxs log x qy s log y p log x q log y x ps y qs px s qy s x ps y qs, s x y ) / 0, r s; x p 1 /3 y q 1 /3, x/ y, r s 0; x, x y Note that those means are homogeneous of order 1, that s, W r,s p, q; tx, ty tw r,s p, q; x, y, t>0, symmetrc n r, s, W r,s p, q; x, y W s,r p, q; x, y but are not symmetrc n x, y unless p q 1/. 1.. Multvarable Case A natural generalzaton of weghted Stolarsky means to the multvarable case gves r p x s x p s p x r x p ) s ) ) r ) 1/ s r, rs s r / 0; ) p x s p s 1/s x s p log x ), r 0, s/ 0; p log x W r,s p; x exp p x s s log x ) ) p s p log x x ) p x s p s, r s / 0; x p log 3 x ) 3 p log x exp 3 p log x ) ), r s 0, p log x 1.15 where x x 1,x,...,x n R n, n, p s an arbtrary postve weght sequence assocated wth x and W r,s p; x 0 afor x 0 a,a,...,a. We also wrte, nstead of n 1, n 1.

5 Internatonal Mathematcs and Mathematcal Scences 5 The above formulae are obtaned by an approprate lmt process, mplyng contnuty. For example, applyng t s 1 s log t s log t s3 6 log3 t o s 3) s 0, 1.16 we get ) W 0,0 p; x lm W s,0 p; x lm p x s p s x s 0 s 0 s p log x ) p log x lm s 0 s p log x ) ) p log x p s ) ) ) s s p log x p log 3 x p log 3 x 6 ) ) p p s log x s log ) p x ) s 3 log 3 ) ) p x o s 3)) 6 1/s 1/s p log 3 x ) 3 p log x lm 1 s 0 3 p log x ) )s 1 o 1 p log x p log 3 x ) 3 p log x exp 3 p log x ) ). p log x 1/s 1.17 Remark 1.1. Analogously to the former consderatons, one can defne a class of Stolarsky means n n varables E r,s x; n as E r,s x; n : W nr,ns p 0, x, 1.18 where p 0 {1/n} n 1.

6 6 Internatonal Mathematcs and Mathematcal Scences Therefore, E r,s x; n r n 1 xns s n 1 xnr n n 1 xs n n 1 xr ) 1/n s r, rs r s / Detals are left to the readers.. Results The followng basc asserton s of mportance. Proposton.1. The expressons W r,s p; x are actual means, that s, for arbtrary weght sequence p one has mn{x 1,x...,x n } W r,s p; x max{x 1,x,...,x n }..1 Our man result s contaned n the followng. Proposton.. The means W r,s p, x are monotone ncreasng n both varables r and s. Passng to the contnuous varable case, we get the followng defnton of the class W r,s p, x. Assumng that all ntegrals exst, W r,s p, x r p t x s t dt exp s p t log x t dt )) ) 1/ s r s p t x r t dt exp r p t log x t dt )), rs s r / 0; p t x s t dt exp s p t log x t dt ) ) 1/s s p t log x t dt p t log x t dt ), r 0, s/ 0; p t x s exp s t log x t dt p t log x t dt ) exp s p t log x t dt ) ), p t xs t dt exp s p t log x t dt ) p t log 3 x t dt p t log x t dt ) 3 exp 3 p t log x t dt p t log x t dt ) ), r s 0, r s / 0;. where x t s a postve ntegrable functon and p t s a nonnegatve functon wth p t dt 1.

7 Internatonal Mathematcs and Mathematcal Scences 7 From our former consderatons, a very applcable asserton follows. Proposton.3. W r,s p, x s monotone ncreasng n ether r or s. 3. Applcatons 3.1. Applcatons n Analyss As an llustraton of the above, we gve the followng proposton. Proposton 3.1. The functon w s, defned by ) 1/s 1 πs Γ 1 s e γs, s/ 0; w s : exp γ 4ξ 3 ), s 0, π 3.1 s monotone ncreasng for s 1,. In partcular, for s 1, 1, one has Γ 1 s e γs Γ 1 s e γs πs sn πs 1 πs 4 144, 3. where Γ,ξ,γ stands for the Gamma functon, Zeta functon, and Euler s constant, respectvely. 3.. Applcatons n Probablty Theory For a random varable X and an arbtrary probablty dstrbuton wth support on,, t s well known that Ee X e EX. 3.3 Denotng the central moment of order k by μ k μ k X : E X EX k, we mprove ths nequalty to the followng propsostons. Proposton 3.. For an arbtrary probablty law wth support on R, one has Ee X 1 μ ) )) μ3 exp e EX. 3μ 3.4

8 8 Internatonal Mathematcs and Mathematcal Scences Proposton 3.3. One also has that Ee sx e sex ) 1/s 3.5 s σ X / s monotone ncreasng n s Shfted Stolarsky Means Especally nterestng s studyng the shfted Stolarsky means E, defned by E r,s x, y ) : lm p 0 W r,s p, q; x, y ). 3.6 Ther analytc contnuaton to the whole r, s plane s gven by r x s y s 1 s log x/y ))) ) 1/ s r s x r y r 1 r log x/y ))), rs r s x y ) / 0; ))) x s y s 1/s 1 s log x/y Er,s ) s log x/y ), s x y ) / 0, r 0; x, y x s exp s y s) log x sy s log y log x/y ) ) x s y s 1 s log x/y )), s x y ) / 0, r s; x 1/3 y /3, r s 0; x, x y. 3.7 Man results concernng the means E are contaned n the followng propostons. Proposton 3.4. Means E r,s x, y are monotone ncreasng n ether r or s for each fxed x, y R. Proposton 3.5. Means E r,s x, y are monotone ncreasng n ether x or y for each r, s R. A well known result of Q 5 states that the means E r,s x, y are logarthmcally concave for each fxed x, y > 0andr, s 0, ; also, they are logarthmcally convex for r, s, 0. Accordng to ths, we propose the followng proposton. Open Queston Is there any compact nterval I,I R such that the means E r,s x, y are logarthmcally convex concave for r, s I and each x, y R?

9 Internatonal Mathematcs and Mathematcal Scences 9 A partal answer to ths problem s gven n what follows. Proposton 3.6. On any nterval I whch ncludes zero and r, s I, ) E r,s x, y are not logarthmcally convex concave); ) W r,s p, q; x, y are logarthmcally convex concave) f and only f p q 1/. 4. Proofs For the proof of Proposton.1, we apply the followng asserton on Jensen functonals J f p, x from 6. Theorem 4.1. Let f, g : I R be twce contnuously dfferentable functons. Assume that g s strctly convex and φ s a contnuous and strctly monotonc functon on I. Then the expresson )) Jn p, x; f φ 1 ) J n p, x; g n 4.1 represents a mean value of the numbers x 1,...,x n, that s, )) Jn p, x; f mn{x 1,...,x n } φ 1 ) max{x 1,...,x n } J n p, x; g 4. f and only f the relaton f t φ t g t 4.3 holds for each t I. Recall that the Jensen functonal J n p, x; f s defned on an nterval I,I R by ) n n J n p, x; f : p f x f p x ), where f : I R, x x 1,x,...,x n I n, and p {p } n 1 s a postve weght sequence. The famous Jensen s nequalty asserts that J n p, x; f ) 0, 4.5 whenever f s a strctly convex functon on I, wth the equalty case f and only f x 1 x x n.

10 10 Internatonal Mathematcs and Mathematcal Scences Proof of Proposton.1. Defne the auxlary functon h s x by h s x : e sx sx 1 s, s/ 0; x, s Snce e sx 1, s/ 0; h s x s x, s 0, 4.7 h s x e sx, s R, we conclude that h s x s a contnuously twce dfferentable convex functon on R. Denotng f t : h s t, g t : h r t, we realze that the condton 4.3 of Theorem 4.1 s fulflled wth φ t e s r t. Hence, applyng Theorem 4.1, we obtan that log W r,s p,e x represents a mean value, whch s equvalent to the asserton of Proposton.1. Proof of Proposton.. We prove frst a global theorem concernng log-convexty of the Jensen s functonal wth a parameter, whch can be very usable cf. 7. Theorem 4.. Let f s x be a twce contnuously dfferentable functon n x wth a parameter s. If f s x s log-convex n s for s I : a, b ; x K : c, d, then the Jensen functonal J f w, x; s J s : w f s x f s w x ), 4.8 s log-convex n s for s I, x K, 1,,...,wherew {w } s any postve weght sequence. At the begnnng, we need some prelmnary lemmas. Lemma 4.3. A postve functon f s log-convex on I f and only f the relaton ) s t f s u f uw f t w holds for each real u, w and s, t I. Ths asserton s nothng more than the dscrmnant test for the nonnegatvty of second-order polynomals. Other well known assertons are the followng cf 8, pages 74, lemmas.

11 Internatonal Mathematcs and Mathematcal Scences 11 Lemma 4.4 Jensen s nequalty. If g x s twce contnuously dfferentable and g x 0 on K, then g x s convex on K and the nequalty ) w g x g w x holds for each x K, 1,,...,and any postve weght sequence {w }, w 1. Lemma 4.5. For a convex f, the expresson f s f r s r 4.11 s ncreasng n both varables. Proof of Theorem 4.. Consder the functon F x defned as F x F u, v, s, t; x : u f s x uvf s t / x v f t x, 4.1 where u, v R; s, t I are real parameters ndependent of the varable x K. Snce F x u f s x uvf s t / x v f t x, 4.13 and by assumng f s x s log-convex n s, t follows from Lemma 4.3 that F x 0, x K. Therefore, by Lemma 4.4, weget ) w F x F w x 0, x K, 4.14 whch s equvalent to ) s t u J s uvj v J t Accordng to Lemma 4.3 agan, ths s possble only f J s s log-convex and the proof s done. Now, the proof of Proposton. easly follows. From the above, we see that h s x s twce contnuously dfferentable and that h s x s a log-convex functon for each real s, x.

12 1 Internatonal Mathematcs and Mathematcal Scences Applyng Theorem 4., we conclude that the form w e sx e s w x, s/ 0, s Φ h w, x; s Φ s : w x w x, s 0, 4.16 s log-convex n s. By Lemma 4.5,wthf s log Φ s, we fnd out that log Φ s log Φ r s r log ) Φ s 1/ s r 4.17 Φ r s monotone ncreasng ether n s or r. Therefore, by changng varable x log x, we fnally obtan the proof of Proposton.. Proof of Proposton.3. The asserton of Proposton.3 follows from Proposton. by the standard argument cf. 8, pages Detals are left to the reader. Proof of Proposton 3.1. The proof follows puttng x t t, p t e t,t 0, and applyng Proposton..wthr 0. Correspondng ntegrals are 0 e t log t γ; 0 e t log t γ π 6 ; 0 e t log 3 t γ 3 γπ ξ 3, 4.18 wth Γ 1 s Γ 1 s πs sn πs Proof of Proposton 3.. By Proposton.3, weget W 0,1 p,e x W 0,0 p,e x, 4.0 that s, Ee X e EX μ / ) EX 3 EX 3 exp μ Usng the dentty EX 3 EX 3 μ 3 3μ EX, we obtan the proof of Proposton 3.. Proof of Proposton 3.3. Ths asserton s straghtforward consequence of the fact that W 0,s p,e x s monotone ncreasng n s.

13 Internatonal Mathematcs and Mathematcal Scences 13 Proof of Proposton 3.4. Drect consequence of Proposton.. Proof of Proposton 3.5. Ths s left as an easy exercse to the readers. Proof of Proposton 3.6. We prove only part. The proof of goes along the same lnes. Suppose that 0 a, b : I and that E r,s p, q; x, y are log-convex concave for r, s I and any fxed x, y R. Then there should be an s, s > 0 such that F s ) : W0,s ) W0, s ) W0,0 )) 4. s of constant sgn for each x, y > 0. Substtutng x/y s : e w,w R, after some calculatons, we get that the above s equvalent to the asserton that F p, q; w s of constant sgn, where F p, q; w ) : pe w q e pw e /3 1 p w pe w q e pw). 4.3 Developng n power seres n w,weget F p, q; w ) pq 1 p ) p ) 1 p ) w 5 O w 6). 4.4 Therefore, F p, q; w can be of constant sgn for each w R only f p 1/ q. Suppose now that I s of the form I : 0,a or I : a, 0,a>0. Then there should be an s, s / 0,s I such that W 0,0 ) W0,s ) W0,s )) 4.5 s of constant sgn for each x, y R. Proceedng as before, ths s equvalent to the asserton that G p, q; w s of constant sgn wth G p, q; w ) : p 3 q 3 w 6 e /3 p 1 w pe w q e pw) pe w q e pw) However, G p, q; w ) 405 p4 q 4 1 p ) 1 q ) q p ) w 11 O w 1). 4.7 Hence, we conclude that G p, q; w can be of constant sgn for suffcently small w, w R only f p q 1/. Combnng ths wth Feng Q theorem, the asserton from Proposton 3.6 follows.

14 14 Internatonal Mathematcs and Mathematcal Scences References 1 K. B. Stolarsky, Generalzatons of the logarthmc mean, Mathematcs Magazne, vol. 48, no., pp. 87 9, E. B. Leach and M. C. Sholander, Multvarable extended mean values, Mathematcal Analyss and Applcatons, vol. 104, no., pp , Z. Páles, Inequaltes for dfferences of powers, Mathematcal Analyss and Applcatons, vol. 131, no. 1, pp , J. K. Merkowsk, Extendng means of two varables to several varables, Inequaltes n Pure and Appled Mathematcs, vol. 5, no. 3, artcle 65, pp. 1 9, F. Q, Logarthmc convexty of extended mean values, Proceedngs of the Amercan Mathematcal Socety, vol. 130, no. 6, pp , S. Smc, Means nvolvng Jensen functonals, submtted to Internatonal Mathematcs and Mathematcal Scences. 7 S. Smc, On logarthmc convexty for dfferences of power means, Inequaltes and Applcatons, vol. 007, Artcle ID , 8 pages, G. H. Hardy, J. E. Lttlewood, and G. Pólya, Inequaltes, Cambrdge Unversty Press, Cambrdge, UK, 1978.

15 Advances n Operatons Research Volume 014 Advances n Decson Scences Volume 014 Appled Mathematcs Algebra Volume 014 Probablty and Statstcs Volume 014 The Scentfc World Journal Volume 014 Internatonal Dfferental Equatons Volume 014 Volume 014 Submt your manuscrpts at Internatonal Advances n Combnatorcs Mathematcal Physcs Volume 014 Complex Analyss Volume 014 Internatonal Mathematcs and Mathematcal Scences Mathematcal Problems n Engneerng Mathematcs Volume 014 Volume 014 Volume 014 Volume 014 Dscrete Mathematcs Volume 014 Dscrete Dynamcs n Nature and Socety Functon Spaces Abstract and Appled Analyss Volume 014 Volume 014 Volume 014 Internatonal Stochastc Analyss Optmzaton Volume 014 Volume 014

Another converse of Jensen s inequality

Another converse of Jensen s inequality Another converse of Jensen s nequalty Slavko Smc Abstract. We gve the best possble global bounds for a form of dscrete Jensen s nequalty. By some examples ts frutfulness s shown. 1. Introducton Throughout

More information

The Order Relation and Trace Inequalities for. Hermitian Operators

The 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 information

Research Article Green s Theorem for Sign Data

Research Article Green s Theorem for Sign Data Internatonal Scholarly Research Network ISRN Appled Mathematcs Volume 2012, Artcle ID 539359, 10 pages do:10.5402/2012/539359 Research Artcle Green s Theorem for Sgn Data Lous M. Houston The Unversty of

More information

More metrics on cartesian products

More 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 information

Research Article Relative Smooth Topological Spaces

Research Article Relative Smooth Topological Spaces Advances n Fuzzy Systems Volume 2009, Artcle ID 172917, 5 pages do:10.1155/2009/172917 Research Artcle Relatve Smooth Topologcal Spaces B. Ghazanfar Department of Mathematcs, Faculty of Scence, Lorestan

More information

Case Study of Markov Chains Ray-Knight Compactification

Case 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 information

Curvature and isoperimetric inequality

Curvature and isoperimetric inequality urvature and sopermetrc nequalty Julà ufí, Agustí Reventós, arlos J Rodríguez Abstract We prove an nequalty nvolvng the length of a plane curve and the ntegral of ts radus of curvature, that has as a consequence

More information

The Jacobsthal and Jacobsthal-Lucas Numbers via Square Roots of Matrices

The 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 information

Sharp integral inequalities involving high-order partial derivatives. Journal Of Inequalities And Applications, 2008, v. 2008, article no.

Sharp integral inequalities involving high-order partial derivatives. Journal Of Inequalities And Applications, 2008, v. 2008, article no. Ttle Sharp ntegral nequaltes nvolvng hgh-order partal dervatves Authors Zhao, CJ; Cheung, WS Ctaton Journal Of Inequaltes And Applcatons, 008, v. 008, artcle no. 5747 Issued Date 008 URL http://hdl.handle.net/07/569

More information

Research Article Global Sufficient Optimality Conditions for a Special Cubic Minimization Problem

Research Article Global Sufficient Optimality Conditions for a Special Cubic Minimization Problem Mathematcal Problems n Engneerng Volume 2012, Artcle ID 871741, 16 pages do:10.1155/2012/871741 Research Artcle Global Suffcent Optmalty Condtons for a Specal Cubc Mnmzaton Problem Xaome Zhang, 1 Yanjun

More information

Some basic inequalities. Definition. Let V be a vector space over the complex numbers. An inner product is given by a function, V V C

Some basic inequalities. Definition. Let V be a vector space over the complex numbers. An inner product is given by a function, V V C Some basc nequaltes Defnton. Let V be a vector space over the complex numbers. An nner product s gven by a functon, V V C (x, y) x, y satsfyng the followng propertes (for all x V, y V and c C) (1) x +

More information

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification E395 - Pattern Recognton Solutons to Introducton to Pattern Recognton, Chapter : Bayesan pattern classfcaton Preface Ths document s a soluton manual for selected exercses from Introducton to Pattern Recognton

More information

Convexity preserving interpolation by splines of arbitrary degree

Convexity 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 information

A note on almost sure behavior of randomly weighted sums of φ-mixing random variables with φ-mixing weights

A note on almost sure behavior of randomly weighted sums of φ-mixing random variables with φ-mixing weights ACTA ET COMMENTATIONES UNIVERSITATIS TARTUENSIS DE MATHEMATICA Volume 7, Number 2, December 203 Avalable onlne at http://acutm.math.ut.ee A note on almost sure behavor of randomly weghted sums of φ-mxng

More information

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation Nonl. Analyss and Dfferental Equatons, ol., 4, no., 5 - HIKARI Ltd, www.m-har.com http://dx.do.org/.988/nade.4.456 Asymptotcs of the Soluton of a Boundary alue Problem for One-Characterstc Dfferental Equaton

More information

Affine transformations and convexity

Affine 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 information

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

More information

Appendix B. Criterion of Riemann-Stieltjes Integrability

Appendix B. Criterion of Riemann-Stieltjes Integrability Appendx B. Crteron of Remann-Steltes Integrablty Ths note s complementary to [R, Ch. 6] and [T, Sec. 3.5]. The man result of ths note s Theorem B.3, whch provdes the necessary and suffcent condtons for

More information

On the spectral norm of r-circulant matrices with the Pell and Pell-Lucas numbers

On 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 information

Randić Energy and Randić Estrada Index of a Graph

Randić 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 information

Linear, affine, and convex sets and hulls In the sequel, unless otherwise specified, X will denote a real vector space.

Linear, affine, and convex sets and hulls In the sequel, unless otherwise specified, X will denote a real vector space. Lnear, affne, and convex sets and hulls In the sequel, unless otherwse specfed, X wll denote a real vector space. Lnes and segments. Gven two ponts x, y X, we defne xy = {x + t(y x) : t R} = {(1 t)x +

More information

Research Article A Generalized Sum-Difference Inequality and Applications to Partial Difference Equations

Research Article A Generalized Sum-Difference Inequality and Applications to Partial Difference Equations Hndaw Publshng Corporaton Advances n Dfference Equatons Volume 008, Artcle ID 695495, pages do:0.55/008/695495 Research Artcle A Generalzed Sum-Dfference Inequalty and Applcatons to Partal Dfference Equatons

More information

Voting Games with Positive Weights and. Dummy Players: Facts and Theory

Voting Games with Positive Weights and. Dummy Players: Facts and Theory Appled Mathematcal Scences, Vol 10, 2016, no 53, 2637-2646 HIKARI Ltd, wwwm-hkarcom http://dxdoorg/1012988/ams201667209 Votng Games wth Postve Weghts and Dummy Players: Facts and Theory Zdravko Dmtrov

More information

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method Appled Mathematcal Scences, Vol. 7, 0, no. 47, 07-0 HIARI Ltd, www.m-hkar.com Comparson of the Populaton Varance Estmators of -Parameter Exponental Dstrbuton Based on Multple Crtera Decson Makng Method

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

Perron Vectors of an Irreducible Nonnegative Interval Matrix

Perron 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 information

A Note on Bound for Jensen-Shannon Divergence by Jeffreys

A Note on Bound for Jensen-Shannon Divergence by Jeffreys OPEN ACCESS Conference Proceedngs Paper Entropy www.scforum.net/conference/ecea- A Note on Bound for Jensen-Shannon Dvergence by Jeffreys Takuya Yamano, * Department of Mathematcs and Physcs, Faculty of

More information

The internal structure of natural numbers and one method for the definition of large prime numbers

The internal structure of natural numbers and one method for the definition of large prime numbers The nternal structure of natural numbers and one method for the defnton of large prme numbers Emmanul Manousos APM Insttute for the Advancement of Physcs and Mathematcs 3 Poulou str. 53 Athens Greece Abstract

More information

Using T.O.M to Estimate Parameter of distributions that have not Single Exponential Family

Using T.O.M to Estimate Parameter of distributions that have not Single Exponential Family IOSR Journal of Mathematcs IOSR-JM) ISSN: 2278-5728. Volume 3, Issue 3 Sep-Oct. 202), PP 44-48 www.osrjournals.org Usng T.O.M to Estmate Parameter of dstrbutons that have not Sngle Exponental Famly Jubran

More information

International Journal of Algebra, Vol. 8, 2014, no. 5, HIKARI Ltd,

International Journal of Algebra, Vol. 8, 2014, no. 5, HIKARI Ltd, Internatonal Journal of Algebra, Vol. 8, 2014, no. 5, 229-238 HIKARI Ltd, www.m-hkar.com http://dx.do.org/10.12988/ja.2014.4212 On P-Duo odules Inaam ohammed Al Had Department of athematcs College of Educaton

More information

Exercise Solutions to Real Analysis

Exercise Solutions to Real Analysis xercse Solutons to Real Analyss Note: References refer to H. L. Royden, Real Analyss xersze 1. Gven any set A any ɛ > 0, there s an open set O such that A O m O m A + ɛ. Soluton 1. If m A =, then there

More information

Monotonic Interpolating Curves by Using Rational. Cubic Ball Interpolation

Monotonic Interpolating Curves by Using Rational. Cubic Ball Interpolation Appled Mathematcal Scences, vol. 8, 204, no. 46, 7259 7276 HIKARI Ltd, www.m-hkar.com http://dx.do.org/0.2988/ams.204.47554 Monotonc Interpolatng Curves by Usng Ratonal Cubc Ball Interpolaton Samsul Arffn

More information

P exp(tx) = 1 + t 2k M 2k. k N

P exp(tx) = 1 + t 2k M 2k. k N 1. Subgaussan tals Defnton. Say that a random varable X has a subgaussan dstrbuton wth scale factor σ< f P exp(tx) exp(σ 2 t 2 /2) for all real t. For example, f X s dstrbuted N(,σ 2 ) then t s subgaussan.

More information

An (almost) unbiased estimator for the S-Gini index

An (almost) unbiased estimator for the S-Gini index An (almost unbased estmator for the S-Gn ndex Thomas Demuynck February 25, 2009 Abstract Ths note provdes an unbased estmator for the absolute S-Gn and an almost unbased estmator for the relatve S-Gn for

More information

The lower and upper bounds on Perron root of nonnegative irreducible matrices

The 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 information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

General viscosity iterative method for a sequence of quasi-nonexpansive mappings

General 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 information

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 )

Yong 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 information

THE WEIGHTED WEAK TYPE INEQUALITY FOR THE STRONG MAXIMAL FUNCTION

THE WEIGHTED WEAK TYPE INEQUALITY FOR THE STRONG MAXIMAL FUNCTION THE WEIGHTED WEAK TYPE INEQUALITY FO THE STONG MAXIMAL FUNCTION THEMIS MITSIS Abstract. We prove the natural Fefferman-Sten weak type nequalty for the strong maxmal functon n the plane, under the assumpton

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 12 10/21/2013. Martingale Concentration Inequalities and Applications

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 12 10/21/2013. Martingale Concentration Inequalities and Applications MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.65/15.070J Fall 013 Lecture 1 10/1/013 Martngale Concentraton Inequaltes and Applcatons Content. 1. Exponental concentraton for martngales wth bounded ncrements.

More information

arxiv: v2 [math.ca] 24 Sep 2010

arxiv: v2 [math.ca] 24 Sep 2010 A Note on the Weghted Harmonc-Geometrc-Arthmetc Means Inequaltes arxv:0900948v2 [mathca] 24 Sep 200 Gérard Maze, Urs Wagner e-mal: {gmaze,uwagner}@mathuzhch Mathematcs Insttute Unversty of Zürch Wnterthurerstr

More information

Exercises of Chapter 2

Exercises of Chapter 2 Exercses of Chapter Chuang-Cheh Ln Department of Computer Scence and Informaton Engneerng, Natonal Chung Cheng Unversty, Mng-Hsung, Chay 61, Tawan. Exercse.6. Suppose that we ndependently roll two standard

More information

Supplementary material: Margin based PU Learning. Matrix Concentration Inequalities

Supplementary material: Margin based PU Learning. Matrix Concentration Inequalities Supplementary materal: Margn based PU Learnng We gve the complete proofs of Theorem and n Secton We frst ntroduce the well-known concentraton nequalty, so the covarance estmator can be bounded Then we

More information

On some variants of Jensen s inequality

On some variants of Jensen s inequality On some varants of Jensen s nequalty S S DRAGOMIR School of Communcatons & Informatcs, Vctora Unversty, Vc 800, Australa EMMA HUNT Department of Mathematcs, Unversty of Adelade, SA 5005, Adelade, Australa

More information

Perfect Competition and the Nash Bargaining Solution

Perfect Competition and the Nash Bargaining Solution Perfect Competton and the Nash Barganng Soluton Renhard John Department of Economcs Unversty of Bonn Adenauerallee 24-42 53113 Bonn, Germany emal: rohn@un-bonn.de May 2005 Abstract For a lnear exchange

More information

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,

More information

TAIL BOUNDS FOR SUMS OF GEOMETRIC AND EXPONENTIAL VARIABLES

TAIL BOUNDS FOR SUMS OF GEOMETRIC AND EXPONENTIAL VARIABLES TAIL BOUNDS FOR SUMS OF GEOMETRIC AND EXPONENTIAL VARIABLES SVANTE JANSON Abstract. We gve explct bounds for the tal probabltes for sums of ndependent geometrc or exponental varables, possbly wth dfferent

More information

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

COMPLEX NUMBERS AND QUADRATIC EQUATIONS COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s non-negatve Hence the equatons x, x, x + 7 0 etc are not

More information

e - c o m p a n i o n

e - 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 information

Research Article On the Open Problem Related to Rank Equalities for the Sum of Finitely Many Idempotent Matrices and Its Applications

Research Article On the Open Problem Related to Rank Equalities for the Sum of Finitely Many Idempotent Matrices and Its Applications e Scentfc World Journal Volume 204, Artcle ID 70243, 7 pages http://dxdoorg/055/204/70243 Research Artcle On the Open roblem Related to Ran Equaltes for the Sum of Fntely Many Idempotent Matrces and Its

More information

Existence of Two Conjugate Classes of A 5 within S 6. by Use of Character Table of S 6

Existence of Two Conjugate Classes of A 5 within S 6. by Use of Character Table of S 6 Internatonal Mathematcal Forum, Vol. 8, 2013, no. 32, 1591-159 HIKARI Ltd, www.m-hkar.com http://dx.do.org/10.12988/mf.2013.3359 Exstence of Two Conjugate Classes of A 5 wthn S by Use of Character Table

More information

On the correction of the h-index for career length

On the correction of the h-index for career length 1 On the correcton of the h-ndex for career length by L. Egghe Unverstet Hasselt (UHasselt), Campus Depenbeek, Agoralaan, B-3590 Depenbeek, Belgum 1 and Unverstet Antwerpen (UA), IBW, Stadscampus, Venusstraat

More information

On the size of quotient of two subsets of positive integers.

On the size of quotient of two subsets of positive integers. arxv:1706.04101v1 [math.nt] 13 Jun 2017 On the sze of quotent of two subsets of postve ntegers. Yur Shtenkov Abstract We obtan non-trval lower bound for the set A/A, where A s a subset of the nterval [1,

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

Foundations of Arithmetic

Foundations of Arithmetic Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an

More information

CHAPTER 14 GENERAL PERTURBATION THEORY

CHAPTER 14 GENERAL PERTURBATION THEORY CHAPTER 4 GENERAL PERTURBATION THEORY 4 Introducton A partcle n orbt around a pont mass or a sphercally symmetrc mass dstrbuton s movng n a gravtatonal potental of the form GM / r In ths potental t moves

More information

Dirichlet s Theorem In Arithmetic Progressions

Dirichlet s Theorem In Arithmetic Progressions Drchlet s Theorem In Arthmetc Progressons Parsa Kavkan Hang Wang The Unversty of Adelade February 26, 205 Abstract The am of ths paper s to ntroduce and prove Drchlet s theorem n arthmetc progressons,

More information

APPENDIX A Some Linear Algebra

APPENDIX 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 information

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION

More information

REAL ANALYSIS I HOMEWORK 1

REAL ANALYSIS I HOMEWORK 1 REAL ANALYSIS I HOMEWORK CİHAN BAHRAN The questons are from Tao s text. Exercse 0.0.. If (x α ) α A s a collecton of numbers x α [0, + ] such that x α

More information

The binomial transforms of the generalized (s, t )-Jacobsthal matrix sequence

The 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 information

A Local Variational Problem of Second Order for a Class of Optimal Control Problems with Nonsmooth Objective Function

A Local Variational Problem of Second Order for a Class of Optimal Control Problems with Nonsmooth Objective Function A Local Varatonal Problem of Second Order for a Class of Optmal Control Problems wth Nonsmooth Objectve Functon Alexander P. Afanasev Insttute for Informaton Transmsson Problems, Russan Academy of Scences,

More information

MMA and GCMMA two methods for nonlinear optimization

MMA and GCMMA two methods for nonlinear optimization MMA and GCMMA two methods for nonlnear optmzaton Krster Svanberg Optmzaton and Systems Theory, KTH, Stockholm, Sweden. krlle@math.kth.se Ths note descrbes the algorthms used n the author s 2007 mplementatons

More information

arxiv: v1 [math.ho] 18 May 2008

arxiv: v1 [math.ho] 18 May 2008 Recurrence Formulas for Fbonacc Sums Adlson J. V. Brandão, João L. Martns 2 arxv:0805.2707v [math.ho] 8 May 2008 Abstract. In ths artcle we present a new recurrence formula for a fnte sum nvolvng the Fbonacc

More information

STEINHAUS PROPERTY IN BANACH LATTICES

STEINHAUS PROPERTY IN BANACH LATTICES DEPARTMENT OF MATHEMATICS TECHNICAL REPORT STEINHAUS PROPERTY IN BANACH LATTICES DAMIAN KUBIAK AND DAVID TIDWELL SPRING 2015 No. 2015-1 TENNESSEE TECHNOLOGICAL UNIVERSITY Cookevlle, TN 38505 STEINHAUS

More information

Linear Algebra and its Applications

Linear 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 information

Estimation: Part 2. Chapter GREG estimation

Estimation: Part 2. Chapter GREG estimation Chapter 9 Estmaton: Part 2 9. GREG estmaton In Chapter 8, we have seen that the regresson estmator s an effcent estmator when there s a lnear relatonshp between y and x. In ths chapter, we generalzed the

More information

Quantum Particle Motion in Physical Space

Quantum Particle Motion in Physical Space Adv. Studes Theor. Phys., Vol. 8, 014, no. 1, 7-34 HIKARI Ltd, www.-hkar.co http://dx.do.org/10.1988/astp.014.311136 Quantu Partcle Moton n Physcal Space A. Yu. Saarn Dept. of Physcs, Saara State Techncal

More information

SUCCESSIVE MINIMA AND LATTICE POINTS (AFTER HENK, GILLET AND SOULÉ) M(B) := # ( B Z N)

SUCCESSIVE MINIMA AND LATTICE POINTS (AFTER HENK, GILLET AND SOULÉ) M(B) := # ( B Z N) SUCCESSIVE MINIMA AND LATTICE POINTS (AFTER HENK, GILLET AND SOULÉ) S.BOUCKSOM Abstract. The goal of ths note s to present a remarably smple proof, due to Hen, of a result prevously obtaned by Gllet-Soulé,

More information

Lecture Notes on Linear Regression

Lecture Notes on Linear Regression Lecture Notes on Lnear Regresson Feng L fl@sdueducn Shandong Unversty, Chna Lnear Regresson Problem In regresson problem, we am at predct a contnuous target value gven an nput feature vector We assume

More information

Generalizations Of Bernoulli s Inequality With Utility-Based Approach

Generalizations Of Bernoulli s Inequality With Utility-Based Approach Appled Mathematcs E-Notes, 13(2013), 212-220 c ISSN 1607-2510 Avalable free at mrror stes of http://www.math.nthu.edu.tw/ amen/ Generalzatons Of Bernoull s Inequalty Wth Utlty-Based Approach Alreza Hosenzadeh,

More information

BOUNDEDNESS OF THE RIESZ TRANSFORM WITH MATRIX A 2 WEIGHTS

BOUNDEDNESS 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 information

SOME NEW CHARACTERIZATION RESULTS ON EXPONENTIAL AND RELATED DISTRIBUTIONS. Communicated by Ahmad Reza Soltani. 1. Introduction

SOME NEW CHARACTERIZATION RESULTS ON EXPONENTIAL AND RELATED DISTRIBUTIONS. Communicated by Ahmad Reza Soltani. 1. Introduction Bulletn of the Iranan Mathematcal Socety Vol. 36 No. 1 (21), pp 257-272. SOME NEW CHARACTERIZATION RESULTS ON EXPONENTIAL AND RELATED DISTRIBUTIONS M. TAVANGAR AND M. ASADI Communcated by Ahmad Reza Soltan

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - 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 information

Geometry of Müntz Spaces

Geometry of Müntz Spaces WDS'12 Proceedngs of Contrbuted Papers, Part I, 31 35, 212. ISBN 978-8-7378-224-5 MATFYZPRESS Geometry of Müntz Spaces P. Petráček Charles Unversty, Faculty of Mathematcs and Physcs, Prague, Czech Republc.

More information

Some modelling aspects for the Matlab implementation of MMA

Some modelling aspects for the Matlab implementation of MMA Some modellng aspects for the Matlab mplementaton of MMA Krster Svanberg krlle@math.kth.se Optmzaton and Systems Theory Department of Mathematcs KTH, SE 10044 Stockholm September 2004 1. Consdered optmzaton

More information

MATH 829: Introduction to Data Mining and Analysis The EM algorithm (part 2)

MATH 829: Introduction to Data Mining and Analysis The EM algorithm (part 2) 1/16 MATH 829: Introducton to Data Mnng and Analyss The EM algorthm (part 2) Domnque Gullot Departments of Mathematcal Scences Unversty of Delaware Aprl 20, 2016 Recall 2/16 We are gven ndependent observatons

More information

Maximizing the number of nonnegative subsets

Maximizing the number of nonnegative subsets Maxmzng the number of nonnegatve subsets Noga Alon Hao Huang December 1, 213 Abstract Gven a set of n real numbers, f the sum of elements of every subset of sze larger than k s negatve, what s the maxmum

More information

SPECTRAL PROPERTIES OF IMAGE MEASURES UNDER THE INFINITE CONFLICT INTERACTION

SPECTRAL PROPERTIES OF IMAGE MEASURES UNDER THE INFINITE CONFLICT INTERACTION SPECTRAL PROPERTIES OF IMAGE MEASURES UNDER THE INFINITE CONFLICT INTERACTION SERGIO ALBEVERIO 1,2,3,4, VOLODYMYR KOSHMANENKO 5, MYKOLA PRATSIOVYTYI 6, GRYGORIY TORBIN 7 Abstract. We ntroduce the conflct

More information

Generalized Linear Methods

Generalized Linear Methods Generalzed Lnear Methods 1 Introducton In the Ensemble Methods the general dea s that usng a combnaton of several weak learner one could make a better learner. More formally, assume that we have a set

More information

Restricted divisor sums

Restricted divisor sums ACTA ARITHMETICA 02 2002) Restrcted dvsor sums by Kevn A Broughan Hamlton) Introducton There s a body of work n the lterature on varous restrcted sums of the number of dvsors of an nteger functon ncludng

More information

Remarks on the Properties of a Quasi-Fibonacci-like Polynomial Sequence

Remarks on the Properties of a Quasi-Fibonacci-like Polynomial Sequence Remarks on the Propertes of a Quas-Fbonacc-lke Polynomal Sequence Brce Merwne LIU Brooklyn Ilan Wenschelbaum Wesleyan Unversty Abstract Consder the Quas-Fbonacc-lke Polynomal Sequence gven by F 0 = 1,

More information

THERE ARE INFINITELY MANY FIBONACCI COMPOSITES WITH PRIME SUBSCRIPTS

THERE ARE INFINITELY MANY FIBONACCI COMPOSITES WITH PRIME SUBSCRIPTS Research and Communcatons n Mathematcs and Mathematcal Scences Vol 10, Issue 2, 2018, Pages 123-140 ISSN 2319-6939 Publshed Onlne on November 19, 2018 2018 Jyot Academc Press http://jyotacademcpressorg

More information

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction ECONOMICS 5* -- NOTE (Summary) ECON 5* -- NOTE The Multple Classcal Lnear Regresson Model (CLRM): Specfcaton and Assumptons. Introducton CLRM stands for the Classcal Lnear Regresson Model. The CLRM s also

More information

HADAMARD PRODUCT VERSIONS OF THE CHEBYSHEV AND KANTOROVICH INEQUALITIES

HADAMARD 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 information

The Expectation-Maximization Algorithm

The Expectation-Maximization Algorithm The Expectaton-Maxmaton Algorthm Charles Elan elan@cs.ucsd.edu November 16, 2007 Ths chapter explans the EM algorthm at multple levels of generalty. Secton 1 gves the standard hgh-level verson of the algorthm.

More information

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP

FACTORIZATION 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 information

Determinants Containing Powers of Generalized Fibonacci Numbers

Determinants 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 information

MA 323 Geometric Modelling Course Notes: Day 13 Bezier Curves & Bernstein Polynomials

MA 323 Geometric Modelling Course Notes: Day 13 Bezier Curves & Bernstein Polynomials MA 323 Geometrc Modellng Course Notes: Day 13 Bezer Curves & Bernsten Polynomals Davd L. Fnn Over the past few days, we have looked at de Casteljau s algorthm for generatng a polynomal curve, and we have

More information

SELECTED PROOFS. DeMorgan s formulas: The first one is clear from Venn diagram, or the following truth table:

SELECTED PROOFS. DeMorgan s formulas: The first one is clear from Venn diagram, or the following truth table: SELECTED PROOFS DeMorgan s formulas: The frst one s clear from Venn dagram, or the followng truth table: A B A B A B Ā B Ā B T T T F F F F T F T F F T F F T T F T F F F F F T T T T The second one can be

More information

arxiv: v1 [quant-ph] 6 Sep 2007

arxiv: v1 [quant-ph] 6 Sep 2007 An Explct Constructon of Quantum Expanders Avraham Ben-Aroya Oded Schwartz Amnon Ta-Shma arxv:0709.0911v1 [quant-ph] 6 Sep 2007 Abstract Quantum expanders are a natural generalzaton of classcal expanders.

More information

The Quadratic Trigonometric Bézier Curve with Single Shape Parameter

The Quadratic Trigonometric Bézier Curve with Single Shape Parameter J. Basc. Appl. Sc. Res., (3541-546, 01 01, TextRoad Publcaton ISSN 090-4304 Journal of Basc and Appled Scentfc Research www.textroad.com The Quadratc Trgonometrc Bézer Curve wth Sngle Shape Parameter Uzma

More information

Bezier curves. Michael S. Floater. August 25, These notes provide an introduction to Bezier curves. i=0

Bezier curves. Michael S. Floater. August 25, These notes provide an introduction to Bezier curves. i=0 Bezer curves Mchael S. Floater August 25, 211 These notes provde an ntroducton to Bezer curves. 1 Bernsten polynomals Recall that a real polynomal of a real varable x R, wth degree n, s a functon of the

More information

Lecture 17 : Stochastic Processes II

Lecture 17 : Stochastic Processes II : Stochastc Processes II 1 Contnuous-tme stochastc process So far we have studed dscrete-tme stochastc processes. We studed the concept of Makov chans and martngales, tme seres analyss, and regresson analyss

More information

ON SEPARATING SETS OF WORDS IV

ON 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 information

Geometric drawings of K n with few crossings

Geometric drawings of K n with few crossings Geometrc drawngs of K n wth few crossngs Bernardo M. Ábrego, Slva Fernández-Merchant Calforna State Unversty Northrdge {bernardo.abrego,slva.fernandez}@csun.edu ver 9 Abstract We gve a new upper bound

More information

A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS

A 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 information

The Minimum Universal Cost Flow in an Infeasible Flow Network

The Minimum Universal Cost Flow in an Infeasible Flow Network Journal of Scences, Islamc Republc of Iran 17(2): 175-180 (2006) Unversty of Tehran, ISSN 1016-1104 http://jscencesutacr The Mnmum Unversal Cost Flow n an Infeasble Flow Network H Saleh Fathabad * M Bagheran

More information

Math 426: Probability MWF 1pm, Gasson 310 Homework 4 Selected Solutions

Math 426: Probability MWF 1pm, Gasson 310 Homework 4 Selected Solutions Exercses from Ross, 3, : Math 26: Probablty MWF pm, Gasson 30 Homework Selected Solutons 3, p. 05 Problems 76, 86 3, p. 06 Theoretcal exercses 3, 6, p. 63 Problems 5, 0, 20, p. 69 Theoretcal exercses 2,

More information