HADAMARD PRODUCT VERSIONS OF THE CHEBYSHEV AND KANTOROVICH INEQUALITIES

Size: px
Start display at page:

Download "HADAMARD PRODUCT VERSIONS OF THE CHEBYSHEV AND KANTOROVICH INEQUALITIES"

Transcription

1 HADAMARD PRODUCT VERSIONS OF THE CHEBYSHEV AND KANTOROVICH INEQUALITIES JAGJIT SINGH MATHARU AND JASPAL SINGH AUJLA Department of Mathematcs Natonal Insttute of Technology Jalandhar , Punab, INDIA EMal: Receved: 10 February, 2009 Accepted: 15 Aprl, 2009 Communcated by: S. Puntanen 2000 AMS Sub. Class.: Prmary 15A48; Secondary 15A18, 15A45. Key words: Abstract: Chebyshev nequalty, Kantorovch nequalty, Hadamard product The purpose of ths note s to prove Hadamard product versons of the Chebyshev and the Kantorovch nequaltes for postve real numbers. We also prove a generalzaton of Fedler s nequalty. Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 1 of 13 Acknowledgements: The authors thank a referee for useful suggestons.

2 1 Introducton 3 2 The Chebyshev and Kantorovch Inequaltes: Matrx Versons 5 Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 2 of 13

3 1. Introducton In what follows, the captal letters A, B, C,... denote m m complex matrces, whereas the small letters a, b, c,... denote real numbers, unless mentoned otherwse. By X Y we mean that X Y s postve semdefnte X > Y mean X Y s postve defnte. For A = a and B = b, A B = a b denotes the Hadamard product of A and B. Accordng to Schur s theorem [4, Page 23] the Hadamard product s monotone n the sense that A B, C D mples A C B D. The tensor product A B s the m 2 m 2 matrx 1.1 a 11 B a 1m B... a m1 B a mm B Marcus and Khan n [10] made the smple but mportant observaton that the Hadamard product s a prncpal submatrx of the tensor product. The nequalty n 1.2 w b w a b w a holds for all a 1 a 2 a n 0, b 1 b 2 b n 0 and weghts w 0, = 1,..., n. Hardy, Lttlewood and Polya [6, page 43] attrbute ths nequalty to Chebyshev. For 0 < a a b, w 0, = 1, 2,..., n, Kantorovch s nequalty states that 2 w a + b2 1.3 w a w. a 4ab Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 3 of 13

4 In Secton 2, we state and prove matrx versons of nequaltes 1.2 and 1.3 nvolvng the Hadamard product. A generalzaton of Fedler s nequalty s also proved n ths secton. There are several generalzatons of Kantorovch and Fedler s nequalty; see [2, 3, 8, 9]. Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 4 of 13

5 2. The Chebyshev and Kantorovch Inequaltes: Matrx Versons We begn wth a Hadamard product verson of nequalty 1.2. Theorem 2.1. Let A 1 A n 0 and B 1 B n 0. Then 2.1 w A w B w A B, where w 0, = 1,..., n, are weghts. Proof. We have 2.2 w w n = w w A B w w A B = 1 2 = 1 2,=1 w A B w A w B n,=1 w w A B w w A B + w w A B w w A B n w w A A B B.,=1 Snce the Hadamard product of two postve semdefnte matrces s postve semdefnte, therefore the summand n 2.2 s postve semdefnte. Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 5 of 13

6 Our next result s a Hadamard product verson of nequalty 1.3. Theorem 2.2. Let A 1,..., A n be such that 0 < ai m A bi m, = 1,..., n here I m denotes the m m dentty matrx. Then 2.3 A for all W 0, = 1,..., n. Proof. We frst prove the nequalty A 1 a2 + b 2 2ab W W 2.4 P 1/2 AP 1/2 Q 1/2 B 1 Q 1/2 + P 1/2 A 1 P 1/2 Q 1/2 BQ 1/2 a2 + b 2 P Q, ab when 0 < ai m A, B bi m and P, Q 0. Let A = UDU and B = V ΓV wth untary U and V, and dagonal matrces D and Γ. Then A B 1 + A 1 B = U V D Γ + Γ 1 DU V a 2 + b 2 U V I m I m U V ab = a2 + b 2 I m I m, ab where the nequalty follows from 1.3. Thus we have Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 6 of P 1/2 AP 1/2 Q 1/2 B 1 Q 1/2 + P 1/2 A 1 P 1/2 Q 1/2 BQ 1/2

7 = P 1/2 Q 1/2 A B 1 + A 1 BP 1/2 Q 1/2 a2 + b 2 P Q. ab Snce the Hadamard product s a prncpal submatrx of the tensor product, the nequalty 2.4 follows from 2.5. On takng B = A and Q = P n 2.4 we see that 2.3 holds for n = 1. Further, by 2.4 we have A A 1 + A 1 for, = 1,..., n. Summng over,, we have n,=1 [ A A 1 whch mples that A A 1 A a2 + b 2 W W ab ] n a 2 + b 2 W W, ab,=1 a 2 + b 2 n n W W. 2ab The next corollary follows on takng W = w I m, = 1,..., n. Corollary 2.3. Let A 1,..., A n be such that 0 < ai m A bi m, and w 0, = 1,..., n be weghts. Then 2 a w A w A b 2 n w I m. 2ab Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 7 of 13

8 Remark 1. The case n = 1 of Corollary 2.3 s proved n [7]. The example 2 1 A =, a = 3 5, b = shows that the nequalty need not be true. A A 1 a + b2 I 2 4ab For our next result we need the followng lemma. Lemma 2.4. Let 0 r 1. Then A r + A r A + A 1 for all A > 0. Proof. Suppose that A = UΓU wth untary U and dagonal matrx Γ. Then A r + A r = UΓ r + Γ r U UΓ + Γ 1 U = A + A 1 snce x r + x r x + x 1 for any postve real number x and 0 r 1. Theorem 2.5. Let 0 α < β. Then A α for all A > 0 and W 0, = 1,..., n. A α A β A β Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 8 of 13

9 Proof. We frst prove the nequalty 2.7 A α A α + A α A α A β + for 0 α < β. Let 0 r 1. Then A r A r A = r A r = A A 1 A A 1 + A r + A r r + A A 1 A β A β A r A β A r r + A A 1 1 where the nequalty follows from Lemma 2.4. Takng r = α/β and replacng A by A β and A by A β, we have A α A β A α A β + + A α A β A α A β. Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 9 of 13 Agan usng the fact that the Hadamard product s a prncpal submatrx of the tensor

10 product, the precedng nequalty mples 2.7. Summng over, n 2.7, we have A α A α A β A β. A α Corollary 2.6. Let 0 α < β. Then for all A > 0, = 1,..., n. =1 A α A β Proof. Takng W = I m n Theorem 2.5 we get the desred result. =1 A β Corollary 2.7. Let 0 β. Then I m A β A β for all A > 0 and W 0, = 1,..., n, where n W = I m. Proof. Takng α = 0 n Theorem 2.5 gves the desred nequalty. Remark 2. Corollary 2.7 s another generalzaton of Fedler s nequalty [5] Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 10 of 13 A A 1 I m.

11 Next we prove a convexty theorem nvolvng the Hadamard product. Theorem 2.8. The functon ft = A 1+t B 1 t + A 1 t B 1+t s convex on the nterval [ 1, 1] and attans ts mnmum at t = 0 for all A, B > 0. Proof. Snce f s contnuous we need to prove only that f s md-pont convex. Note that for A, B > 0 and s, t n [ 1, 1] the matrces A 1+s+t A 1+s A 1 s+t A A 1+s A 1+s t, 1 s A 1 s A 1 s t, B 1+s+t B 1+s B 1 s+t B B 1+s B 1+s t, 1 s B 1 s B 1 s t are postve semdefnte. Hence the matrx A X= 1+s+t B 1 s+t + A 1 s+t B 1+s+t A 1+s B 1 s + A 1 s B 1+s A 1+s B 1 s + A 1 s B 1+s A 1+s t B 1 s t + A 1 s t B 1+s t s postve semdefnte. Smlarly, the matrx A Y = 1+s t B 1 s t + A 1 s t B 1+s t A 1+s B 1 s + A 1 s B 1+s A 1+s B 1 s + A 1 s B 1+s A 1+s+t B 1 s+t + A 1 s+t B 1+s+t s postve semdefnte. Hence fs + t + fs t 2fs 2.8 X + Y = 2fs fs + t + fs t s postve semdefnte, whch mples that Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 11 of 13 fs 1 [fs + t + fs t]. 2

12 Ths proves the convexty of f. Further, note that ft = f t. Ths together wth the convexty of f mples that f attans ts mnmum at 0. Corollary 2.9. The functon gt = A t B 1 t + A 1 t B t s decreasng on [0, 1/2], ncreasng on [1/2, 1], and attans ts mnmum at t = 1 2 for all A, B > 0. Proof. The proof follows on replacng A, B by A 1/2, B 1/2 and t by 1+t 2 n Theorem 2.8. A norm on m m complex matrces s called untarly nvarant f UXV = X for all untary matrces U, V. If A s postve semdefnte and X s any matrx, then A X max a X for all untarly nvarant norms [1]. Thus the proof of the followng corollary follows from Corollary 2.9 usng the fact that g1/2 gt g1 = g0. Corollary Let 0 t 1. Then, 2 A 1/2 B 1/2 A t B 1 t + A 1 t B t A + B for all untarly nvarant norms and all A, B > 0. Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 12 of 13

13 References [1] T. ANDO, R.A. HORN AND C.R. JOHNSON, The sngular values of the Hadamard product: A basc nequalty, Lnear Multlnear Algebra, , [2] J.K. BAKSALARY AND S. PUNTANEN, Generalzed matrx versons of the Cauchy-Schwarz and Kantorovch nequaltes, Aequatones Math., , [3] R.B. BAPAT AND M.K. KWONG, A generalsaton of A A 1 I, Lnear Algebra Appl., , [4] R. BHATIA, Matrx Analyss, Sprnger Verlag, New York, [5] M. FIEDLER, Über ene Unglechung für postv defnte Matrzen, Math. Nachrchten, , [6] G.H. HARDY, J.E. LITTLEWOOD AND G. POLYA, Inequaltes, Cambrdge Unversty Press, Cambrdge, [7] J. MIĆIĆ, J. PECARIC AND Y. SEO, Complementary nequaltes to nequaltes of Jensen and Ando based on the Mond-Pečarć method, Lnear Algebra Appl., , [8] A.W. MARSHALL AND I. OLKIN, Matrx versons of the Cauchy and Kantorovch nequaltes, Aequatones Math., , [9] M. SINGH, J.S. AUJLA AND H.L. VASUDEVA, Inequaltes for Hadamard product and untarly nvarant norms of matrces, Lnear Multlnear Algebra, , [10] M. MARCUS AND N.A. KHAN, A note on Hadamard product, Canad. Math. Bull., , Hadamard Product Versons Jagt Sngh Matharu and Jaspal Sngh Aula vol. 10, ss. 2, art. 51, 2009 Ttle Page Page 13 of 13

An Inequality for the trace of matrix products, using absolute values

An Inequality for the trace of matrix products, using absolute values arxv:1106.6189v2 [math-ph] 1 Sep 2011 An Inequalty for the trace of matrx products, usng absolute values Bernhard Baumgartner 1 Fakultät für Physk, Unverstät Wen Boltzmanngasse 5, A-1090 Venna, Austra

More information

CSCE 790S Background Results

CSCE 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 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

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

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

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

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

On Finite Rank Perturbation of Diagonalizable Operators

On 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 information

REFINING CBS INEQUALITY FOR DIVISIONS OF MEASURABLE SPACE

REFINING CBS INEQUALITY FOR DIVISIONS OF MEASURABLE SPACE EFINING CBS INEQUALITY FO DIVISIONS OF MEASUABLE SPACE S. S. DAGOMI ; Abstract. In ths paper we establsh a re nement some reverses for CBS nequalty for the general Lebesgue ntegral on dvsons of measurable

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

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

Cauchy-Schwarz Inequalities Associated with Positive Semidenite. Matrices. Roger A. Horn and Roy Mathias. October 9, 2000

Cauchy-Schwarz Inequalities Associated with Positive Semidenite. Matrices. Roger A. Horn and Roy Mathias. October 9, 2000 Cauchy-Schwarz Inequaltes ssocated wth Postve Semdente Matrces Roger. Horn and Roy Mathas Department of Mathematcal Scences The Johns Hopkns Unversty, altmore, Maryland 228 October 9, 2 Lnear lgebra and

More information

OPERATOR POWER MEANS DUE TO LAWSON-LIM-PÁLFIA FOR 1 < t < 2

OPERATOR POWER MEANS DUE TO LAWSON-LIM-PÁLFIA FOR 1 < t < 2 OPERATOR POWER MEANS DUE TO LAWSON-LIM-PÁLFIA FOR 1 < t < 2 YUKI SEO Abstract. For 1 t 1, Lm-Pálfa defned a new famly of operator power means of postve defnte matrces and subsequently by Lawson-Lm ther

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

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

THE Hadamard product of two nonnegative matrices and

THE 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 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

Econometrica Supplementary Material

Econometrica Supplementary Material Econometrca Supplementary Materal SUPPLEMENT TO IDENTIFICATION AND ESTIMATION OF TRIANGULAR SIMULTANEOUS EQUATIONS MODELS WITHOUT ADDITIVITY Econometrca, Vol. 77, No. 5, September 009, 48 5) BY GUIDO W.

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

Bounds for Spectral Radius of Various Matrices Associated With Graphs

Bounds 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 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

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 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 information

Math 217 Fall 2013 Homework 2 Solutions

Math 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 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

A generalization of a trace inequality for positive definite matrices

A generalization of a trace inequality for positive definite matrices A generalzaton of a trace nequalty for postve defnte matrces Elena Veronca Belmega, Marc Jungers, Samson Lasaulce To cte ths verson: Elena Veronca Belmega, Marc Jungers, Samson Lasaulce. A generalzaton

More information

Chapter 7 Generalized and Weighted Least Squares Estimation. In this method, the deviation between the observed and expected values of

Chapter 7 Generalized and Weighted Least Squares Estimation. In this method, the deviation between the observed and expected values of Chapter 7 Generalzed and Weghted Least Squares Estmaton The usual lnear regresson model assumes that all the random error components are dentcally and ndependently dstrbuted wth constant varance. When

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

Norm Bounds for a Transformed Activity Level. Vector in Sraffian Systems: A Dual Exercise

Norm 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 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

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

Solutions HW #2. minimize. Ax = b. Give the dual problem, and make the implicit equality constraints explicit. Solution.

Solutions HW #2. minimize. Ax = b. Give the dual problem, and make the implicit equality constraints explicit. Solution. Solutons HW #2 Dual of general LP. Fnd the dual functon of the LP mnmze subject to c T x Gx h Ax = b. Gve the dual problem, and make the mplct equalty constrants explct. Soluton. 1. The Lagrangan s L(x,

More information

EXPONENTIAL ERGODICITY FOR SINGLE-BIRTH PROCESSES

EXPONENTIAL ERGODICITY FOR SINGLE-BIRTH PROCESSES J. Appl. Prob. 4, 022 032 (2004) Prnted n Israel Appled Probablty Trust 2004 EXPONENTIAL ERGODICITY FOR SINGLE-BIRTH PROCESSES YONG-HUA MAO and YU-HUI ZHANG, Beng Normal Unversty Abstract An explct, computable,

More information

The Degrees of Nilpotency of Nilpotent Derivations on the Ring of Matrices

The 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 information

Zhi-Wei Sun (Nanjing)

Zhi-Wei Sun (Nanjing) Acta Arth. 1262007, no. 4, 387 398. COMBINATORIAL CONGRUENCES AND STIRLING NUMBERS Zh-We Sun Nanng Abstract. In ths paper we obtan some sophstcated combnatoral congruences nvolvng bnomal coeffcents and

More information

On an operator inequality

On an operator inequality Linear Algebra and its Applications 310 (000 3 7 www.elsevier.com/locate/laa On an operator inequality Jaspal Singh Aujla Department of Applied Mathematics, Regional Engineering College, Jalandhar 1011,

More information

2.3 Nilpotent endomorphisms

2.3 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 information

On (T,f )-connections of matrices and generalized inverses of linear operators

On (T,f )-connections of matrices and generalized inverses of linear operators Electronic Journal of Linear Algebra Volume 30 Volume 30 (2015) Article 33 2015 On (T,f )-connections of matrices and generalized inverses of linear operators Marek Niezgoda University of Life Sciences

More information

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017

U.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 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

Math 702 Midterm Exam Solutions

Math 702 Midterm Exam Solutions Math 702 Mdterm xam Solutons The terms measurable, measure, ntegrable, and almost everywhere (a.e.) n a ucldean space always refer to Lebesgue measure m. Problem. [6 pts] In each case, prove the statement

More information

Kantorovich type inequalities for ordered linear spaces

Kantorovich type inequalities for ordered linear spaces Electronic Journal of Linear Algebra Volume 20 Volume 20 (2010) Article 8 2010 Kantorovich type inequalities for ordered linear spaces Marek Niezgoda bniezgoda@wp.pl Follow this and additional works at:

More information

Ann. Funct. Anal. 5 (2014), no. 2, A nnals of F unctional A nalysis ISSN: (electronic) URL:www.emis.

Ann. Funct. Anal. 5 (2014), no. 2, A nnals of F unctional A nalysis ISSN: (electronic) URL:www.emis. Ann. Funct. Anal. 5 (2014), no. 2, 147 157 A nnals of F unctional A nalysis ISSN: 2008-8752 (electronic) URL:www.emis.de/journals/AFA/ ON f-connections OF POSITIVE DEFINITE MATRICES MAREK NIEZGODA This

More information

SL n (F ) Equals its Own Derived Group

SL 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 information

Research Article An Extension of Stolarsky Means to the Multivariable Case

Research Article An Extension of Stolarsky Means to the Multivariable Case Internatonal Mathematcs and Mathematcal Scences Volume 009, Artcle ID 43857, 14 pages do:10.1155/009/43857 Research Artcle An Extenson of Stolarsky Means to the Multvarable Case Slavko Smc Mathematcal

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

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

Projective change between two Special (α, β)- Finsler Metrics

Projective 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 information

Binomial transforms of the modified k-fibonacci-like sequence

Binomial 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 information

arxiv: v1 [math.fa] 13 Dec 2011

arxiv: v1 [math.fa] 13 Dec 2011 NON-COMMUTATIVE CALLEBAUT INEQUALITY arxiv:.3003v [ath.fa] 3 Dec 0 MOHAMMAD SAL MOSLEHIAN, JAGJIT SINGH MATHARU AND JASPAL SINGH AUJLA 3 Abstract. We present an operator version of the Callebaut inequality

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

Stanford University CS359G: Graph Partitioning and Expanders Handout 4 Luca Trevisan January 13, 2011

Stanford University CS359G: Graph Partitioning and Expanders Handout 4 Luca Trevisan January 13, 2011 Stanford Unversty CS359G: Graph Parttonng and Expanders Handout 4 Luca Trevsan January 3, 0 Lecture 4 In whch we prove the dffcult drecton of Cheeger s nequalty. As n the past lectures, consder an undrected

More information

2 S. S. DRAGOMIR, N. S. BARNETT, AND I. S. GOMM Theorem. Let V :(d d)! R be a twce derentable varogram havng the second dervatve V :(d d)! R whch s bo

2 S. S. DRAGOMIR, N. S. BARNETT, AND I. S. GOMM Theorem. Let V :(d d)! R be a twce derentable varogram havng the second dervatve V :(d d)! R whch s bo J. KSIAM Vol.4, No., -7, 2 FURTHER BOUNDS FOR THE ESTIMATION ERROR VARIANCE OF A CONTINUOUS STREAM WITH STATIONARY VARIOGRAM S. S. DRAGOMIR, N. S. BARNETT, AND I. S. GOMM Abstract. In ths paper we establsh

More information

Hyper-Sums of Powers of Integers and the Akiyama-Tanigawa Matrix

Hyper-Sums of Powers of Integers and the Akiyama-Tanigawa Matrix 6 Journal of Integer Sequences, Vol 8 (00), Artcle 0 Hyper-Sums of Powers of Integers and the Ayama-Tangawa Matrx Yoshnar Inaba Toba Senor Hgh School Nshujo, Mnam-u Kyoto 60-89 Japan nava@yoto-benejp Abstract

More information

Eigenvalue inequalities for convex and log-convex functions

Eigenvalue inequalities for convex and log-convex functions Linear Algebra and its Applications 44 (007) 5 35 www.elsevier.com/locate/laa Eigenvalue inequalities for convex and log-convex functions Jaspal Singh Aujla a,, Jean-Christophe Bourin b a Department of

More information

An Explicit Construction of an Expander Family (Margulis-Gaber-Galil)

An Explicit Construction of an Expander Family (Margulis-Gaber-Galil) An Explct Constructon of an Expander Famly Marguls-Gaber-Gall) Orr Paradse July 4th 08 Prepared for a Theorst's Toolkt, a course taught by Irt Dnur at the Wezmann Insttute of Scence. The purpose of these

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

Introduction. - The Second Lyapunov Method. - The First Lyapunov Method

Introduction. - The Second Lyapunov Method. - The First Lyapunov Method Stablty Analyss A. Khak Sedgh Control Systems Group Faculty of Electrcal and Computer Engneerng K. N. Toos Unversty of Technology February 2009 1 Introducton Stablty s the most promnent characterstc of

More information

MAT 578 Functional Analysis

MAT 578 Functional Analysis MAT 578 Functonal Analyss John Qugg Fall 2008 Locally convex spaces revsed September 6, 2008 Ths secton establshes the fundamental propertes of locally convex spaces. Acknowledgment: although I wrote these

More information

MATH Homework #2

MATH 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 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

Large-Scale Data-Dependent Kernel Approximation Appendix

Large-Scale Data-Dependent Kernel Approximation Appendix Large-Scale Data-Depenent Kernel Approxmaton Appenx Ths appenx presents the atonal etal an proofs assocate wth the man paper [1]. 1 Introucton Let k : R p R p R be a postve efnte translaton nvarant functon

More information

Lecture 3. Ax x i a i. i i

Lecture 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 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

A Simple Proof of Sylvester s (Determinants) Identity

A Simple Proof of Sylvester s (Determinants) Identity Appled Mathematcal Scences, Vol 2, 2008, no 32, 1571-1580 A Smple Proof of Sylvester s (Determnants) Identty Abdelmalek Salem Department of Mathematcs and Informatques, Unversty Centre Chekh Larb Tebess

More information

Anti-van der Waerden numbers of 3-term arithmetic progressions.

Anti-van der Waerden numbers of 3-term arithmetic progressions. Ant-van der Waerden numbers of 3-term arthmetc progressons. Zhanar Berkkyzy, Alex Schulte, and Mchael Young Aprl 24, 2016 Abstract The ant-van der Waerden number, denoted by aw([n], k), s the smallest

More information

for Linear Systems With Strictly Diagonally Dominant Matrix

for 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 information

Discrete Mathematics. Laplacian spectral characterization of some graphs obtained by product operation

Discrete 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 information

SELECTED SOLUTIONS, SECTION (Weak duality) Prove that the primal and dual values p and d defined by equations (4.3.2) and (4.3.3) satisfy p d.

SELECTED SOLUTIONS, SECTION (Weak duality) Prove that the primal and dual values p and d defined by equations (4.3.2) and (4.3.3) satisfy p d. SELECTED SOLUTIONS, SECTION 4.3 1. Weak dualty Prove that the prmal and dual values p and d defned by equatons 4.3. and 4.3.3 satsfy p d. We consder an optmzaton problem of the form The Lagrangan for ths

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

Lecture 20: Lift and Project, SDP Duality. Today we will study the Lift and Project method. Then we will prove the SDP duality theorem.

Lecture 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 information

A FORMULA FOR COMPUTING INTEGER POWERS FOR ONE TYPE OF TRIDIAGONAL MATRIX

A 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 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

On statistical convergence in generalized Lacunary sequence spaces

On statistical convergence in generalized Lacunary sequence spaces BULETINUL ACADEMIEI DE ŞTIINŢE A REPUBLICII MOLDOVA. MATEMATICA Number 2(87), 208, Pages 7 29 ISSN 024 7696 On statstcal convergence n generalzed Lacunary sequence spaces K.Raj, R.Anand Abstract. In the

More information

Short running title: A generating function approach A GENERATING FUNCTION APPROACH TO COUNTING THEOREMS FOR SQUARE-FREE POLYNOMIALS AND MAXIMAL TORI

Short running title: A generating function approach A GENERATING FUNCTION APPROACH TO COUNTING THEOREMS FOR SQUARE-FREE POLYNOMIALS AND MAXIMAL TORI Short runnng ttle: A generatng functon approach A GENERATING FUNCTION APPROACH TO COUNTING THEOREMS FOR SQUARE-FREE POLYNOMIALS AND MAXIMAL TORI JASON FULMAN Abstract. A recent paper of Church, Ellenberg,

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

A property of the elementary symmetric functions

A 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 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

Journal of Inequalities in Pure and Applied Mathematics

Journal of Inequalities in Pure and Applied Mathematics Journal of Inequalities in Pure and Applied Mathematics KANTOROVICH TYPE INEQUALITIES FOR 1 > p > 0 MARIKO GIGA Department of Mathematics Nippon Medical School 2-297-2 Kosugi Nakahara-ku Kawasaki 211-0063

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

A New Refinement of Jacobi Method for Solution of Linear System Equations AX=b

A 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 information

n ). This is tight for all admissible values of t, k and n. k t + + n t

n ). This is tight for all admissible values of t, k and n. k t + + n t MAXIMIZING THE NUMBER OF NONNEGATIVE SUBSETS NOGA ALON, HAROUT AYDINIAN, AND HAO HUANG Abstract. Gven a set of n real numbers, f the sum of elements of every subset of sze larger than k s negatve, what

More information

Christian Aebi Collège Calvin, Geneva, Switzerland

Christian Aebi Collège Calvin, Geneva, Switzerland #A7 INTEGERS 12 (2012) A PROPERTY OF TWIN PRIMES Chrstan Aeb Collège Calvn, Geneva, Swtzerland chrstan.aeb@edu.ge.ch Grant Carns Department of Mathematcs, La Trobe Unversty, Melbourne, Australa G.Carns@latrobe.edu.au

More information

A GENERALIZATION OF JUNG S THEOREM. M. Henk

A GENERALIZATION OF JUNG S THEOREM. M. Henk A GENERALIZATION OF JUNG S THEOREM M. Henk Abstract. The theorem of Jung establshes a relaton between crcumraus an ameter of a convex boy. The half of the ameter can be nterprete as the maxmum of crcumra

More information

ON THE EXTENDED HAAGERUP TENSOR PRODUCT IN OPERATOR SPACES. 1. Introduction

ON THE EXTENDED HAAGERUP TENSOR PRODUCT IN OPERATOR SPACES. 1. Introduction ON THE EXTENDED HAAGERUP TENSOR PRODUCT IN OPERATOR SPACES TAKASHI ITOH AND MASARU NAGISA Abstract We descrbe the Haagerup tensor product l h l and the extended Haagerup tensor product l eh l n terms of

More information

REGULAR POSITIVE TERNARY QUADRATIC FORMS. 1. Introduction

REGULAR POSITIVE TERNARY QUADRATIC FORMS. 1. Introduction REGULAR POSITIVE TERNARY QUADRATIC FORMS BYEONG-KWEON OH Abstract. A postve defnte quadratc form f s sad to be regular f t globally represents all ntegers that are represented by the genus of f. In 997

More information

arxiv: v1 [math.sp] 3 Nov 2011

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 information

Complete subgraphs in multipartite graphs

Complete 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 information

A summation on Bernoulli numbers

A summation on Bernoulli numbers Journal of Number Theory 111 (005 37 391 www.elsever.com/locate/jnt A summaton on Bernoull numbers Kwang-Wu Chen Department of Mathematcs and Computer Scence Educaton, Tape Muncpal Teachers College, No.

More information

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg prnceton unv. F 17 cos 521: Advanced Algorthm Desgn Lecture 7: LP Dualty Lecturer: Matt Wenberg Scrbe: LP Dualty s an extremely useful tool for analyzng structural propertes of lnear programs. Whle there

More information

A new construction of 3-separable matrices via an improved decoding of Macula s construction

A new construction of 3-separable matrices via an improved decoding of Macula s construction Dscrete Optmzaton 5 008 700 704 Contents lsts avalable at ScenceDrect Dscrete Optmzaton journal homepage: wwwelsevercom/locate/dsopt A new constructon of 3-separable matrces va an mproved decodng of Macula

More information

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016

U.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 information

Quantum Mechanics I - Session 4

Quantum Mechanics I - Session 4 Quantum Mechancs I - Sesson 4 Aprl 3, 05 Contents Operators Change of Bass 4 3 Egenvectors and Egenvalues 5 3. Denton....................................... 5 3. Rotaton n D....................................

More information

Random Walks on Digraphs

Random 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 information

10-801: Advanced Optimization and Randomized Methods Lecture 2: Convex functions (Jan 15, 2014)

10-801: Advanced Optimization and Randomized Methods Lecture 2: Convex functions (Jan 15, 2014) 0-80: Advanced Optmzaton and Randomzed Methods Lecture : Convex functons (Jan 5, 04) Lecturer: Suvrt Sra Addr: Carnege Mellon Unversty, Sprng 04 Scrbes: Avnava Dubey, Ahmed Hefny Dsclamer: These notes

More information

COUNTABLE-CODIMENSIONAL SUBSPACES OF LOCALLY CONVEX SPACES

COUNTABLE-CODIMENSIONAL SUBSPACES OF LOCALLY CONVEX SPACES COUNTABLE-CODIMENSIONAL SUBSPACES OF LOCALLY CONVEX SPACES by J. H. WEBB (Receved 9th December 1971) A barrel n a locally convex Hausdorff space E[x] s a closed absolutely convex absorbent set. A a-barrel

More information

COMPUTING THE NORM OF A MATRIX

COMPUTING THE NORM OF A MATRIX COMPUTING THE NORM OF A MATRIX KEITH CONRAD 1. Introducton In R n there s a standard noton of length: the sze of a vector v = (a 1,..., a n ) s v = a 2 1 + + a2 n. We wll dscuss n Secton 2 the general

More information

Stability analysis for class of switched nonlinear systems

Stability analysis for class of switched nonlinear systems Stablty analyss for class of swtched nonlnear systems The MIT Faculty has made ths artcle openly avalable. Please share how ths access benefts you. Your story matters. Ctaton As Publshed Publsher Shaker,

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

Formulas for the Determinant

Formulas for the Determinant page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use

More information