Properties of k - CentroSymmetric and k Skew CentroSymmetric Matrices

Size: px
Start display at page:

Download "Properties of k - CentroSymmetric and k Skew CentroSymmetric Matrices"

Transcription

1 International Journal of Pure and Applied Mathematical Sciences. ISSN Volume 10, Number 1 (2017), pp Research India Publications Properties of k - CentroSymmetric and k Skew CentroSymmetric Matrices 1 Dr. N.Elumalai and 2 Mrs.B.Arthi 1 Associate Professor, 2 Assistant Professor 1 Department of Mathematics, A.V.C. College (Autonomous), Mannampandal, TamilNadu, India. 2 Department of Mathematics, A.V.C. College (Autonomous), Mannampandal, TamilNadu, India. Abstract The basic concepts and theorems of k- Centrosymmetric, k- Skew Centrosymmetric matrices are introduced with examples. Keywords: Symmetric matrix, Centrosymmetric,k- Centrosymmetric matrix,skewsymmetric matrix Skew Centrosymmetric matrix and k-skew centrosymmetric matrix. AMS CLASSIFICATIONS: 15B05, 15A09 I. INTRODUCTION The concept of k-symmetric matrices and was introduced in [1], [2] and [3] Some properties of symmetric matrices given in [5],[6],[7].In this paper, our intention is to define k- Centrosymmetric matrix, k-skew Centrosymmetric matrix and also we discussed some results on Centrosymmetric matrices. II. PRELIMINARIES AND NOTATIONS C is centrosymmetric matrix,c T is called Transpose of C.Let k be a fixed product of disjoint transposition in Sn and K be the permutation matrix associated with K.Clearly K satisfies the following properties. K 2 = I, K T = K.

2 100 Dr. N.Elumalai and Mrs. B. Arthi III. DEFINITIONS AND THEOREMS DEFINITION:1 A Square matrix A = [aij ] nxn is said to be symmetric if A = A T (ie) aij = aji i, j DEFINITION:2 A Square matrix which is symmetric about the centre of its array of elements is called centrosymmetric thus C = [aij ] nxn centrosymmetric if aij = an-i+1,n-j+1. DEFINITION: 3 A centrosymmetric matrix C R n xn is called k-centosymmetric matrix if C = K C T K. THEOREM: 1 Let C R n x n is k-centrosymmetric matrix then C T = K C K. Proof: K C K = K C T K where C = C T = C T K K where K C T = C T K = C T K 2 = C T THEOREM:2 If C1 and C2 are k-centrosymmetric matrices then C1C2 is also k-cetrosymmetric matrix Let C1, and C2 are k-centrosymmetric matrices if C1 = K C1 T K and C2 = K C2 T K. Since C1 T and C2 T are also k-centrosymmetric matrices then C1 T = K C1K and C2 T = K C2 K. To prove C1 C2 is k-centrosymmetric matrix We will show that C1 C2= K (C1 C2) T K Now K (C1 C2) T K = K C2 T C1 T K = K [(K C2 K)(K C1 K)]K where C1 T = K C1 K and C2 T = K C2 K.

3 Properties of k - CentroSymmetric and k Skew CentroSymmetric Matrices 101 THEOREM :3 = K 2 C2 K 2 C1 K 2 =C2 C1 = C1 C2 where C2 C1 = C1 C2 If C is k-centro symmetric matrices and K is the permutation matrix, k = (1 2) then KC is also k-centro symmetric matrix. A matrix C R n x n is said to be k-centrosymmetric matrix if C = K C T K Since C T is also k-centrosymmetric matrices then C T = K C K To prove K C is K- centrosymmetric matrix We will show that KC= K (KC) T K Now K (KC) T K = K ( C T K T ) K where ( KC ) T = C T K T THEOREM: 4 = KC T where K T K = I = KC where KC T = KC If C R n xn is k-centrosymmetric matrix then C C T is also k-centrosymmetric matrix A matrix C R n xn is said to be k-centrosymmetric matrix if C = K C T K Since C T is also k-centrosymmetric matrices then C T = K CK We will show that, C C T = K (C C T ) T K For that, THEOREM:5 K (C C T ) T K = K [ (C T ) T C T ] K where ( KC ) T = C T K T = K (C C T ) K where (C T ) T = C = (C C T ) KK where KC = CK = (C C T ) K 2 where KK=K 2 = (C C T ) If C R n xn is k-centrosymmetric matrix then C ± C T is also k-centrosymmetric matrix

4 102 Dr. N.Elumalai and Mrs. B. Arthi A matrix C R n xn is said to be k-centrosymmetric matrix if C = K C T K Since C T is also k-centrosymmetric matrices then C T = K CK We will show that, C +C T = K (C +C T ) T K For that, K (C +C T ) T K = K [ (C T ) T +C T ] K where ( C 1 +C 2 ) T T = ( C 1 +C T 2 ) = K (C +C T ) K where (C T ) T = C = (C + C T ) KK where KC = CK = (C + C T ) K 2 = (C +C T ) THEOREM:6 If C1 and C2 are k-centrosymmetric matrices then C 1 ± C2 is also k- cetrosymmetric matrix Let C1, and C2 are k-centrosymmetric matrices if C1 = K C1 T K and C2 = K C2 T K. Since C1 T and C2 T are also k-centrosymmetric matrices then C1 T = K C1K and C2 T = K C2 K. To prove C1 + C2 is k-centrosymmetric matrix We will show that C1 + C2= K (C1 + C2) T K Now K (C1 + C2) T K = K(C1 T + C2 T ) K = K C1 K + K C2 K where C1 T = K C1 K and C2 T = K C2 K. = C1 + C2 RESULT: Let C1 and C2 holds are k-centrosymmetric matrices for the following conditions are [i] C 1 C 2 = C 2 C 1 [ii] (C T 1 C 2 C 1 ) and (C T 2 C 1 C 2 ) are also k- centrosymmetric matrices. [iii] Adj C 1 also k-centro symmetric matrix. [iv] C 1 (Adj C 1 ) is also k-centrosymmetric matrix.

5 Properties of k - CentroSymmetric and k Skew CentroSymmetric Matrices 103 EXAMPLE: 1 Let C 1 =( ) and C 2 =( ) ; K = ( ) (i) K (C 1 C 2 ) T K =( ) ( ) ( ) ( ) = ( ) = C 1 C 2 (ii) K (C T 1 C 2 C 1 ) T K ==( ) ( ) ( ) ( ) ( ) = ( ) = C 1 T C 2 C 1 DEFINITION:4 A Square matrix A = [aij ] nxn is said to be skewsymmetric matrix if A = - A T (ie) aij = - aji i, j DEFINITION:5 A Square matrix C = [aij ] nxn is called skew centrosymmetric matrix if C = - C T DEFINITION: 6 A skew centrosymmetric matrix C R n xn is called k-skew centosymmetric matrix if K C K = -C T. THEOREM: 7 Let C R n x n is k- skew centrosymmetric matrix then K C T K. = - C Proof: THEOREM:8 K C T K = K (-C ) K = where C T = -C = - C K K = -C If C1 and C2 are k- skew centrosymmetric matrices then C1C2 is also k- skew cetrosymmetric matrix

6 104 Dr. N.Elumalai and Mrs. B. Arthi Let C1, and C2 are k-skew centrosymmetric matrices if K C1 T K = - C1 and K C2 T K = -C2. Since C1 T and C2 T are also k- skew centrosymmetric matrices then K C1K = - C1 T and K C2 K = - C2 T. To prove C1 C2 is k- skew centrosymmetric matrix We will show that C1 C2= K (C1 C2) T K Now K (C1 C2) T K = K C2 T C1 T K = K [( -K C2 K)( -K C1 K)]K where K C1 K = - C1 T and K C2 K == - C2 T. = K 2 C2 K 2 C1 K 2 =C2 C1 where K 2 = I = C1 C2 where C2 C1 = C1 C2 THEOREM :9 If C is k-skew centrosymmetric matrix and K is the permutation matrix, k = (1 2) then - KC is also k- skew centro symmetric matrix. A matrix C R n x n is said to be k- skew centrosymmetric matrix if K C T K = -C Since C T is also k-skew centrosymmetric matrices then K C K = - C T To prove - K C is K- skew centrosymmetric matrix We will show that -KC= K (KC) T K Now K (KC) T K = K ( C T K T ) K where ( KC ) T = C T K T = KC T where K T K = I = - KC where KC T = - KC THEOREM: 10 If C R n xn is k-skew centrosymmetric matrix then C C T is also k- skew centrosymmetric matrix A matrix C R n xn is said to be k-skew centrosymmetric matrix if K C T K = -C

7 Properties of k - CentroSymmetric and k Skew CentroSymmetric Matrices 105 Since C T is also k- skew centrosymmetric matrices then K CK = - C T We will show that, C C T = K (C C T ) T K For that, RESULT: K (C C T ) T K = K [ (C T ) T C T ] K where ( KC ) T = C T K T = K (C C T ) K where (C T ) T = C = (C C T ) KK where KC = CK = (C C T ) K 2 where KK=K 2 = (C C T ) 1. If C R n xn is k-skew centrosymmetric matrix then C C T is also k- skew centrosymmetric matrix. 2. Let C1 and C2 are k- skewcentrosymmetric matrices for the following conditions are holds [i] C 1 C 2 = C 2 C 1 [ii] (C 1 T C 2 C 1 ) and (C 2 T C 1 C 2 ) are also k- skew centrosymmetric matrices [iii] Adj C 1 also k- skew centro symmetric matrix [iv] C 1 (Adj C 1 ) is also k- skew centrosymmetric matrix. REFERENCES [1] Ann Lec. Secondary symmetric and skew symmetric secondary orthogonal matrices; (i) Period, Math Hungary, 7, 63-70(1976). [2] A. Cantoni and P. Butler, Eigenvalues and eigenvectors of symmetric centrosymmetric matrices, Linear Algebra Appl. 13 (1976), [3] James R. Weaver, Centrosymmetric (cross-symmetric) matrices, their basic properties, eigenvalues, and eigenvectors, Amer. Math. Monthly 92 (1985), [4] Gunasekaran.K, Mohana.N, k-symmetric Double stochastic, s-symmetric Double stochastic, s-k-symmetric Double stochastic Matrices International Journal of Engineering Science Invention, Vol 3,Issue 8,(2014). [5] Hazewinkel, Michiel, ed. (2001), "Symmetric matrix", Encyclopedia of Mathematics, Springer, ISBN [6] Krishnamoorthy.S, Gunasekaran.K, Mohana.N, Characterization and theorems on doubly stochastic matrices Antartica Journal of Mathematics, 11(5)(2014).

8 106 Dr. N.Elumalai and Mrs. B. Arthi [7] Elumalai.N,Rajesh kannan.k k - Symmetric Circulant, s - Symmetric Circulant and s k Symmetric Circulant Matrices Journal of ultra scientist of physical sciences, Vol.28 (6), (2016 ).

Equivalent Conditions on Conjugate Unitary Matrices

Equivalent Conditions on Conjugate Unitary Matrices International Journal of Mathematics Trends and Technology (IJMTT Volume 42 Number 1- February 2017 Equivalent Conditions on Conjugate Unitary Matrices A. Govindarasu #, S.Sassicala #1 # Department of

More information

Some Properties of Conjugate Unitary Matrices

Some Properties of Conjugate Unitary Matrices Volume 119 No. 6 2018, 75-88 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu ijpam.eu Some Properties of Conjugate Unitary Matrices A.Govindarasu and S.Sassicala

More information

Secondary κ-kernel Symmetric Fuzzy Matrices

Secondary κ-kernel Symmetric Fuzzy Matrices Intern. J. Fuzzy Mathematical rchive Vol. 5, No. 2, 24, 89-94 ISSN: 232 3242 (P), 232 325 (online) Published on 2 December 24 www.researchmathsci.org International Journal of Secondary κ-ernel Symmetric

More information

ALGORITHMS FOR CENTROSYMMETRIC AND SKEW-CENTROSYMMETRIC MATRICES. Iyad T. Abu-Jeib

ALGORITHMS FOR CENTROSYMMETRIC AND SKEW-CENTROSYMMETRIC MATRICES. Iyad T. Abu-Jeib ALGORITHMS FOR CENTROSYMMETRIC AND SKEW-CENTROSYMMETRIC MATRICES Iyad T. Abu-Jeib Abstract. We present a simple algorithm that reduces the time complexity of solving the linear system Gx = b where G is

More information

On Sums of Conjugate Secondary Range k-hermitian Matrices

On Sums of Conjugate Secondary Range k-hermitian Matrices Thai Journal of Mathematics Volume 10 (2012) Number 1 : 195 202 www.math.science.cmu.ac.th/thaijournal Online ISSN 1686-0209 On Sums of Conjugate Secondary Range k-hermitian Matrices S. Krishnamoorthy,

More information

Ep Matrices and Its Weighted Generalized Inverse

Ep Matrices and Its Weighted Generalized Inverse Vol.2, Issue.5, Sep-Oct. 2012 pp-3850-3856 ISSN: 2249-6645 ABSTRACT: If A is a con s S.Krishnamoorthy 1 and B.K.N.MuthugobaI 2 Research Scholar Ramanujan Research Centre, Department of Mathematics, Govt.

More information

On Pseudo SCHUR Complements in an EP Matrix

On Pseudo SCHUR Complements in an EP Matrix International Journal of Scientific Innovative Mathematical Research (IJSIMR) Volume, Issue, February 15, PP 79-89 ISSN 47-7X (Print) & ISSN 47-4 (Online) wwwarcjournalsorg On Pseudo SCHUR Complements

More information

Magic Squares Indeed!

Magic Squares Indeed! Magic Squares Indeed! Arthur T. Benjamin and Kan Yasuda 1 Introduction Behold the remarkable property of the magic square: 6 1 8 7 5 3 2 9 4 618 2 + 753 2 + 294 2 = 816 2 + 357 2 + 492 2 (rows) 672 2 +

More information

Review of Linear Algebra

Review of Linear Algebra Review of Linear Algebra Definitions An m n (read "m by n") matrix, is a rectangular array of entries, where m is the number of rows and n the number of columns. 2 Definitions (Con t) A is square if m=

More information

Linear Algebra Practice Problems

Linear Algebra Practice Problems Math 7, Professor Ramras Linear Algebra Practice Problems () Consider the following system of linear equations in the variables x, y, and z, in which the constants a and b are real numbers. x y + z = a

More information

A SIMPLIFIED FORM FOR NEARLY REDUCIBLE AND NEARLY DECOMPOSABLE MATRICES D. J. HARTFIEL

A SIMPLIFIED FORM FOR NEARLY REDUCIBLE AND NEARLY DECOMPOSABLE MATRICES D. J. HARTFIEL A SIMPLIFIED FORM FOR NEARLY REDUCIBLE AND NEARLY DECOMPOSABLE MATRICES D. J. HARTFIEL Introduction and definitions. Nearly reducible and nearly decomposable matrices have been discussed in [4], [5], and

More information

Math 2J Lecture 16-11/02/12

Math 2J Lecture 16-11/02/12 Math 2J Lecture 16-11/02/12 William Holmes Markov Chain Recap The population of a town is 100000. Each person is either independent, democrat, or republican. In any given year, each person can choose to

More information

Math 360 Linear Algebra Fall Class Notes. a a a a a a. a a a

Math 360 Linear Algebra Fall Class Notes. a a a a a a. a a a Math 360 Linear Algebra Fall 2008 9-10-08 Class Notes Matrices As we have already seen, a matrix is a rectangular array of numbers. If a matrix A has m columns and n rows, we say that its dimensions are

More information

Range Symmetric Matrices in Indefinite Inner Product Space

Range Symmetric Matrices in Indefinite Inner Product Space Intern. J. Fuzzy Mathematical Archive Vol. 5, No. 2, 2014, 49-56 ISSN: 2320 3242 (P), 2320 3250 (online) Published on 20 December 2014 www.researchmathsci.org International Journal of Range Symmetric Matrices

More information

Schur Complement of con-s-k-ep Matrices

Schur Complement of con-s-k-ep Matrices Advances in Linear Algebra & Matrix heory - http://dx.doi.org/.436/alamt.. Published Online March (http://www.scirp.org/journal/alamt) Schur Complement of con-s-k-ep Matrices Bagyalakshmi Karuna Nithi

More information

Example Linear Algebra Competency Test

Example Linear Algebra Competency Test Example Linear Algebra Competency Test The 4 questions below are a combination of True or False, multiple choice, fill in the blank, and computations involving matrices and vectors. In the latter case,

More information

A ROLE FOR DOUBLY STOCHASTIC MATRICES IN GRAPH THEORY

A ROLE FOR DOUBLY STOCHASTIC MATRICES IN GRAPH THEORY proceedings of the american mathematical society Volume 36, No. 2, December 1972 A ROLE FOR DOUBLY STOCHASTIC MATRICES IN GRAPH THEORY D. J. HARTFIEL AND J. W. SPELLMANN Abstract. This paper represents

More information

Image Registration Lecture 2: Vectors and Matrices

Image Registration Lecture 2: Vectors and Matrices Image Registration Lecture 2: Vectors and Matrices Prof. Charlene Tsai Lecture Overview Vectors Matrices Basics Orthogonal matrices Singular Value Decomposition (SVD) 2 1 Preliminary Comments Some of this

More information

Generalized Principal Pivot Transform

Generalized Principal Pivot Transform Generalized Principal Pivot Transform M. Rajesh Kannan and R. B. Bapat Indian Statistical Institute New Delhi, 110016, India Abstract The generalized principal pivot transform is a generalization of the

More information

ENGI 9420 Lecture Notes 2 - Matrix Algebra Page Matrix operations can render the solution of a linear system much more efficient.

ENGI 9420 Lecture Notes 2 - Matrix Algebra Page Matrix operations can render the solution of a linear system much more efficient. ENGI 940 Lecture Notes - Matrix Algebra Page.0. Matrix Algebra A linear system of m equations in n unknowns, a x + a x + + a x b (where the a ij and i n n a x + a x + + a x b n n a x + a x + + a x b m

More information

Convexity of the Joint Numerical Range

Convexity of the Joint Numerical Range Convexity of the Joint Numerical Range Chi-Kwong Li and Yiu-Tung Poon October 26, 2004 Dedicated to Professor Yik-Hoi Au-Yeung on the occasion of his retirement. Abstract Let A = (A 1,..., A m ) be an

More information

Research Article k-kernel Symmetric Matrices

Research Article k-kernel Symmetric Matrices Hindawi Publishing Corporation International Journal of Mathematics and Mathematical Sciences Volume 2009, Article ID 926217, 8 pages doi:10.1155/2009/926217 Research Article k-kernel Symmetric Matrices

More information

On Schur Complement in k-kernel Symmetric Matrices

On Schur Complement in k-kernel Symmetric Matrices Int. Journal of Math. Analysis, Vol. 4, 2010, no. 7, 331-339 On Schur Complement in k-kernel Symmetric Matrices A. R. Meenakshi and D. Jaya Shree 1 Department of Mathematics Karpagam college of Engineering

More information

Constructing and (some) classification of integer matrices with integer eigenvalues

Constructing and (some) classification of integer matrices with integer eigenvalues Constructing and (some) classification of integer matrices with integer eigenvalues Chris Towse* and Eric Campbell Scripps College Pomona College January 6, 2017 The question An example Solve a linear

More information

Lecture 15 Review of Matrix Theory III. Dr. Radhakant Padhi Asst. Professor Dept. of Aerospace Engineering Indian Institute of Science - Bangalore

Lecture 15 Review of Matrix Theory III. Dr. Radhakant Padhi Asst. Professor Dept. of Aerospace Engineering Indian Institute of Science - Bangalore Lecture 15 Review of Matrix Theory III Dr. Radhakant Padhi Asst. Professor Dept. of Aerospace Engineering Indian Institute of Science - Bangalore Matrix An m n matrix is a rectangular or square array of

More information

Phys 201. Matrices and Determinants

Phys 201. Matrices and Determinants Phys 201 Matrices and Determinants 1 1.1 Matrices 1.2 Operations of matrices 1.3 Types of matrices 1.4 Properties of matrices 1.5 Determinants 1.6 Inverse of a 3 3 matrix 2 1.1 Matrices A 2 3 7 =! " 1

More information

3 (Maths) Linear Algebra

3 (Maths) Linear Algebra 3 (Maths) Linear Algebra References: Simon and Blume, chapters 6 to 11, 16 and 23; Pemberton and Rau, chapters 11 to 13 and 25; Sundaram, sections 1.3 and 1.5. The methods and concepts of linear algebra

More information

arxiv: v5 [math.fa] 2 May 2013

arxiv: v5 [math.fa] 2 May 2013 COMPUTATION OF ANTIEIGENVALUES OF BOUNDED LINEAR OPERATORS VIA CENTRE OF MASS arxiv:1007.4368v5 [math.fa] 2 May 20 KALLOL PAUL, GOPAL DAS AND LOKENATH DEBNATH Abstract. We introduce the concept of θ-antieigenvalue

More information

Study Notes on Matrices & Determinants for GATE 2017

Study Notes on Matrices & Determinants for GATE 2017 Study Notes on Matrices & Determinants for GATE 2017 Matrices and Determinates are undoubtedly one of the most scoring and high yielding topics in GATE. At least 3-4 questions are always anticipated from

More information

On the solvability of an equation involving the Smarandache function and Euler function

On the solvability of an equation involving the Smarandache function and Euler function Scientia Magna Vol. 008), No., 9-33 On the solvability of an equation involving the Smarandache function and Euler function Weiguo Duan and Yanrong Xue Department of Mathematics, Northwest University,

More information

On Almost Supra N-continuous Function

On Almost Supra N-continuous Function International Journal of Scientific and Innovative Mathematical Research (IJSIMR) Volume 3, Issue 7, July 2015, PP 20-25 ISSN 2347-307X (Print) & ISSN 2347-3142 (Online) www.arcjournals.org On Almost Supra

More information

The Solvability Conditions for the Inverse Eigenvalue Problem of Hermitian and Generalized Skew-Hamiltonian Matrices and Its Approximation

The Solvability Conditions for the Inverse Eigenvalue Problem of Hermitian and Generalized Skew-Hamiltonian Matrices and Its Approximation The Solvability Conditions for the Inverse Eigenvalue Problem of Hermitian and Generalized Skew-Hamiltonian Matrices and Its Approximation Zheng-jian Bai Abstract In this paper, we first consider the inverse

More information

Inequalities For Singular Values And Traces Of Quaternion Hermitian Matrices

Inequalities For Singular Values And Traces Of Quaternion Hermitian Matrices Inequalities For Singular Values And Traces Of Quaternion Hermitian Matrices K. Gunasekaran M. Rahamathunisha Ramanujan Research Centre, PG and Research Department of Mathematics, Government Arts College

More information

arxiv: v3 [math.ra] 22 Aug 2014

arxiv: v3 [math.ra] 22 Aug 2014 arxiv:1407.0331v3 [math.ra] 22 Aug 2014 Positivity of Partitioned Hermitian Matrices with Unitarily Invariant Norms Abstract Chi-Kwong Li a, Fuzhen Zhang b a Department of Mathematics, College of William

More information

CENTROSYMMETRIC MATRICES: PROPERTIES AND AN ALTERNATIVE APPROACH

CENTROSYMMETRIC MATRICES: PROPERTIES AND AN ALTERNATIVE APPROACH CANADIAN APPLIED MATHEMATICS QUARTERLY Volume 10 Number 4 Winter 2002 CENTROSYMMETRIC MATRICES: PROPERTIES AND AN ALTERNATIVE APPROACH IYAD T. ABU-JEIB ABSTRACT. We present a simple approach to deriving

More information

A Characterization of Distance-Regular Graphs with Diameter Three

A Characterization of Distance-Regular Graphs with Diameter Three Journal of Algebraic Combinatorics 6 (1997), 299 303 c 1997 Kluwer Academic Publishers. Manufactured in The Netherlands. A Characterization of Distance-Regular Graphs with Diameter Three EDWIN R. VAN DAM

More information

PAijpam.eu ON THE BOUNDS FOR THE NORMS OF R-CIRCULANT MATRICES WITH THE JACOBSTHAL AND JACOBSTHAL LUCAS NUMBERS Ş. Uygun 1, S.

PAijpam.eu ON THE BOUNDS FOR THE NORMS OF R-CIRCULANT MATRICES WITH THE JACOBSTHAL AND JACOBSTHAL LUCAS NUMBERS Ş. Uygun 1, S. International Journal of Pure and Applied Mathematics Volume 11 No 1 017, 3-10 ISSN: 1311-8080 (printed version); ISSN: 1314-335 (on-line version) url: http://wwwijpameu doi: 10173/ijpamv11i17 PAijpameu

More information

Spring 2019 Exam 2 3/27/19 Time Limit: / Problem Points Score. Total: 280

Spring 2019 Exam 2 3/27/19 Time Limit: / Problem Points Score. Total: 280 Math 307 Spring 2019 Exam 2 3/27/19 Time Limit: / Name (Print): Problem Points Score 1 15 2 20 3 35 4 30 5 10 6 20 7 20 8 20 9 20 10 20 11 10 12 10 13 10 14 10 15 10 16 10 17 10 Total: 280 Math 307 Exam

More information

frg Connectedness in Fine- Topological Spaces

frg Connectedness in Fine- Topological Spaces Global Journal of Pure and Applied Mathematics. ISSN 0973-1768 Volume 13, Number 8 (2017), pp. 4313-4321 Research India Publications http://www.ripublication.com frg Connectedness in Fine- Topological

More information

In insight into QAC2 (1) : Dynkin diagrams and properties of roots

In insight into QAC2 (1) : Dynkin diagrams and properties of roots International Research Journal of Engineering and Technology (IRJET) e-issn: 395-0056 Volume: 03 Issue: 0 Jan-06 www.iret.net p-issn: 395-007 In insight into QAC () : Dynkin diagrams and properties of

More information

Inverse Eigenvalue Problems for Checkerboard Toeplitz Matrices

Inverse Eigenvalue Problems for Checkerboard Toeplitz Matrices Inverse Eigenvalue Problems for Checkerboard Toeplitz Matrices T. H. Jones 1 and N. B. Willms 1 1 Department of Mathematics, Bishop s University. Sherbrooke, Québec, Canada, J1M 1Z7. E-mail: tjones@ubishops.ca,

More information

AN INVERSE EIGENVALUE PROBLEM AND AN ASSOCIATED APPROXIMATION PROBLEM FOR GENERALIZED K-CENTROHERMITIAN MATRICES

AN INVERSE EIGENVALUE PROBLEM AND AN ASSOCIATED APPROXIMATION PROBLEM FOR GENERALIZED K-CENTROHERMITIAN MATRICES AN INVERSE EIGENVALUE PROBLEM AND AN ASSOCIATED APPROXIMATION PROBLEM FOR GENERALIZED K-CENTROHERMITIAN MATRICES ZHONGYUN LIU AND HEIKE FAßBENDER Abstract: A partially described inverse eigenvalue problem

More information

Spectrum (functional analysis) - Wikipedia, the free encyclopedia

Spectrum (functional analysis) - Wikipedia, the free encyclopedia 1 of 6 18/03/2013 19:45 Spectrum (functional analysis) From Wikipedia, the free encyclopedia In functional analysis, the concept of the spectrum of a bounded operator is a generalisation of the concept

More information

POSITIVE MAP AS DIFFERENCE OF TWO COMPLETELY POSITIVE OR SUPER-POSITIVE MAPS

POSITIVE MAP AS DIFFERENCE OF TWO COMPLETELY POSITIVE OR SUPER-POSITIVE MAPS Adv. Oper. Theory 3 (2018), no. 1, 53 60 http://doi.org/10.22034/aot.1702-1129 ISSN: 2538-225X (electronic) http://aot-math.org POSITIVE MAP AS DIFFERENCE OF TWO COMPLETELY POSITIVE OR SUPER-POSITIVE MAPS

More information

MATH 23a, FALL 2002 THEORETICAL LINEAR ALGEBRA AND MULTIVARIABLE CALCULUS Solutions to Final Exam (in-class portion) January 22, 2003

MATH 23a, FALL 2002 THEORETICAL LINEAR ALGEBRA AND MULTIVARIABLE CALCULUS Solutions to Final Exam (in-class portion) January 22, 2003 MATH 23a, FALL 2002 THEORETICAL LINEAR ALGEBRA AND MULTIVARIABLE CALCULUS Solutions to Final Exam (in-class portion) January 22, 2003 1. True or False (28 points, 2 each) T or F If V is a vector space

More information

Prepared by: M. S. KumarSwamy, TGT(Maths) Page

Prepared by: M. S. KumarSwamy, TGT(Maths) Page Prepared by: M. S. KumarSwamy, TGT(Maths) Page - 50 - CHAPTER 3: MATRICES QUICK REVISION (Important Concepts & Formulae) MARKS WEIGHTAGE 03 marks Matrix A matrix is an ordered rectangular array of numbers

More information

Fundamentals of Engineering Analysis (650163)

Fundamentals of Engineering Analysis (650163) Philadelphia University Faculty of Engineering Communications and Electronics Engineering Fundamentals of Engineering Analysis (6563) Part Dr. Omar R Daoud Matrices: Introduction DEFINITION A matrix is

More information

Construction of some new families of nested orthogonal arrays

Construction of some new families of nested orthogonal arrays isid/ms/2017/01 April 7, 2017 http://www.isid.ac.in/ statmath/index.php?module=preprint Construction of some new families of nested orthogonal arrays Tian-fang Zhang, Guobin Wu and Aloke Dey Indian Statistical

More information

10: Representation of point group part-1 matrix algebra CHEMISTRY. PAPER No.13 Applications of group Theory

10: Representation of point group part-1 matrix algebra CHEMISTRY. PAPER No.13 Applications of group Theory 1 Subject Chemistry Paper No and Title Module No and Title Module Tag Paper No 13: Applications of Group Theory CHE_P13_M10 2 TABLE OF CONTENTS 1. Learning outcomes 2. Introduction 3. Definition of a matrix

More information

Block Representation and Spectral Properties of Constant Sum Matrices

Block Representation and Spectral Properties of Constant Sum Matrices Electronic Journal of Linear Algebra Volume 34 Volume 34 (2018 Article 13 2018 Block Representation and Spectral Properties of Constant Sum Matrices Sally L. Hill School of Mathematics Cardiff University,

More information

BOUNDS FOR LAPLACIAN SPECTRAL RADIUS OF THE COMPLETE BIPARTITE GRAPH

BOUNDS FOR LAPLACIAN SPECTRAL RADIUS OF THE COMPLETE BIPARTITE GRAPH Volume 115 No. 9 017, 343-351 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu ijpam.eu BOUNDS FOR LAPLACIAN SPECTRAL RADIUS OF THE COMPLETE BIPARTITE GRAPH

More information

Applied Linear Algebra in Geoscience Using MATLAB

Applied Linear Algebra in Geoscience Using MATLAB Applied Linear Algebra in Geoscience Using MATLAB Contents Getting Started Creating Arrays Mathematical Operations with Arrays Using Script Files and Managing Data Two-Dimensional Plots Programming in

More information

Bulletin of the Iranian Mathematical Society

Bulletin of the Iranian Mathematical Society ISSN: 7-6X (Print ISSN: 735-855 (Online Special Issue of the ulletin of the Iranian Mathematical Society in Honor of Professor Heydar Radjavi s 8th irthday Vol. 4 (5, No. 7, pp. 85 94. Title: Submajorization

More information

18.02 Multivariable Calculus Fall 2007

18.02 Multivariable Calculus Fall 2007 MIT OpenCourseWare http://ocw.mit.edu 18.02 Multivariable Calculus Fall 2007 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. M. Matrices and Linear Algebra

More information

ABSTRACT. closed sets, fuzzy locally regular closed sets, and fuzzy locally G δ. continuous functions

ABSTRACT. closed sets, fuzzy locally regular closed sets, and fuzzy locally G δ. continuous functions American J. of Mathematics and Sciences Vol., No -,(January 204) Copyright Mind Reader Publications ISSN No: 2250-02 A STUDY ON FUZZY LOCALLY G δ Dr. B.AMUDHAMBIGAI Assistant Professor of Mathematics Department

More information

Clarkson Inequalities With Several Operators

Clarkson Inequalities With Several Operators isid/ms/2003/23 August 14, 2003 http://www.isid.ac.in/ statmath/eprints Clarkson Inequalities With Several Operators Rajendra Bhatia Fuad Kittaneh Indian Statistical Institute, Delhi Centre 7, SJSS Marg,

More information

JUST THE MATHS UNIT NUMBER 9.8. MATRICES 8 (Characteristic properties) & (Similarity transformations) A.J.Hobson

JUST THE MATHS UNIT NUMBER 9.8. MATRICES 8 (Characteristic properties) & (Similarity transformations) A.J.Hobson JUST THE MATHS UNIT NUMBER 9.8 MATRICES 8 (Characteristic properties) & (Similarity transformations) by A.J.Hobson 9.8. Properties of eigenvalues and eigenvectors 9.8. Similar matrices 9.8.3 Exercises

More information

MATH 304 Linear Algebra Lecture 20: The Gram-Schmidt process (continued). Eigenvalues and eigenvectors.

MATH 304 Linear Algebra Lecture 20: The Gram-Schmidt process (continued). Eigenvalues and eigenvectors. MATH 304 Linear Algebra Lecture 20: The Gram-Schmidt process (continued). Eigenvalues and eigenvectors. Orthogonal sets Let V be a vector space with an inner product. Definition. Nonzero vectors v 1,v

More information

Math 3191 Applied Linear Algebra

Math 3191 Applied Linear Algebra Math 9 Applied Linear Algebra Lecture 9: Diagonalization Stephen Billups University of Colorado at Denver Math 9Applied Linear Algebra p./9 Section. Diagonalization The goal here is to develop a useful

More information

On Statistical Limit Superior, Limit Inferior and Statistical Monotonicity

On Statistical Limit Superior, Limit Inferior and Statistical Monotonicity International Journal of Fuzzy Mathematics and Systems. ISSN 2248-9940 Volume 4, Number 1 (2014), pp. 1-5 Research India Publications http://www.ripublication.com On Statistical Limit Superior, Limit Inferior

More information

Applied Linear Algebra in Geoscience Using MATLAB

Applied Linear Algebra in Geoscience Using MATLAB Applied Linear Algebra in Geoscience Using MATLAB Contents Getting Started Creating Arrays Mathematical Operations with Arrays Using Script Files and Managing Data Two-Dimensional Plots Programming in

More information

MATRICES The numbers or letters in any given matrix are called its entries or elements

MATRICES The numbers or letters in any given matrix are called its entries or elements MATRICES A matrix is defined as a rectangular array of numbers. Examples are: 1 2 4 a b 1 4 5 A : B : C 0 1 3 c b 1 6 2 2 5 8 The numbers or letters in any given matrix are called its entries or elements

More information

Mathematics for Computer Science

Mathematics for Computer Science Mathematics for Computer Science w11 Algebra of Matrices matrix definition, geometric interpretation, determinant, inverse, orthogonal, system of linear equations Summary and Figures from : Linear Algebra

More information

GENERATING TERNARY SIMPLEX CODES ARISING FROM COMPLEX HADAMARD MATRICES

GENERATING TERNARY SIMPLEX CODES ARISING FROM COMPLEX HADAMARD MATRICES GENERATING TERNARY SIMPLEX CODES ARISING FROM COMPLEX HADAMARD MATRICES ABSTRACT Chandradeo Prasad Assistant Professor, Department. Of CSE, RGIT, Koderma, (India) In this paper, simplex codes are constructed

More information

Three-Space Stability of Various Reflexivities in Locally Convex Spaces

Three-Space Stability of Various Reflexivities in Locally Convex Spaces International Journal of Mathematics Research. ISSN 0976-5840 Volume 8, Number 1 (2016), pp. 51-59 International Research PublicationHouse http://www.irphouse.com Three-Space Stability of Various Reflexivities

More information

A REVIEW AND NEW SYMMETRIC CONFERENCE MATRICES

A REVIEW AND NEW SYMMETRIC CONFERENCE MATRICES UDC 004438 A REVIEW AND NEW SYMMETRIC CONFERENCE MATRICES N A Balonin a, Dr Sc, Tech, Professor, korbendfs@mailru Jennifer Seberry b, PhD, Foundation Professor, jennifer_seberry@uoweduau a Saint-Petersburg

More information

SMARANDACHE R-MODULE AND COMMUTATIVE AND BOUNDED BE-ALGEBRAS. TBML College, Porayar , TamilNadu, India

SMARANDACHE R-MODULE AND COMMUTATIVE AND BOUNDED BE-ALGEBRAS. TBML College, Porayar , TamilNadu, India SMARANDACHE R-MODULE AND COMMUTATIVE AND BOUNDED BE-ALGEBRAS Dr. N. KANNAPPA 1 P. HIRUDAYARAJ 2 1 Head & Associate Professor, PG & Research Department of Mathematics, TBML College, Porayar - 609307, TamilNadu,

More information

REVERSALS ON SFT S. 1. Introduction and preliminaries

REVERSALS ON SFT S. 1. Introduction and preliminaries Trends in Mathematics Information Center for Mathematical Sciences Volume 7, Number 2, December, 2004, Pages 119 125 REVERSALS ON SFT S JUNGSEOB LEE Abstract. Reversals of topological dynamical systems

More information

Identifying second degree equations

Identifying second degree equations Chapter 7 Identifing second degree equations 71 The eigenvalue method In this section we appl eigenvalue methods to determine the geometrical nature of the second degree equation a 2 + 2h + b 2 + 2g +

More information

A note on the product of two skew-hamiltonian matrices

A note on the product of two skew-hamiltonian matrices A note on the product of two skew-hamiltonian matrices H. Faßbender and Kh. D. Ikramov October 13, 2007 Abstract: We show that the product C of two skew-hamiltonian matrices obeys the Stenzel conditions.

More information

Extended Binary Linear Codes from Legendre Sequences

Extended Binary Linear Codes from Legendre Sequences Extended Binary Linear Codes from Legendre Sequences T. Aaron Gulliver and Matthew G. Parker Abstract A construction based on Legendre sequences is presented for a doubly-extended binary linear code of

More information

ENERGY OF A COMPLEX FUZZY GRAPH

ENERGY OF A COMPLEX FUZZY GRAPH International J. of Math. Sci. & Engg. Appls. (IJMSEA) ISSN 0973-9424, Vol. 10 No. I (April, 2016), pp. 243-248 ENERGY OF A COMPLEX FUZZY GRAPH P. THIRUNAVUKARASU 1, R. SURESH 2 AND K. K. VISWANATHAN 3

More information

Introduction Eigen Values and Eigen Vectors An Application Matrix Calculus Optimal Portfolio. Portfolios. Christopher Ting.

Introduction Eigen Values and Eigen Vectors An Application Matrix Calculus Optimal Portfolio. Portfolios. Christopher Ting. Portfolios Christopher Ting Christopher Ting http://www.mysmu.edu/faculty/christophert/ : christopherting@smu.edu.sg : 6828 0364 : LKCSB 5036 November 4, 2016 Christopher Ting QF 101 Week 12 November 4,

More information

Linear Algebra (Review) Volker Tresp 2017

Linear Algebra (Review) Volker Tresp 2017 Linear Algebra (Review) Volker Tresp 2017 1 Vectors k is a scalar (a number) c is a column vector. Thus in two dimensions, c = ( c1 c 2 ) (Advanced: More precisely, a vector is defined in a vector space.

More information

SAMPLE OF THE STUDY MATERIAL PART OF CHAPTER 1 Introduction to Linear Algebra

SAMPLE OF THE STUDY MATERIAL PART OF CHAPTER 1 Introduction to Linear Algebra 1.1. Introduction SAMPLE OF THE STUDY MATERIAL PART OF CHAPTER 1 Introduction to Linear algebra is a specific branch of mathematics dealing with the study of vectors, vector spaces with functions that

More information

spring, math 204 (mitchell) list of theorems 1 Linear Systems Linear Transformations Matrix Algebra

spring, math 204 (mitchell) list of theorems 1 Linear Systems Linear Transformations Matrix Algebra spring, 2016. math 204 (mitchell) list of theorems 1 Linear Systems THEOREM 1.0.1 (Theorem 1.1). Uniqueness of Reduced Row-Echelon Form THEOREM 1.0.2 (Theorem 1.2). Existence and Uniqueness Theorem THEOREM

More information

Hebbian Learning II. Robert Jacobs Department of Brain & Cognitive Sciences University of Rochester. July 20, 2017

Hebbian Learning II. Robert Jacobs Department of Brain & Cognitive Sciences University of Rochester. July 20, 2017 Hebbian Learning II Robert Jacobs Department of Brain & Cognitive Sciences University of Rochester July 20, 2017 Goals Teach about one-half of an undergraduate course on Linear Algebra Understand when

More information

LINEAR SYSTEMS (11) Intensive Computation

LINEAR SYSTEMS (11) Intensive Computation LINEAR SYSTEMS () Intensive Computation 27-8 prof. Annalisa Massini Viviana Arrigoni EXACT METHODS:. GAUSSIAN ELIMINATION. 2. CHOLESKY DECOMPOSITION. ITERATIVE METHODS:. JACOBI. 2. GAUSS-SEIDEL 2 CHOLESKY

More information

Rodrigues-type formulae for Hermite and Laguerre polynomials

Rodrigues-type formulae for Hermite and Laguerre polynomials An. Şt. Univ. Ovidius Constanţa Vol. 16(2), 2008, 109 116 Rodrigues-type formulae for Hermite and Laguerre polynomials Vicenţiu RĂDULESCU Abstract In this paper we give new proofs of some elementary properties

More information

COMPOUND MATRICES AND THREE CELEBRATED THEOREMS

COMPOUND MATRICES AND THREE CELEBRATED THEOREMS COMPOUND MATRICES AND THREE CELEBRATED THEOREMS K. K. NAMBIAR ABSTRACT. Apart from the regular and adjugate compounds of a matrix, an inverse compound of a matrix is defined. Theorems of Laplace, Binet-

More information

On Construction of a Class of. Orthogonal Arrays

On Construction of a Class of. Orthogonal Arrays On Construction of a Class of Orthogonal Arrays arxiv:1210.6923v1 [cs.dm] 25 Oct 2012 by Ankit Pat under the esteemed guidance of Professor Somesh Kumar A Dissertation Submitted for the Partial Fulfillment

More information

The Nearest Doubly Stochastic Matrix to a Real Matrix with the same First Moment

The Nearest Doubly Stochastic Matrix to a Real Matrix with the same First Moment he Nearest Doubly Stochastic Matrix to a Real Matrix with the same First Moment William Glunt 1, homas L. Hayden 2 and Robert Reams 2 1 Department of Mathematics and Computer Science, Austin Peay State

More information

Gershgorin s Circle Theorem for Estimating the Eigenvalues of a Matrix with Known Error Bounds

Gershgorin s Circle Theorem for Estimating the Eigenvalues of a Matrix with Known Error Bounds Gershgorin s Circle Theorem for Estimating the Eigenvalues of a Matrix with Known Error Bounds Author: David Marquis Advisors: Professor Hans De Moor Dr. Kathryn Porter Reader: Dr. Michael Nathanson May

More information

Math 18, Linear Algebra, Lecture C00, Spring 2017 Review and Practice Problems for Final Exam

Math 18, Linear Algebra, Lecture C00, Spring 2017 Review and Practice Problems for Final Exam Math 8, Linear Algebra, Lecture C, Spring 7 Review and Practice Problems for Final Exam. The augmentedmatrix of a linear system has been transformed by row operations into 5 4 8. Determine if the system

More information

a Λ q 1. Introduction

a Λ q 1. Introduction International Journal of Pure and Applied Mathematics Volume 9 No 26, 959-97 ISSN: -88 (printed version); ISSN: -95 (on-line version) url: http://wwwijpameu doi: 272/ijpamv9i7 PAijpameu EXPLICI MOORE-PENROSE

More information

A MATRIX REPRESENTATION OF POSETS AND ITS APPLICATIONS MIN SURP RHEE. e In this fashion we can associate a finite poset X with an n X n matrix

A MATRIX REPRESENTATION OF POSETS AND ITS APPLICATIONS MIN SURP RHEE. e In this fashion we can associate a finite poset X with an n X n matrix J. Korean Math. Soc. 27(1990), No. 2, pp. 223-230 A MATRIX REPRESENTATION OF POSETS AND ITS APPLICATIONS 1. Introduction MIN SURP RHEE Let X = {Xl> X2, "', xn} be a finite partially ordered set (a poset,

More information

Matrix Algebra: Summary

Matrix Algebra: Summary May, 27 Appendix E Matrix Algebra: Summary ontents E. Vectors and Matrtices.......................... 2 E.. Notation.................................. 2 E..2 Special Types of Vectors.........................

More information

Various symmetries in matrix theory with application to modeling dynamic systems

Various symmetries in matrix theory with application to modeling dynamic systems Available online at wwwtjnsacom J Nonlinear Sci Appl 7 (2014), 63 69 Research Article Various symmetries in matrix theory with application to modeling dynamic systems Arya Aghili Ashtiani a,, Pandora Raja

More information

LINEAR SYSTEMS, MATRICES, AND VECTORS

LINEAR SYSTEMS, MATRICES, AND VECTORS ELEMENTARY LINEAR ALGEBRA WORKBOOK CREATED BY SHANNON MARTIN MYERS LINEAR SYSTEMS, MATRICES, AND VECTORS Now that I ve been teaching Linear Algebra for a few years, I thought it would be great to integrate

More information

c c c c c c c c c c a 3x3 matrix C= has a determinant determined by

c c c c c c c c c c a 3x3 matrix C= has a determinant determined by Linear Algebra Determinants and Eigenvalues Introduction: Many important geometric and algebraic properties of square matrices are associated with a single real number revealed by what s known as the determinant.

More information

A A x i x j i j (i, j) (j, i) Let. Compute the value of for and

A A x i x j i j (i, j) (j, i) Let. Compute the value of for and 7.2 - Quadratic Forms quadratic form on is a function defined on whose value at a vector in can be computed by an expression of the form, where is an symmetric matrix. The matrix R n Q R n x R n Q(x) =

More information

Finite-Horizon Statistics for Markov chains

Finite-Horizon Statistics for Markov chains Analyzing FSDT Markov chains Friday, September 30, 2011 2:03 PM Simulating FSDT Markov chains, as we have said is very straightforward, either by using probability transition matrix or stochastic update

More information

Sparse spectrally arbitrary patterns

Sparse spectrally arbitrary patterns Electronic Journal of Linear Algebra Volume 28 Volume 28: Special volume for Proceedings of Graph Theory, Matrix Theory and Interactions Conference Article 8 2015 Sparse spectrally arbitrary patterns Brydon

More information

A Study of Solving Linear System of Equations by GAUSS-JORDAN Matrix Method-An Algorithmic Approach

A Study of Solving Linear System of Equations by GAUSS-JORDAN Matrix Method-An Algorithmic Approach A Study of Solving Linear System of Equations by GAUSS-JORDAN Matrix Method-An Algorithmic Approach ABSTRACT Dr. YOGEESH N Assistant professor in Mathematics Government First Grade College BH Road, Tumkur-572102

More information

Research Article Constrained Solutions of a System of Matrix Equations

Research Article Constrained Solutions of a System of Matrix Equations Journal of Applied Mathematics Volume 2012, Article ID 471573, 19 pages doi:10.1155/2012/471573 Research Article Constrained Solutions of a System of Matrix Equations Qing-Wen Wang 1 and Juan Yu 1, 2 1

More information

On the eigenvalues of Euclidean distance matrices

On the eigenvalues of Euclidean distance matrices Volume 27, N. 3, pp. 237 250, 2008 Copyright 2008 SBMAC ISSN 00-8205 www.scielo.br/cam On the eigenvalues of Euclidean distance matrices A.Y. ALFAKIH Department of Mathematics and Statistics University

More information

GENERAL ARTICLE Realm of Matrices

GENERAL ARTICLE Realm of Matrices Realm of Matrices Exponential and Logarithm Functions Debapriya Biswas Debapriya Biswas is an Assistant Professor at the Department of Mathematics, IIT- Kharagpur, West Bengal, India. Her areas of interest

More information

The Waring rank of the Vandermonde determinant

The Waring rank of the Vandermonde determinant The Waring rank of the Vandermonde determinant Alexander Woo (U. Idaho) joint work with Zach Teitler(Boise State) SIAM Conference on Applied Algebraic Geometry, August 3, 2014 Waring rank Given a polynomial

More information

On the Amicability of Orthogonal Designs

On the Amicability of Orthogonal Designs On the Amicability of Orthogonal Designs W. H. Holzmann and H. Kharaghani Department of Mathematics & Computer Science University of Lethbridge Lethbridge, Alberta, T1K 3M4 Canada email: holzmann@uleth.ca,

More information

The Fibonacci Identities of Orthogonality

The Fibonacci Identities of Orthogonality The Fibonacci Identities of Orthogonality Kyle Hawins, Ursula Hebert-Johnson and Ben Mathes January 14, 015 Abstract In even dimensions, the orthogonal projection onto the two dimensional space of second

More information