A Note On The Exponential Of A Matrix Whose Elements Are All 1

Similar documents
TRACES OF HADAMARD AND KRONECKER PRODUCTS OF MATRICES. 1. Introduction

MATH10212 Linear Algebra B Proof Problems

Symmetric Matrices and Quadratic Forms

PAijpam.eu ON TENSOR PRODUCT DECOMPOSITION

A Hadamard-type lower bound for symmetric diagonally dominant positive matrices

A GENERALIZATION OF THE SYMMETRY BETWEEN COMPLETE AND ELEMENTARY SYMMETRIC FUNCTIONS. Mircea Merca

ON MEAN ERGODIC CONVERGENCE IN THE CALKIN ALGEBRAS

On the Jacobsthal-Lucas Numbers by Matrix Method 1

NEW FAST CONVERGENT SEQUENCES OF EULER-MASCHERONI TYPE

On the Determinants and Inverses of Skew Circulant and Skew Left Circulant Matrices with Fibonacci and Lucas Numbers

New Results for the Fibonacci Sequence Using Binet s Formula

SOME TRIBONACCI IDENTITIES

Generalization of Samuelson s inequality and location of eigenvalues

Some p-adic congruences for p q -Catalan numbers

24 MATH 101B: ALGEBRA II, PART D: REPRESENTATIONS OF GROUPS

Lecture 8: October 20, Applications of SVD: least squares approximation

1 Last time: similar and diagonalizable matrices

SOME RELATIONS ON HERMITE MATRIX POLYNOMIALS. Levent Kargin and Veli Kurt

On Nonsingularity of Saddle Point Matrices. with Vectors of Ones

Inverse Matrix. A meaning that matrix B is an inverse of matrix A.

Minimal surface area position of a convex body is not always an M-position

Matrix Algebra 2.2 THE INVERSE OF A MATRIX Pearson Education, Inc.

Iterative Techniques for Solving Ax b -(3.8). Assume that the system has a unique solution. Let x be the solution. Then x A 1 b.

Some identities involving Fibonacci, Lucas polynomials and their applications

THE TRANSFORMATION MATRIX OF CHEBYSHEV IV BERNSTEIN POLYNOMIAL BASES

Riesz-Fischer Sequences and Lower Frame Bounds

LECTURE 8: ORTHOGONALITY (CHAPTER 5 IN THE BOOK)

Some Trigonometric Identities Involving Fibonacci and Lucas Numbers

Sh. Al-sharif - R. Khalil

Stochastic Matrices in a Finite Field

A generalization of Fibonacci and Lucas matrices

Linear Regression Demystified

Iterative method for computing a Schur form of symplectic matrix

A NOTE ON PASCAL S MATRIX. Gi-Sang Cheon, Jin-Soo Kim and Haeng-Won Yoon

ON THE EXISTENCE OF E 0 -SEMIGROUPS

Course : Algebraic Combinatorics

A NEW NOTE ON LOCAL PROPERTY OF FACTORED FOURIER SERIES

Oscillation and Property B for Third Order Difference Equations with Advanced Arguments

Assignment 2 Solutions SOLUTION. ϕ 1 Â = 3 ϕ 1 4i ϕ 2. The other case can be dealt with in a similar way. { ϕ 2 Â} χ = { 4i ϕ 1 3 ϕ 2 } χ.

2.4 - Sequences and Series

CALCULATION OF FIBONACCI VECTORS

The Binet formula, sums and representations of generalized Fibonacci p-numbers

ON THE EXISTENCE OF A GROUP ORTHONORMAL BASIS. Peter Zizler (Received 20 June, 2014)

Eigenvalues and Eigenvectors

Linear chord diagrams with long chords

Efficient GMM LECTURE 12 GMM II

FINITE GROUPS WITH THREE RELATIVE COMMUTATIVITY DEGREES. Communicated by Ali Reza Ashrafi. 1. Introduction

Infinite Products Associated with Counting Blocks in Binary Strings

5.1. The Rayleigh s quotient. Definition 49. Let A = A be a self-adjoint matrix. quotient is the function. R(x) = x,ax, for x = 0.

ON THE HADAMARD PRODUCT OF BALANCING Q n B AND BALANCING Q n

#A51 INTEGERS 14 (2014) MULTI-POLY-BERNOULLI-STAR NUMBERS AND FINITE MULTIPLE ZETA-STAR VALUES

The Jordan Normal Form: A General Approach to Solving Homogeneous Linear Systems. Mike Raugh. March 20, 2005

6. Kalman filter implementation for linear algebraic equations. Karhunen-Loeve decomposition

On forward improvement iteration for stopping problems

Research Article A Note on Ergodicity of Systems with the Asymptotic Average Shadowing Property

4 The Sperner property.

CALCULATING FIBONACCI VECTORS

Improving the Localization of Eigenvalues for Complex Matrices

GAMALIEL CERDA-MORALES 1. Blanco Viel 596, Valparaíso, Chile. s: /

The log-behavior of n p(n) and n p(n)/n

COMMON FIXED POINT THEOREMS VIA w-distance

An enumeration of flags in finite vector spaces

GENERALIZED HARMONIC NUMBER IDENTITIES AND A RELATED MATRIX REPRESENTATION

Tauberian theorems for the product of Borel and Hölder summability methods

Chimica Inorganica 3

Solution of a tridiagonal operator equation

Some Tauberian theorems for weighted means of bounded double sequences

A constructive analysis of convex-valued demand correspondence for weakly uniformly rotund and monotonic preference

Bounds for the Extreme Eigenvalues Using the Trace and Determinant

On Summability Factors for N, p n k

Confidence interval for the two-parameter exponentiated Gumbel distribution based on record values

On the Inverse of a Certain Matrix Involving Binomial Coefficients

A Characterization of Compact Operators by Orthogonality

ki, X(n) lj (n) = (ϱ (n) ij ) 1 i,j d.

17. Joint distributions of extreme order statistics Lehmann 5.1; Ferguson 15

CHAPTER I: Vector Spaces

Math 155 (Lecture 3)

Enumerative & Asymptotic Combinatorics

COMPLEX FACTORIZATIONS OF THE GENERALIZED FIBONACCI SEQUENCES {q n } Sang Pyo Jun

SOME TRIGONOMETRIC IDENTITIES RELATED TO POWERS OF COSINE AND SINE FUNCTIONS

The path polynomial of a complete graph

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a

AN INTRODUCTION TO SPECTRAL GRAPH THEORY

On Some Inverse Singular Value Problems with Toeplitz-Related Structure

Characterizations Of (p, α)-convex Sequences

A new error bound for linear complementarity problems for B-matrices

Linear recurrence sequences and periodicity of multidimensional continued fractions

CMSE 820: Math. Foundations of Data Sci.

A Note on the Kolmogorov-Feller Weak Law of Large Numbers

BESSEL- AND GRÜSS-TYPE INEQUALITIES IN INNER PRODUCT MODULES

k-generalized FIBONACCI NUMBERS CLOSE TO THE FORM 2 a + 3 b + 5 c 1. Introduction

On Extracting Properties of Lie Groups from Their Lie Algebras

An Introduction to Randomized Algorithms

Xhevat Z. Krasniqi and Naim L. Braha

The r-generalized Fibonacci Numbers and Polynomial Coefficients

Regular Elements and BQ-Elements of the Semigroup (Z n, )

M A T H F A L L CORRECTION. Algebra I 1 4 / 1 0 / U N I V E R S I T Y O F T O R O N T O

Chapter 2. Periodic points of toral. automorphisms. 2.1 General introduction

Research Article Some E-J Generalized Hausdorff Matrices Not of Type M

Testing Statistical Hypotheses for Compare. Means with Vague Data

Transcription:

Applied Mathematics E-Notes, 8(208), 92-99 c ISSN 607-250 Available free at mirror sites of http://wwwmaththuedutw/ ame/ A Note O The Expoetial Of A Matrix Whose Elemets Are All Reza Farhadia Received 30 Jauary 208 Abstract Let J deote a matrix whose elemets are all It is well-kow that e J exp(j ) I + e J, where I is the idetity matrix of order The aim of our work is to establish a geeralizatio of this equality To prove the mai results, we will use the wellkow Helmert matrix Itroductio I liear algebra ad matrix theory there are may special ad importat matrices For example, the expoetial of a matrix is oe of them The expoetial of a complex square matrix of order such as A [a ij ] is defied as: e A exp(a ) z0 A z z! I + A + A2 2! + A3 3! + A4 4! +, () where I is the idetity matrix of order elemets are all It is well-kow that Let J deote a matrix whose e J I + e J (2) Sice J z z J for z, 2,, if oe puts J i equatio (), the proof of (2) is the immediate Now, i this paper it is show that exp (k) (J ) exp (exp ( exp (J ))) apply the expoetial of J i k times Clearly exp (k+) (J ) exp(exp (k) (J )) (3) Mathematics Subject Classificatios: 5A6, 5B0 Departmet of Statistics, Loresta Uiversity, Khorramabad, Ira 92

R Farhadia 93 We will prove the followig equatio: exp (k+) (J ) k ei + expk+ e where k e deotes the power tower of order k, amely () k e J, (4) e e k e e (5) k ad exp k e() deotes the iterated expoetial that is defied as: exp k e() e e e (6) Obviously, the special case of iterated expoetial is the power tower of order k, ie, k e exp k e() I subsequet sectios, the followig otatio will be used: a) R deotes the set of all real umbers b) Diag[d d 2 d ] deotes a diagoal matrix with diagoal etries d, d 2,, d c) A deotes the ivers of a matrix A d) A T deotes the traspose of a matrix A 2 Prelimiaries 2 Similarity ad Diagoalizatio I liear algebra two square matrices of order such as A ad B are said to be similar, deoted A B, if there exists a ivertible matrix T, such that T A T B (7) The matrix T is called the similarity trasformatio matrix Similar matrices have the same set of eigevalues [] Hece, it is importat if a matrix is similar to a diagoal matrix, sice the eigevalues of a diagoal matrix are its diagoal elemets I particular, we have the followig defiitio: DEFINITION ([7, page 3]) A matrix is said to be diagoalizable if it is similar to a diagoal matrix Hece, if a real square matrix A is diagoalizable, the A is similar to a diagoal matrix D Diag[d d 2 d ], ad there exists a ivertible matrix T such that T A T D or equivaletly A T D T which is the diagoalized form of A

94 A Note o the Expoetial of A Matrix The diagoalized form of a matrix is useful for some matrix calculatios Cosider the followig propositio which gives us a simple method to compute the expoetial of a diagoalizable matrix: PROPOSITION ([4, Propositio 23]) Let A is a diagoalizable matrix with A T D T, where D Diag[d d 2 d ] The e A T e D T, where e D Diag[e d e d2 e d ] Notice that ot all matrices ca be diagoalizable [] However, we kow that ay symmetric matrix is diagoalizable (see [, page 255]) Sice the matrix J that is the subject of the paper is symmetric, therefore the materials of this part, though brief, are very useful to prove the mai results i the ext sectio 22 The Helmert Matrix A Helmert matrix of order is a square matrix that was itroduced by H O Lacaster i 965 [5] The Helmert matrix of order is defied as: H 2 6 6 2 2 0 0 0 6 0 0 3 2 0 ( ) ( ) 2 2 2 ( ) ( ) ( ) ( ) Moreover, the first row of the Helmert matrix of order, has the followig form Ad the other i-th rows 2 i are formed by (8) [ ] (9) items [ i(i ) i(i ) i(i ) i items (i ) 0 0 i(i ) ] (0) i items Furthermore, we kow that the Helmert matrix is orthogoal [2]: H H T H T H I () I other words, H H T The Helmert matrix is usually used i statistics for the aalysis of variace (ANOVA), see [2, 6] Recetly, i 207, R Farhadia ad N Asadia showed that the Helmert matrix ca be used i stochastic processes [3]

R Farhadia 95 3 Mai results First, let us cosider the followig lemma: LEMMA Let H be the Helmert matrix of order ad β R The β β β βj H T β β PROOF First recall (8) (0) Hece J H T 2 6 2 6 2 2 0 2 6 2 0 0 3 2 0 0 0 By multiplyig the above equatio by β the proof is the complete THEOREM Let H be the Helmert matrix of order ad D Diag[ + β ], ( ) ( ) ( ) ( ) ( ) ( ) where, β R The H T D H I + βj (2) PROOF Startig from the left side of (2), we advace the proof: H T D

96 A Note o the Expoetial of A Matrix 2 6 2 6 2 2 0 2 6 2 0 0 3 2 0 0 0 +β 2 6 2 +β +β 0 2 6 2 2 6 +β 0 0 2 3 2 ( ) ( ) ( ) ( ) ( ) ( ) (+) (+) (+) (+) 0 0 0 +β 2 6 2 6 2 2 2 0 6 2 3 0 0 2 0 0 0 β β β H T + β β Usig Lemma i (3), we obtai ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) + β 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 β β β + β β (3) H T D H T + βj H T (4) Sice the Helmert matrix is orthogoal (see ()), by multiplyig both sides of equatio (4) by the Helmert matrix from the right, we have I I {}}{ H T D H (H T + βj H T )H H T H +βj H T H I + βj The theorem is proved

R Farhadia 97 COROLLARY Let H be the Helmert matrix of order The with similarity trasformatio matrix H J Diag[ 0 0], PROOF Usig Theorem with 0 ad β ad equatio (7), the proof is immediate COROLLARY 2 The matrix e J is a diagoalizable matrix as e J H T D H, where H deotes the Helmert matrix of order ad D Diag[e ] PROOF Recall equatio (2) of e J The the corollary is a immediate cosequece of Theorem (with ad β e ), equatio (7) ad Defiitio Now, i the ext theorem we shall prove (4) THEOREM 2 exp (k+) (J ) k ei + expk+ e () k e J PROOF By Corollary 2, we kow that e 0 0 exp(j ) H T 0 0 0 0 H (3), (7), Defiitio, Propositio, Corollary 2 ad Theorem give e e 0 0 exp (2) (J ) exp(exp(j )) H T 0 e 0 0 0 e H e ei + ee J (5) (3), (7), Defiitio, Propositio, (5) ad Theorem give e ee 0 0 exp (3) (J ) exp(exp (2) (J )) H T 0 e e 0 0 0 e e H

98 A Note o the Expoetial of A Matrix e e I + eee e e J (6) (3), (7), Defiitio, Propositio, (6) ad Theorem give e eee 0 0 exp (4) (J ) exp(exp (3) (J )) H T 0 e ee 0 0 0 e ee e ee I + eee e e ee J H I geeral, sice (3) is a recurrece relatio, repeatig the above actios (use the equatio (7), Defiitio, Propositio ad Theorem for exp (r) (J ) where r 5, 6,, k, k + ), we have ee e e exp (k+) (J ) e e e ee e I + J (7) ee Usig (5) ad (6) (with exp k+ e () e e ) i (7) we obtai The theorem is proved exp (k+) (J ) k ei + expk+ e () k e J We ca also establish a similar geeralizatio for the matrix J I fact sice J is a orthogoal projectio matrix oto the space spaed by the vector of it has a sigle eigevalue of which is the dimesio of the space o which it projects ad a eigevalue of zero with multiplicity Hece, J is a idempotet matrix Followig [, page 248], if A is a idempotet matrix, the exp(a ) I + (e )A Therefore exp ( ) J I + e J Now, let us cosider the followig theorem to geeralize the equality exp ( ) J I + e J i order to get exp ( ) (k+) J THEOREM 3 exp (k+) ( ) J k k+ e k e ei + J PROOF Sice exp ( J ) I + e J, so by Theorem, we have exp ( J ) H T D H, where D Diag[e ] ad H is the Helmert matrix of order The the proof is similar to the proof of the former theorem The theorem is proved Ackowledgmet The author wishes to thak the editor ad the aoymous referee for their helpful commets

R Farhadia 99 Refereces [] K M Abadir ad J R Magus, Matrix Algebra, Cambridge Uiversity Press, New York, 2005 [2] B R Clarke, Liear Models: The Theory ad Applicatio of Aalysis of Variace, Joh Wiley & Sos, New Jersey, 2008 [3] R Farhadia ad N Asadia, O the Helmert matrix ad applicatio i stochastic processes, It J Math Comput Sci, 2(207), 07 5 [4] B C Hall, Lie Groups, Lie Algebras, ad Represetatios, Graduate Texts i Mathematics, Spriger, Switzerlad, 205 [5] H O Lacaster, The Helmert matrices, Amer Math Mothly, 72(965), 4 2 [6] G A F Seber, A Matrix Hadbook for Statisticia, Joh Wiley & Sos, New Jersey, 2007 [7] X Zha, Matrix theory, America Mathematical Society, Providece, Rhode Islad, 203