An angle metric through the notion of Grassmann representative
|
|
- Adele Smith
- 5 years ago
- Views:
Transcription
1 Electronic Journal of Linear Algebra Volume 18 Volume 18 (009 Article An angle metric through the notion of Grassmann representative Grigoris I. Kalogeropoulos Athanasios D. Karageorgos Athanasios A. Pantelous Follow this and additional works at: Recommended Citation Kalogeropoulos, Grigoris I.; Karageorgos, Athanasios D.; and Pantelous, Athanasios A.. (009, "An angle metric through the notion of Grassmann representative", Electronic Journal of Linear Algebra, Volume 18. DOI: This Article is brought to you for free and open access by Wyoming Scholars Repository. It has been accepted for inclusion in Electronic Journal of Linear Algebra by an authorized editor of Wyoming Scholars Repository. For more information, please contact
2 AN ANGLE METRIC THROUGH THE NOTION OF GRASSMANN REPRESENTATIVE GRIGORIS I. KALOGEROPOULOS, ATHANASIOS D. KARAGEORGOS, AND ATHANASIOS A. PANTELOUS Abstract. The present paper has two main goals. Firstly, to introduce different metric topologies on the pencils (F, G associated with autonomous singular (or regular linear differential or difference systems. Secondly, to establish a new angle metric which is described by decomposable multi-vectors called Grassmann representatives (or Plücker coordinates of the corresponding subspaces. A unified framework is provided by connecting the new results to known ones, thus aiding in the deeper understanding of various structural aspects of matrix pencils in system theory. Key words. Angle metric, Grassmann manifold, Grassmann representative, Plücker coordinates, Exterior algebra. AMS subject classifications. 15A75, 15A7, 3F45, 14M Introduction - Metric Topologies on the Relevant Pencil (F, G. The perturbation analysis of rectangular (or square matrix pencils is quite challenging due to the fact that arbitrarily small perturbations of a pencil can result in eigenvalues and eigenvectors vanishing. However, there are applications in which properties of a pencil ensure the existence of certain eigenpairs. Motivated by this situation, in this paper we consider the generalized eigenvalue problem (both for rectangular and for square constant coefficient matrices associated with autonomous singular (or regular linear differential systems Fx (t =Gx(t, or, in the discrete analogue, with autonomous singular (or regular linear difference systems Fx k+1 = Gx k, where x C n is the state control vector and F, G C m n (or F, G C n n. In the last few decades the perturbation analysis of such systems has gained importance, not only in the context of matrix theory, but also in numerical linear algebra and control theory; see [6], [8], [9], [11], [13]. Received by the editors November 5, 008. Accepted for publication February 5, 009. Handling Editor: Michael J. Tsatsomeros. Department of Mathematics, University of Athens, Panepistimiopolis, GR Athens, Greece (gkaloger@math.uoa.gr, athkar@math.uoa.gr, apantelous@math.uoa.gr. 108
3 An Angle Metric Through the Notion of Grassmann Representative 109 The present paper is divided into two main parts. The first part deals with the topological aspects, and the second part with the relativistic aspects of matrix pencils. The topological results have a preliminary nature. By introducing different metric topologies on the space of pencils (F, G, a unified framework is provided aiding in the deeper understanding of perturbation aspects. In addition, our work connects the new angle metric (which in the authors view is more natural to some already known results. In particular, the angle metric is connected to the results in [8]-[11] and the notion of deflating subspaces of Stewart [6], [8], and it is shown to be equivalent to the notion of e.d. subspace. Some useful definitions and notations are required. Definition 1.1. For a given pair L =(F, G L m,n = { L : L =(F, G;F, G C m n }, we define: a the flat matrix representation of L, [L] f = [ F G ] C m n,and [ ] F b the sharp matrix representation of L, [L] s = C m n. G Definition 1.. If L =(F, G L m,n,thenl is called non-degenerate when a m n and rank [L] f = m, or b m n and rank [L] s = n. Remark 1.3. In the case of the flat description, degeneracy implies zero row minimal indices, whereas, in the case of the sharp description, degeneracy implies zero column minimal indices. Remark 1.4. If m = n, then non-degeneracy implies that L is a regular pair. By using these definitions, we can express the notion of strict equivalence as follows. Definition 1.5. Let L, L L m,n. a L and L are called strict equivalent (LE H L if and only if there exist non-singular matrices Q F n n and P F m m such that [ Q O [L ] f = P [L] f O Q ], or equivalently, [ P O [L ] s = O P ] [L] s Q.
4 110 G.I. Kalogeropoulos, A.D. Karageorgos, and A.A. Pantelous b L and L are called left strict equivalent (LE L H L if and only if there exists a non-singular matrix Q F n n such that [L ] f = P [L] f. Similarly, L and L are called right strict equivalent (LE R H L if and only if there exists a non-singular matrix Q F n n such that [L ] s =[L] s Q. For the pair L =(F, G L m,n, we can define four vector spaces as follows: X r f (L = rowspan F [L] f, X c f (L = colspan F [L] f, X r s (L = rowspan F [L] s, X c s (L = colspan F [L] s. It is clear that for every L, L L m,n with LEH LL,wehaveXf r (L =X f r (L and Xs r (L =X s r (L. Moreover, we observe that Xf r (L andx s r (L are under EH L-equivalence, but X f c (LandX s c (L are not always under EH L-equivalence. Also, for every L, L L m,n with LEH RL,weseethatXf c (L =X f c (L and Xs c (L =Xs c (L. Moreover, we observe that Xf c (L andx s c (L are under EH R-equivalence, but X f r (LandX s r (L are not always under ER H -equivalence. In the next lines, we provide a classification of the pairs considering their dimensions. Moreover, the properties of the four vector subspaces are also investigated. The following classification is a simple consequence of the definitions and observations, so far. The table below demonstrates the type of subspace and the properties. Definition 1.6. For a non-degenerate pair L =(F, G L m,n,thenormalcharacteristic space, X N (L, is defined as follows: (i when m n, X N (L = Xf r (L, which is EL H -, (ii when m>n, X N (L = Xs c (L, which is EH R-. A straightforward consequence of (i is that for a regular pencil L =(F, G L n,n, we have that X N (L =X r f (L, and X r f (L =rowspan F [L] f = colspan F [L] t f X c s (L =colspan F [L] s = rowspan F [L] t s.
5 An Angle Metric Through the Notion of Grassmann Representative 111 Furthermore, in the case where the pair is non-degenerate and m n, we have rank [L] f = m, X N (L =X r f (L =rowspan F [L] f and dim X N (L =m. Therefore, we can identify X N (L with a point of the Grassmann manifold G ( m, F n. Note that if L 1 E L H L,thenX N (L 1 represents the same point on G ( m, F n as X N (L. Dimensions X r f (L X r s (L X c f (L X c s (L m n/ n/ <m n n m/ < m n/ <m n Regular, m = n E L H - E L H - X r f (L F n, E H - E L H - E L H - E L H - Xs r (L F m, E H - Xs r (L F n, E H - Xs r (L F n, E H - Xs r (L F n, E H - Xf c (L F m, E H - Xf c (L F m, E H - E R H - Xf c (L F m, E H - Xf c (L F m, E H - X c s (L F m, E H - E R H - E R H - E R H - E R H - Invariant spaces X r f (L, X r s (L. X r f (L, X c s (L X c f (L, X c s (L X r f (L, X c s (L X r f (L, X c s (L Now, let us consider the set of regular pairs. For a pair L =(F, G } L n,n, the equivalent class EH {L L = 1 L n,n :[L 1 ] f = P [L] f,p F n n, det P 0 can be considered as a representation of a point on G ( n, F n. This point is fully identified by X N (L 1, where L 1 EH L (L. Note that a point of G ( n, F n does not represent a pair, but only the left-equivalent class of pairs. Furthermore, we shall denote by Σ L 1 the set of all distinct generalized eigenvalues (finite and infinite of the pair L = (F, G L n,n, and by Σ L the set of normalized generalized eigenvectors (Jordan vectors included defined for every λ Σ L 1. We define Q = {( Σ L 1, ΣL : L Ln,n } and consider the function f : L n,n Q: L f (L = ( Σ L 1, ΣL Q. It is obvious that f {( 1 Σ L 1, } ΣL : L Ln,n = E L H (L, which means that f is EH L-. Thus, from the eigenvalue-eigenvector point of view, it is reasonable to identify the whole class EH L (L as a point of the Grassmann manifold. The study of topological properties of ordered regular pairs is intimately related with the generalized eigenvalue problem. The analysis above demonstrates that such properties may
6 11 G.I. Kalogeropoulos, A.D. Karageorgos, and A.A. Pantelous be studied on the appropriate Grassmann manifold. In the next section, a new angle metric is introduced from the point of view of metric topology on the Grassmann manifold.. A New Angle Metric. In this session, we consider the Grassmann manifolds which are associated with elements of L m,n. In the case where m n, the manifold G ( m, F n is constructed, and on the other hand, when m n the manifolds G ( n, F m is the subject of investigation. The relationship between the two Grassmann manifolds and the pairs of L m,n is clarified by the following remark. Remark.1. (i For any V G ( m, F n,thereexistsaneh L -equivalence class from L m,n (m n, which is represented by a non-degenerate L =(F, G L m,n, such that V = rowspan [L] f. (ii For any V G ( n, F m,thereexistsaneh R-equivalence class from L m,n (m n, which is represented by a non-degenerate L =(F, G L m,n, such that V = colspan [L] s. Definition. ([8]. A real valued function d (, :G ( m, R n G ( m, R n R + o (m n is called an orthogonal metric if for every V 1, V, V 3 G ( m, R n (where V 1 = X N (L 1, V = X N (L, V 3 = X N (L 3, and L 1,L,L 3 L m,n are non-degenerate, it satisfies the following properties: (i d (X N (L 1, X N (L 0, and d (X N (L 1, X N (L = 0 if and only if L 1 EH LL, (ii d (X N (L 1, X N (L = d (X N (L, X N (L 1, (iii d (X N (L 1, X N (L d (X N (L 1, X N (L 3 + d (X N (L 3, X N (L, ( ] ] (iv d colspan [[L 1 ] tf U,colspan [[L ] tf U = d any orthogonal matrix U R m m. ( colspan [L 1 ] t f,colspan[l ] t f for Similarly, we can define the orthogonal metric on G ( n, R m.furthermore, we summarize some already known results for metrics on G ( m, R n, m n, and afterwards, we introduce the new angle metric. Theorem.3 ([1]. For any two points V L1, V L G ( m, R n such that V L1 = X r f (L 1=colspan R [L 1 ] t f and V L = X r f (L =colspan R [L ] t f, if we define X 1 = and ([L 1 ] tf 1 [L 1] f [L 1 ] t f and X = ([L ] tf 1 [L ] f [L ] t f,then J (V L1, V L = arccos [ det [ X 1 XX t X1 t ]] 1 (.1 are orthogonal metrics on G ( m, R n. d J (V L1, V L =sinj (V L1, V L (.
7 An Angle Metric Through the Notion of Grassmann Representative 113 Note that metrics (.1 and (. have been used extensively in [8]-[11], on the perturbation analysis of the generalized eigenvalue-eigenvector problem. These metrics have also been related to other metrics on the Grassmann manifold, for instance, the GAP between subspaces, sin θ (X, Y, etc.; see [8]-[11], [13]-[14]. Now, we denote L m,n /EH L as the quotient EL H-the collection of equivalence classes. It is easily derived that there is an one-to-one map ϕ : L m,n /E L H G ( m, R n such that E L H (L ϕ ( E L H (L = XN (L =X r f (L 1 = V L G ( m, R n. (.3 Considering map (.3, we can always associate an m-dimensional subspace V L of R n to a one-dimensional subspace of the vector space Λ ( m R n (see []-[5], or equivalently, a point on the Grassmann variety Ω (m, n of the projective space P v (R, ( n v = 1. This one-dimensional subspace of Λ ( m R n is described by decomposable multi-vectors called Grassmann representatives (or Plücker coordinates of m the corresponding subspace V L, which are denoted by g (V L. It is also known that if x,x Λ ( m R n are two Grassmann representatives of V L,thenx = λx where λ R\{0}. Definition.4. Let L = (F, G L m,n and V L G ( m, R n be a linear subspace of R n that corresponds to the equivalent class EH L (L. If x ( Λm R n is ( a Grassmann representative of V L and x =[x 0,x 1,...,x v ] t n, v = 1, then m we define the normal Grassmann representative of as the decomposable multi-vector which is given by x = sign(x v x x, if x v 0 sign(x i x x, if x v =0 and x i is the first non-zero component of x where sign (x i = { 1, if xi > 0 1, if x i < 0. Proposition.5. The normal Grassmann representative x of the subspace V L G ( m, R n is unique and x =1( denotes the Euclidean norm. Proof. Let x Λ m ( R n be another Grassmann representative of V L.Itisclear
8 114 G.I. Kalogeropoulos, A.D. Karageorgos, and A.A. Pantelous that x = λx for some λ R\{0}. By Definition.4, sign(x v x x = x, if x v = λx v 0 sign(x i x x, if x v = λx v =0 and x i = λx i = = x, λsign(λsign(x v λ x x, if x v 0 λsign(λsign(x i λ x x, if x v =0 and x i is the first non-zero component of x keeping in mind that λsign(λ λ =1. Thus, x is a unique Grassmann representative of the subspace V L. The property x = 1 is obvious. Definition.6 (The new angle metric. For V L1, V L the angle metric, (V L1, V L, by G ( m, R n, we define (V L1, V L = arccos x 1, x, (.4 where x 1, x are the normal Grassmann representatives of V L1, V L, respectively, and, denotes the inner product. In what it follows, we denote the set of strictly increasing sequences of l integers (1 l m chosenfrom1,,...,m; for example, Q,m = {(1,, (1, 3, (, 3,...}. ( m Clearly, the number of the sequences of Q l,m is equal to. l Furthermore, we assume that A =[a ij ] M m,n (R, where M m,n (R denotes the set of m n matrices over R. Letµ, ν be positive integers satisfying 1 µ m, 1 ν n, α =(i 1,...,i µ Q µ,m and β =(j 1,...j ν Q ν,n. Then A [α β ] M µ,ν (R denotes the submatrix of A formed by the rows i 1,i,...,i µ and the columns j 1,j,...,j ν. Finally, for 1 l min {m, n} the l-compound matrix (or l-adjugate ofa is ( ( m n the matrix whose entries are det {A [α β ]}, α Q l,m, β Q l,n, l l arranged lexicographically in α and β. ThismatrixisdenotedbyC l (A; see []-[5] for more details about this interesting matrix. Moreover, it should be stressed out that a compound matrix is in fact a vector corresponding to the Grassmann representative (or Plücker coordinates of a space. Proposition.7. The angle metric (.4 is an orthogonal metric on the Grassmann manifold G ( m, R n. Proof. It is straightforward to verify conditions (i and (ii of Definition.. Condition (iii is derived by the corresponding inequality of angles between vectors
9 An Angle Metric Through the Notion of Grassmann Representative 115 which is a consequence of the -inequality on the unit sphere. Thus, we need to prove (iv. Let V Li = colspan R [L i ] t f, i =1,, and U be a m m non-singular matrix ( with U = λ. Then C m [L i ] t f U = C m ([L i ] t f U = λc m ([L i ] t f, i =1,, and consequently, ( ([L 1 ] tf U, [L ] tf U = [L 1 ] t f, [L ] t f. Moreover, if U is an orthogonal matrix, then an orthogonal metric is obtained. and This angle metric on G ( m, R n is related to the standard metrics (.1 and (.. Theorem.8. For every V L1, V L G ( m, R n, we have that (V L1, V L =J (V L1, V L sin { (V L1, V L } = d J (V 1, V =sin{j (V 1, V }. Proof. By using the Binet-Cauchy theorem [3], we obtain that det [X 1 X t X X t 1]=C m (X 1 C m (X t C m (X C m (X t 1 = C m (X 1 C t m (X C m (X C t m (X 1. By Theorem.3, we also have C m (X i = ] 1 [C m t [L i ] f C m (L i f Cm ([L t i ] f = g (V L i g (V Li = ε x t i, where ε = ±1, i =1,. Thus, since det [ X 1 X t X X1 t ] = x t 1 x xt x 1 = { x 1, x }, it follows that ( det [ X1 X t X X t 1] 1 = x 1,x. Then arccos ( det [ X 1 XX t X1 t ] 1 = arccos x 1, x J (V L1, V L = (V L1, V L, and sin { (V L1, V L } =sin{j (V L1, V L } = d J (V L1, V L.
10 116 G.I. Kalogeropoulos, A.D. Karageorgos, and A.A. Pantelous Remark.9. When m = n, this angle metric is suitable for the perturbation analysis for the generalized eigenvalue-eigenvector problem. Acknowledgments. The authors are grateful to the anonymous referees for their insightful comments and suggestions. REFERENCES [1] C. Giannakopoulos. Frequency Assignment Problems of Linear Multivariable Problems: An Exterior Algebra and Algebraic Geometry Based Approach. PhD Thesis, City University, London, [] W. Greub. Multilinear Algebra, nd edition. Universitext, Springer-Verlag, New York- Heidelberg, [3] W.V.D. Hodge and D. Pedoe. Methods of Algebraic Geometry. Cambridge University Press, Boston, 195. [4] N. Karcanias and U. Başer. Exterior algebra and spaces of implicit systems: the Grassmann representative approach. Kybernetika (Prague, 30:1, [5] M. Marcus and H. Minc. A Survey of Matrix Theory and Matrix Inequalities. Allyn and Bacon, Boston, [6] G.W. Stewart. On the perturbation of pseudo-inverse, projections and linear least squares problems. SIAM Review, 19:634 66, [7] G.W. Stewart. Perturbation theory for rectangular matrix pencils. Linear Algebra and its Applications, 08/09:97 301, [8] G.W. Stewart and J.G. Sun. Matrix Perturbation Theory. Academic Press, Boston, [9] J.G. Sun. Invariant subspaces and generalized subspaces. I. Existence and uniqueness theorems. Mathematica Numerica Sinica (Chinese, (1:1 13, [10] J.G. Sun. Invariant subspaces and generalized subspaces. II. Perturbation theorems. Mathematica Numerica Sinica (Chinese, (:113 13, [11] J.G. Sun. Perturbation analysis for the generalized eigenvalue and the generalized singular value problem. Lecture Notes in Mathematics: Matrix Pencils, 973:1 44, [1] J.G. Sun. A note on Stewart s theorem for definite matrix pairs. Linear Algebra and its Applications, 48: , 198. [13] J.G. Sun. Perturbation of angles between linear subspaces. Journal of Computational Mathematics, 5:58 61, [14] Y. Zhang and L. Qiu. On the angular metrics between linear subspaces. Linear Algebra and its Applications, 41(1: , 007.
On cardinality of Pareto spectra
Electronic Journal of Linear Algebra Volume 22 Volume 22 (2011) Article 50 2011 On cardinality of Pareto spectra Alberto Seeger Jose Vicente-Perez Follow this and additional works at: http://repository.uwyo.edu/ela
More informationNon-trivial solutions to certain matrix equations
Electronic Journal of Linear Algebra Volume 9 Volume 9 (00) Article 4 00 Non-trivial solutions to certain matrix equations Aihua Li ali@loyno.edu Duane Randall Follow this and additional works at: http://repository.uwyo.edu/ela
More informationMatrix functions that preserve the strong Perron- Frobenius property
Electronic Journal of Linear Algebra Volume 30 Volume 30 (2015) Article 18 2015 Matrix functions that preserve the strong Perron- Frobenius property Pietro Paparella University of Washington, pietrop@uw.edu
More informationSingular Value and Norm Inequalities Associated with 2 x 2 Positive Semidefinite Block Matrices
Electronic Journal of Linear Algebra Volume 32 Volume 32 (2017) Article 8 2017 Singular Value Norm Inequalities Associated with 2 x 2 Positive Semidefinite Block Matrices Aliaa Burqan Zarqa University,
More informationOn nonnegative realization of partitioned spectra
Electronic Journal of Linear Algebra Volume Volume (0) Article 5 0 On nonnegative realization of partitioned spectra Ricardo L. Soto Oscar Rojo Cristina B. Manzaneda Follow this and additional works at:
More informationInterior points of the completely positive cone
Electronic Journal of Linear Algebra Volume 17 Volume 17 (2008) Article 5 2008 Interior points of the completely positive cone Mirjam Duer duer@mathematik.tu-darmstadt.de Georg Still Follow this and additional
More informationA method for computing quadratic Brunovsky forms
Electronic Journal of Linear Algebra Volume 13 Volume 13 (25) Article 3 25 A method for computing quadratic Brunovsky forms Wen-Long Jin wjin@uciedu Follow this and additional works at: http://repositoryuwyoedu/ela
More informationThe spectrum of the edge corona of two graphs
Electronic Journal of Linear Algebra Volume Volume (1) Article 4 1 The spectrum of the edge corona of two graphs Yaoping Hou yphou@hunnu.edu.cn Wai-Chee Shiu Follow this and additional works at: http://repository.uwyo.edu/ela
More informationNilpotent matrices and spectrally arbitrary sign patterns
Electronic Journal of Linear Algebra Volume 16 Article 21 2007 Nilpotent matrices and spectrally arbitrary sign patterns Rajesh J. Pereira rjxpereira@yahoo.com Follow this and additional works at: http://repository.uwyo.edu/ela
More informationZERO STRUCTURE ASSIGNMENT OF MATRIX PENCILS: THE CASE OF STRUCTURED ADDITIVE TRANSFORMATIONS
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 12-15, 2005 ThC05.1 ZERO STRUCTURE ASSIGNMENT OF MATRIX PENCILS: THE CASE
More informationThe 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 informationAn improved characterisation of the interior of the completely positive cone
Electronic Journal of Linear Algebra Volume 2 Volume 2 (2) Article 5 2 An improved characterisation of the interior of the completely positive cone Peter J.C. Dickinson p.j.c.dickinson@rug.nl Follow this
More informationStructured eigenvalue/eigenvector backward errors of matrix pencils arising in optimal control
Electronic Journal of Linear Algebra Volume 34 Volume 34 08) Article 39 08 Structured eigenvalue/eigenvector backward errors of matrix pencils arising in optimal control Christian Mehl Technische Universitaet
More informationPositive definiteness of tridiagonal matrices via the numerical range
Electronic Journal of Linear Algebra Volume 3 ELA Volume 3 (998) Article 9 998 Positive definiteness of tridiagonal matrices via the numerical range Mao-Ting Chien mtchien@math.math.scu.edu.tw Michael
More informationNote on the Jordan form of an irreducible eventually nonnegative matrix
Electronic Journal of Linear Algebra Volume 30 Volume 30 (2015) Article 19 2015 Note on the Jordan form of an irreducible eventually nonnegative matrix Leslie Hogben Iowa State University, hogben@aimath.org
More informationINVESTIGATING THE NUMERICAL RANGE AND Q-NUMERICAL RANGE OF NON SQUARE MATRICES. Aikaterini Aretaki, John Maroulas
Opuscula Mathematica Vol. 31 No. 3 2011 http://dx.doi.org/10.7494/opmath.2011.31.3.303 INVESTIGATING THE NUMERICAL RANGE AND Q-NUMERICAL RANGE OF NON SQUARE MATRICES Aikaterini Aretaki, John Maroulas Abstract.
More informationRecognition of hidden positive row diagonally dominant matrices
Electronic Journal of Linear Algebra Volume 10 Article 9 2003 Recognition of hidden positive row diagonally dominant matrices Walter D. Morris wmorris@gmu.edu Follow this and additional works at: http://repository.uwyo.edu/ela
More informationII. DIFFERENTIABLE MANIFOLDS. Washington Mio CENTER FOR APPLIED VISION AND IMAGING SCIENCES
II. DIFFERENTIABLE MANIFOLDS Washington Mio Anuj Srivastava and Xiuwen Liu (Illustrations by D. Badlyans) CENTER FOR APPLIED VISION AND IMAGING SCIENCES Florida State University WHY MANIFOLDS? Non-linearity
More informationA norm inequality for pairs of commuting positive semidefinite matrices
Electronic Journal of Linear Algebra Volume 30 Volume 30 (205) Article 5 205 A norm inequality for pairs of commuting positive semidefinite matrices Koenraad MR Audenaert Royal Holloway University of London,
More informationInequalities involving eigenvalues for difference of operator means
Electronic Journal of Linear Algebra Volume 7 Article 5 014 Inequalities involving eigenvalues for difference of operator means Mandeep Singh msrawla@yahoo.com Follow this and additional works at: http://repository.uwyo.edu/ela
More informationA Note on Eigenvalues of Perturbed Hermitian Matrices
A Note on Eigenvalues of Perturbed Hermitian Matrices Chi-Kwong Li Ren-Cang Li July 2004 Let ( H1 E A = E H 2 Abstract and à = ( H1 H 2 be Hermitian matrices with eigenvalues λ 1 λ k and λ 1 λ k, respectively.
More informationAnalytic roots of invertible matrix functions
Electronic Journal of Linear Algebra Volume 13 Volume 13 (2005) Article 15 2005 Analytic roots of invertible matrix functions Leiba X. Rodman lxrodm@math.wm.edu Ilya M. Spitkovsky Follow this and additional
More informationDihedral groups of automorphisms of compact Riemann surfaces of genus two
Electronic Journal of Linear Algebra Volume 26 Volume 26 (2013) Article 36 2013 Dihedral groups of automorphisms of compact Riemann surfaces of genus two Qingje Yang yangqj@ruc.edu.com Dan Yang Follow
More informationGershgorin type sets for eigenvalues of matrix polynomials
Electronic Journal of Linear Algebra Volume 34 Volume 34 (18) Article 47 18 Gershgorin type sets for eigenvalues of matrix polynomials Christina Michailidou National Technical University of Athens, xristina.michailidou@gmail.com
More informationOn EP elements, normal elements and partial isometries in rings with involution
Electronic Journal of Linear Algebra Volume 23 Volume 23 (2012 Article 39 2012 On EP elements, normal elements and partial isometries in rings with involution Weixing Chen wxchen5888@163.com Follow this
More informationNote on deleting a vertex and weak interlacing of the Laplacian spectrum
Electronic Journal of Linear Algebra Volume 16 Article 6 2007 Note on deleting a vertex and weak interlacing of the Laplacian spectrum Zvi Lotker zvilo@cse.bgu.ac.il Follow this and additional works at:
More informationThe symmetric linear matrix equation
Electronic Journal of Linear Algebra Volume 9 Volume 9 (00) Article 8 00 The symmetric linear matrix equation Andre CM Ran Martine CB Reurings mcreurin@csvunl Follow this and additional works at: http://repositoryuwyoedu/ela
More informationThe symmetric minimal rank solution of the matrix equation AX=B and the optimal approximation
Electronic Journal of Linear Algebra Volume 18 Volume 18 (2009 Article 23 2009 The symmetric minimal rank solution of the matrix equation AX=B and the optimal approximation Qing-feng Xiao qfxiao@hnu.cn
More informationLower bounds for the Estrada index
Electronic Journal of Linear Algebra Volume 23 Volume 23 (2012) Article 48 2012 Lower bounds for the Estrada index Yilun Shang shylmath@hotmail.com Follow this and additional works at: http://repository.uwyo.edu/ela
More informationOptimization Theory. A Concise Introduction. Jiongmin Yong
October 11, 017 16:5 ws-book9x6 Book Title Optimization Theory 017-08-Lecture Notes page 1 1 Optimization Theory A Concise Introduction Jiongmin Yong Optimization Theory 017-08-Lecture Notes page Optimization
More informationRETRACTED On construction of a complex finite Jacobi matrix from two spectra
Electronic Journal of Linear Algebra Volume 26 Volume 26 (203) Article 8 203 On construction of a complex finite Jacobi matrix from two spectra Gusein Sh. Guseinov guseinov@ati.edu.tr Follow this and additional
More informationA Simple Proof of Fiedler's Conjecture Concerning Orthogonal Matrices
University of Wyoming Wyoming Scholars Repository Mathematics Faculty Publications Mathematics 9-1-1997 A Simple Proof of Fiedler's Conjecture Concerning Orthogonal Matrices Bryan L. Shader University
More informationOn the Feichtinger conjecture
Electronic Journal of Linear Algebra Volume 26 Volume 26 (2013) Article 35 2013 On the Feichtinger conjecture Pasc Gavruta pgavruta@yahoo.com Follow this and additional works at: http://repository.uwyo.edu/ela
More informationOn the simplest expression of the perturbed Moore Penrose metric generalized inverse
Annals of the University of Bucharest (mathematical series) 4 (LXII) (2013), 433 446 On the simplest expression of the perturbed Moore Penrose metric generalized inverse Jianbing Cao and Yifeng Xue Communicated
More informationOn the computation of the Jordan canonical form of regular matrix polynomials
On the computation of the Jordan canonical form of regular matrix polynomials G Kalogeropoulos, P Psarrakos 2 and N Karcanias 3 Dedicated to Professor Peter Lancaster on the occasion of his 75th birthday
More informationLecture 1: Review of linear algebra
Lecture 1: Review of linear algebra Linear functions and linearization Inverse matrix, least-squares and least-norm solutions Subspaces, basis, and dimension Change of basis and similarity transformations
More informationOn the distance signless Laplacian spectral radius of graphs and digraphs
Electronic Journal of Linear Algebra Volume 3 Volume 3 (017) Article 3 017 On the distance signless Laplacian spectral radius of graphs and digraphs Dan Li Xinjiang University,Urumqi, ldxjedu@163.com Guoping
More informationA note on a conjecture for the distance Laplacian matrix
Electronic Journal of Linear Algebra Volume 31 Volume 31: (2016) Article 5 2016 A note on a conjecture for the distance Laplacian matrix Celso Marques da Silva Junior Centro Federal de Educação Tecnológica
More informationELA ON A SCHUR COMPLEMENT INEQUALITY FOR THE HADAMARD PRODUCT OF CERTAIN TOTALLY NONNEGATIVE MATRICES
ON A SCHUR COMPLEMENT INEQUALITY FOR THE HADAMARD PRODUCT OF CERTAIN TOTALLY NONNEGATIVE MATRICES ZHONGPENG YANG AND XIAOXIA FENG Abstract. Under the entrywise dominance partial ordering, T.L. Markham
More informationOn Projection of a Positive Definite Matrix on a Cone of Nonnegative Definite Toeplitz Matrices
Electronic Journal of Linear Algebra Volume 33 Volume 33: Special Issue for the International Conference on Matrix Analysis and its Applications, MAT TRIAD 2017 Article 8 2018 On Proection of a Positive
More informationThe Eigenvalue Problem: Perturbation Theory
Jim Lambers MAT 610 Summer Session 2009-10 Lecture 13 Notes These notes correspond to Sections 7.2 and 8.1 in the text. The Eigenvalue Problem: Perturbation Theory The Unsymmetric Eigenvalue Problem Just
More informationClass Meeting # 12: Kirchhoff s Formula and Minkowskian Geometry
MATH 8.52 COURSE NOTES - CLASS MEETING # 2 8.52 Introduction to PDEs, Spring 207 Professor: Jared Speck Class Meeting # 2: Kirchhoff s Formula and Minkowskian Geometry. Kirchhoff s Formula We are now ready
More informationLecture # 3 Orthogonal Matrices and Matrix Norms. We repeat the definition an orthogonal set and orthornormal set.
Lecture # 3 Orthogonal Matrices and Matrix Norms We repeat the definition an orthogonal set and orthornormal set. Definition A set of k vectors {u, u 2,..., u k }, where each u i R n, is said to be an
More informationGeneralized Schur complements of matrices and compound matrices
Electronic Journal of Linear Algebra Volume 2 Volume 2 (200 Article 3 200 Generalized Schur complements of matrices and compound matrices Jianzhou Liu Rong Huang Follow this and additional wors at: http://repository.uwyo.edu/ela
More informationA note on estimates for the spectral radius of a nonnegative matrix
Electronic Journal of Linear Algebra Volume 13 Volume 13 (2005) Article 22 2005 A note on estimates for the spectral radius of a nonnegative matrix Shi-Ming Yang Ting-Zhu Huang tingzhuhuang@126com Follow
More informationStat 159/259: Linear Algebra Notes
Stat 159/259: Linear Algebra Notes Jarrod Millman November 16, 2015 Abstract These notes assume you ve taken a semester of undergraduate linear algebra. In particular, I assume you are familiar with the
More informationRefined Inertia of Matrix Patterns
Electronic Journal of Linear Algebra Volume 32 Volume 32 (2017) Article 24 2017 Refined Inertia of Matrix Patterns Kevin N. Vander Meulen Redeemer University College, kvanderm@redeemer.ca Jonathan Earl
More informationGENERAL 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 informationMATH 423 Linear Algebra II Lecture 33: Diagonalization of normal operators.
MATH 423 Linear Algebra II Lecture 33: Diagonalization of normal operators. Adjoint operator and adjoint matrix Given a linear operator L on an inner product space V, the adjoint of L is a transformation
More informationLinear Algebra Review
January 29, 2013 Table of contents Metrics Metric Given a space X, then d : X X R + 0 and z in X if: d(x, y) = 0 is equivalent to x = y d(x, y) = d(y, x) d(x, y) d(x, z) + d(z, y) is a metric is for all
More information2. Linear algebra. matrices and vectors. linear equations. range and nullspace of matrices. function of vectors, gradient and Hessian
FE661 - Statistical Methods for Financial Engineering 2. Linear algebra Jitkomut Songsiri matrices and vectors linear equations range and nullspace of matrices function of vectors, gradient and Hessian
More informationPartial isometries and EP elements in rings with involution
Electronic Journal of Linear Algebra Volume 18 Volume 18 (2009) Article 55 2009 Partial isometries and EP elements in rings with involution Dijana Mosic dragan@pmf.ni.ac.yu Dragan S. Djordjevic Follow
More informationThe third smallest eigenvalue of the Laplacian matrix
Electronic Journal of Linear Algebra Volume 8 ELA Volume 8 (001) Article 11 001 The third smallest eigenvalue of the Laplacian matrix Sukanta Pati pati@iitg.ernet.in Follow this and additional works at:
More informationMATH 583A REVIEW SESSION #1
MATH 583A REVIEW SESSION #1 BOJAN DURICKOVIC 1. Vector Spaces Very quick review of the basic linear algebra concepts (see any linear algebra textbook): (finite dimensional) vector space (or linear space),
More informationThe least eigenvalue of the signless Laplacian of non-bipartite unicyclic graphs with k pendant vertices
Electronic Journal of Linear Algebra Volume 26 Volume 26 (2013) Article 22 2013 The least eigenvalue of the signless Laplacian of non-bipartite unicyclic graphs with k pendant vertices Ruifang Liu rfliu@zzu.edu.cn
More informationLinear Algebra: Matrix Eigenvalue Problems
CHAPTER8 Linear Algebra: Matrix Eigenvalue Problems Chapter 8 p1 A matrix eigenvalue problem considers the vector equation (1) Ax = λx. 8.0 Linear Algebra: Matrix Eigenvalue Problems Here A is a given
More informationIntroduction to Quantitative Techniques for MSc Programmes SCHOOL OF ECONOMICS, MATHEMATICS AND STATISTICS MALET STREET LONDON WC1E 7HX
Introduction to Quantitative Techniques for MSc Programmes SCHOOL OF ECONOMICS, MATHEMATICS AND STATISTICS MALET STREET LONDON WC1E 7HX September 2007 MSc Sep Intro QT 1 Who are these course for? The September
More informationA generalization of Moore-Penrose biorthogonal systems
Electronic Journal of Linear Algebra Volume 10 Article 11 2003 A generalization of Moore-Penrose biorthogonal systems Masaya Matsuura masaya@mist.i.u-tokyo.ac.jp Follow this and additional works at: http://repository.uwyo.edu/ela
More informationA new parallel polynomial division by a separable polynomial via hermite interpolation with applications, pp
Electronic Journal of Linear Algebra Volume 23 Volume 23 (2012 Article 54 2012 A new parallel polynomial division by a separable polynomial via hermite interpolation with applications, pp 770-781 Aristides
More informationSingular value inequality and graph energy change
Electronic Journal of Linear Algebra Volume 16 Article 5 007 Singular value inequality and graph energy change Jane Day so@mathsjsuedu Wasin So Follow this and additional works at: http://repositoryuwyoedu/ela
More informationLECTURE: KOBORDISMENTHEORIE, WINTER TERM 2011/12; SUMMARY AND LITERATURE
LECTURE: KOBORDISMENTHEORIE, WINTER TERM 2011/12; SUMMARY AND LITERATURE JOHANNES EBERT 1.1. October 11th. 1. Recapitulation from differential topology Definition 1.1. Let M m, N n, be two smooth manifolds
More informationThe following definition is fundamental.
1. Some Basics from Linear Algebra With these notes, I will try and clarify certain topics that I only quickly mention in class. First and foremost, I will assume that you are familiar with many basic
More informationOn the reduction of matrix polynomials to Hessenberg form
Electronic Journal of Linear Algebra Volume 3 Volume 3: (26) Article 24 26 On the reduction of matrix polynomials to Hessenberg form Thomas R. Cameron Washington State University, tcameron@math.wsu.edu
More informationCSC Linear Programming and Combinatorial Optimization Lecture 10: Semidefinite Programming
CSC2411 - Linear Programming and Combinatorial Optimization Lecture 10: Semidefinite Programming Notes taken by Mike Jamieson March 28, 2005 Summary: In this lecture, we introduce semidefinite programming
More informationA new upper bound for the eigenvalues of the continuous algebraic Riccati equation
Electronic Journal of Linear Algebra Volume 0 Volume 0 (00) Article 3 00 A new upper bound for the eigenvalues of the continuous algebraic Riccati equation Jianzhou Liu liujz@xtu.edu.cn Juan Zhang Yu Liu
More informationInertially arbitrary nonzero patterns of order 4
Electronic Journal of Linear Algebra Volume 1 Article 00 Inertially arbitrary nonzero patterns of order Michael S. Cavers Kevin N. Vander Meulen kvanderm@cs.redeemer.ca Follow this and additional works
More informationCourse Summary Math 211
Course Summary Math 211 table of contents I. Functions of several variables. II. R n. III. Derivatives. IV. Taylor s Theorem. V. Differential Geometry. VI. Applications. 1. Best affine approximations.
More informationHigher rank numerical ranges of rectangular matrix polynomials
Journal of Linear and Topological Algebra Vol. 03, No. 03, 2014, 173-184 Higher rank numerical ranges of rectangular matrix polynomials Gh. Aghamollaei a, M. Zahraei b a Department of Mathematics, Shahid
More informationUniversity of Colorado at Denver Mathematics Department Applied Linear Algebra Preliminary Exam With Solutions 16 January 2009, 10:00 am 2:00 pm
University of Colorado at Denver Mathematics Department Applied Linear Algebra Preliminary Exam With Solutions 16 January 2009, 10:00 am 2:00 pm Name: The proctor will let you read the following conditions
More informationOperator norms of words formed from positivedefinite
Electronic Journal of Linear Algebra Volume 18 Volume 18 (009) Article 009 Operator norms of words formed from positivedefinite matrices Stephen W Drury drury@mathmcgillca Follow this and additional wors
More informationOperators with numerical range in a closed halfplane
Operators with numerical range in a closed halfplane Wai-Shun Cheung 1 Department of Mathematics, University of Hong Kong, Hong Kong, P. R. China. wshun@graduate.hku.hk Chi-Kwong Li 2 Department of Mathematics,
More informationA priori bounds on the condition numbers in interior-point methods
A priori bounds on the condition numbers in interior-point methods Florian Jarre, Mathematisches Institut, Heinrich-Heine Universität Düsseldorf, Germany. Abstract Interior-point methods are known to be
More informationSection 3.9. Matrix Norm
3.9. Matrix Norm 1 Section 3.9. Matrix Norm Note. We define several matrix norms, some similar to vector norms and some reflecting how multiplication by a matrix affects the norm of a vector. We use matrix
More informatione j = Ad(f i ) 1 2a ij/a ii
A characterization of generalized Kac-Moody algebras. J. Algebra 174, 1073-1079 (1995). Richard E. Borcherds, D.P.M.M.S., 16 Mill Lane, Cambridge CB2 1SB, England. Generalized Kac-Moody algebras can be
More informationLinear Algebra Review. Vectors
Linear Algebra Review 9/4/7 Linear Algebra Review By Tim K. Marks UCSD Borrows heavily from: Jana Kosecka http://cs.gmu.edu/~kosecka/cs682.html Virginia de Sa (UCSD) Cogsci 8F Linear Algebra review Vectors
More informationMore calculations on determinant evaluations
Electronic Journal of Linear Algebra Volume 16 Article 007 More calculations on determinant evaluations A. R. Moghaddamfar moghadam@kntu.ac.ir S. M. H. Pooya S. Navid Salehy S. Nima Salehy Follow this
More informationMath Camp Lecture 4: Linear Algebra. Xiao Yu Wang. Aug 2010 MIT. Xiao Yu Wang (MIT) Math Camp /10 1 / 88
Math Camp 2010 Lecture 4: Linear Algebra Xiao Yu Wang MIT Aug 2010 Xiao Yu Wang (MIT) Math Camp 2010 08/10 1 / 88 Linear Algebra Game Plan Vector Spaces Linear Transformations and Matrices Determinant
More informationMaths for Signals and Systems Linear Algebra in Engineering
Maths for Signals and Systems Linear Algebra in Engineering Lectures 13 15, Tuesday 8 th and Friday 11 th November 016 DR TANIA STATHAKI READER (ASSOCIATE PROFFESOR) IN SIGNAL PROCESSING IMPERIAL COLLEGE
More informationSOME INEQUALITIES FOR THE EUCLIDEAN OPERATOR RADIUS OF TWO OPERATORS IN HILBERT SPACES
SOME INEQUALITIES FOR THE EUCLIDEAN OPERATOR RADIUS OF TWO OPERATORS IN HILBERT SPACES SEVER S DRAGOMIR Abstract Some sharp bounds for the Euclidean operator radius of two bounded linear operators in Hilbert
More informationarxiv: v1 [math.gr] 8 Nov 2008
SUBSPACES OF 7 7 SKEW-SYMMETRIC MATRICES RELATED TO THE GROUP G 2 arxiv:0811.1298v1 [math.gr] 8 Nov 2008 ROD GOW Abstract. Let K be a field of characteristic different from 2 and let C be an octonion algebra
More informationLECTURE 16: LIE GROUPS AND THEIR LIE ALGEBRAS. 1. Lie groups
LECTURE 16: LIE GROUPS AND THEIR LIE ALGEBRAS 1. Lie groups A Lie group is a special smooth manifold on which there is a group structure, and moreover, the two structures are compatible. Lie groups are
More informationThe singular value of A + B and αa + βb
An. Ştiinţ. Univ. Al. I. Cuza Iaşi Mat. (N.S.) Tomul LXII, 2016, f. 2, vol. 3 The singular value of A + B and αa + βb Bogdan D. Djordjević Received: 16.II.2015 / Revised: 3.IV.2015 / Accepted: 9.IV.2015
More informationTrace Class Operators and Lidskii s Theorem
Trace Class Operators and Lidskii s Theorem Tom Phelan Semester 2 2009 1 Introduction The purpose of this paper is to provide the reader with a self-contained derivation of the celebrated Lidskii Trace
More information1. General Vector Spaces
1.1. Vector space axioms. 1. General Vector Spaces Definition 1.1. Let V be a nonempty set of objects on which the operations of addition and scalar multiplication are defined. By addition we mean a rule
More informationNotes on Linear Algebra and Matrix Theory
Massimo Franceschet featuring Enrico Bozzo Scalar product The scalar product (a.k.a. dot product or inner product) of two real vectors x = (x 1,..., x n ) and y = (y 1,..., y n ) is not a vector but a
More informationNOTES ON LINEAR ODES
NOTES ON LINEAR ODES JONATHAN LUK We can now use all the discussions we had on linear algebra to study linear ODEs Most of this material appears in the textbook in 21, 22, 23, 26 As always, this is a preliminary
More informationBasic Concepts of Group Theory
Chapter 1 Basic Concepts of Group Theory The theory of groups and vector spaces has many important applications in a number of branches of modern theoretical physics. These include the formal theory of
More informationTopics in linear algebra
Chapter 6 Topics in linear algebra 6.1 Change of basis I want to remind you of one of the basic ideas in linear algebra: change of basis. Let F be a field, V and W be finite dimensional vector spaces over
More informationIr O D = D = ( ) Section 2.6 Example 1. (Bottom of page 119) dim(v ) = dim(l(v, W )) = dim(v ) dim(f ) = dim(v )
Section 3.2 Theorem 3.6. Let A be an m n matrix of rank r. Then r m, r n, and, by means of a finite number of elementary row and column operations, A can be transformed into the matrix ( ) Ir O D = 1 O
More informationc 1995 Society for Industrial and Applied Mathematics Vol. 37, No. 1, pp , March
SIAM REVIEW. c 1995 Society for Industrial and Applied Mathematics Vol. 37, No. 1, pp. 93 97, March 1995 008 A UNIFIED PROOF FOR THE CONVERGENCE OF JACOBI AND GAUSS-SEIDEL METHODS * ROBERTO BAGNARA Abstract.
More informationSymmetric Matrices and Eigendecomposition
Symmetric Matrices and Eigendecomposition Robert M. Freund January, 2014 c 2014 Massachusetts Institute of Technology. All rights reserved. 1 2 1 Symmetric Matrices and Convexity of Quadratic Functions
More information1. Select the unique answer (choice) for each problem. Write only the answer.
MATH 5 Practice Problem Set Spring 7. Select the unique answer (choice) for each problem. Write only the answer. () Determine all the values of a for which the system has infinitely many solutions: x +
More informationGeneralized Shifted Inverse Iterations on Grassmann Manifolds 1
Proceedings of the Sixteenth International Symposium on Mathematical Networks and Systems (MTNS 2004), Leuven, Belgium Generalized Shifted Inverse Iterations on Grassmann Manifolds 1 J. Jordan α, P.-A.
More informationLinear Algebra I Lecture 8
Linear Algebra I Lecture 8 Xi Chen 1 1 University of Alberta January 25, 2019 Outline 1 2 Gauss-Jordan Elimination Given a system of linear equations f 1 (x 1, x 2,..., x n ) = 0 f 2 (x 1, x 2,..., x n
More informationBicyclic digraphs with extremal skew energy
Electronic Journal of Linear Algebra Volume 3 Volume 3 (01) Article 01 Bicyclic digraphs with extremal skew energy Xiaoling Shen Yoaping Hou yphou@hunnu.edu.cn Chongyan Zhang Follow this and additional
More informationThroughout these notes we assume V, W are finite dimensional inner product spaces over C.
Math 342 - Linear Algebra II Notes Throughout these notes we assume V, W are finite dimensional inner product spaces over C 1 Upper Triangular Representation Proposition: Let T L(V ) There exists an orthonormal
More informationReview 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 informationTHE PERTURBATION BOUND FOR THE SPECTRAL RADIUS OF A NON-NEGATIVE TENSOR
THE PERTURBATION BOUND FOR THE SPECTRAL RADIUS OF A NON-NEGATIVE TENSOR WEN LI AND MICHAEL K. NG Abstract. In this paper, we study the perturbation bound for the spectral radius of an m th - order n-dimensional
More informationOn (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 informationNormalized rational semiregular graphs
Electronic Journal of Linear Algebra Volume 8 Volume 8: Special volume for Proceedings of Graph Theory, Matrix Theory and Interactions Conference Article 6 015 Normalized rational semiregular graphs Randall
More information