Open AccessBook
Matrix Mathematics: Theory, Facts, and Formulas with Application to Linear Systems Theory
Dennis S. Bernstein
- 14 Mar 2005
TL;DR: This book brings together a vast body of results on matrix theory for easy reference and immediate application with hundreds of identities, inequalities, and matrix facts stated rigorously and clearly.
read more
Abstract: "Matrix Mathematics" is a reference work for users of matrices in all branches of engineering, science, and applied mathematics. This book brings together a vast body of results on matrix theory for easy reference and immediate application. Each chapter begins with the development of relevant background theory followed by a large collection of specialized results. Hundreds of identities, inequalities, and matrix facts are stated rigorously and clearly with cross references, citations to the literature, and illuminating remarks. Twelve chapters cover all of the major topics in matrix theory: preliminaries; basic matrix properties; matrix classes and transformations; matrix polynomials and rational transfer functions; matrix decompositions; generalized inverses; Kronecker and Schur algebra; positive-semidefinite matrices; norms; functions of matrices and their derivatives; the matrix exponential and stability theory; and linear systems and control theory. A detailed list of symbols, a summary of notation and conventions, an extensive bibliography with author index, and an extensive index are provided for ease of use. The book will be useful for students at both the undergraduate and graduate levels, as well as for researchers and practitioners in all branches of engineering, science, and applied mathematics.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Weak and Strong Cross Section Dependence and Estimation of Large Panels
TL;DR: In this paper, the authors introduce the concepts of weak and strong cross-section dependence and apply them to the estimation of panel data models with an in-time number of strong and weak common factors.
Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction
TL;DR: In this article, the authors presented optimal constructions of minimum bandwidth regenerating (MBR) codes for all values of [n, k, d] and (b) minimum storage regeneration (MSR) code for all value n ≥ 2k-2, using a new product-matrix framework.
Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction
TL;DR: To the best of the knowledge, these are the first constructions of exact-regenerating codes that allow the number n of nodes in the network, to be chosen independent of the other parameters.
Large Panels with Common Factors and Spatial Correlation
M. Hashem Pesaran,Elisa Tosetti +1 more
TL;DR: In this paper, the authors consider the statistical analysis of large panel data sets where even after condi- tioning on common observed eects the cross section units might remain dependently distrib- uted.
744
Two-component spinor techniques and Feynman rules for quantum field theory and supersymmetry
TL;DR: Two-component spinors are the basic ingredients for describing fermions in quantum field theory in 3 + 1 spacetime dimensions as mentioned in this paper, and they are suitable for practical calculations of crosssections, decay rates, and radiative corrections in the Standard Model and its extensions, including supersymmetry, and many explicit examples are provided.
690
References
Structured tools for structured matrices
TL;DR: In this paper, an extensive and unified collection of structure-preserving transformations for non-degenerate bilinear or sesquilinear forms on R n or C n is presented.
Computing the norm ∥A∥∞,1 is NP-hard ∗
TL;DR: It is proved that computing the subordinate matrix norm ∥A∥∞1 is NP-hard and existence of a polynomial-time algorithm for computing this norm with relative accuracy less than 1/(4n2 ), where n is matrix size, implies P = NP.
Non-commutative Clarkson inequalities for unitarily invariant norms
Omar Hirzallah,Fuad Kittaneh +1 more
TL;DR: In this article, it was shown that if A and B are operators on a separable complex Hilbert space and if ||| is any unitarily invariant norm, then 2 |||A| p + |B| p ||| ≤ 2 p-1 for 2 ≤ p < ∞.
Majorizations and inequalities in matrix theory
TL;DR: In matrix theory, majorization plays a significant role as discussed by the authors, and majorization relations among eigenvalues and singular values of matrices produce a lot of norm inequalities and even matrix inequalities.
Related Papers (5)
Adi Ben-Israel,T. N. E. Greville +1 more
- 01 Jan 1974
Roger A. Horn,Charles R. Johnson +1 more
- 01 Jan 1985