The Theory of Matrices. By F R. Gantmacher. Two volumes, pp. 374 and 276. 1959. (Translated from the Russian by K. A. Hirsch; Chelsea Publishing Company, New York)

Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

Systems of the form E\dot{x}=Ax + Bu, y=Cx , with E singular, are studied. Of particular interest are the impulsive modes that may appear in the free-response of such systems when arbitrary initial conditions are permitted, modes that are associated with natural system frequencies at infinity. A generalized definition of system order that incorporates these impulsive degrees of freedom is proposed, and concepts of controllability and observability are defined for the impulsive modes. Allowable equivalence transformations of such singular systems are specified. The present framework is shown to overcome several difficulties inherent in other treatments of singular systems, and to extend, in a natural and satisfying way, many results previously known only for regular state-space systems.

A generalized state-space for singular systems

Some mathematical topics, circulant matrices, in particular, are pure gems that cry out to be admired and studied with different techniques or perspectives in mind. Our work on this subject was originally motivated by the apparent need of one of the authors (IK) to derive a specific result, in the spirit of Proposition 24, to be applied in his investigation of theta constant identities [9]. Although progress on that front eliminated the need for such a theorem, the search for it continued and was stimulated by enlightening conversations with Yum-Tong Siu during a visit to Vietnam. Upon IK’s return to the US, a visit by Paul Fuhrmann brought to his attention a vast literature on the subject, including the monograph [4]. Conversations in the Stony Brook Mathematics’ common room attracted the attention of the other author, and that of Sorin Popescu and Daryl Geller∗ to the subject, and made it apparent that circulant matrices are worth studying in their own right, in part because of the rich literature on the subject connecting it to diverse parts of mathematics. These productive interchanges between the participants resulted in [5], the basis for this article. After that version of the paper lay dormant for a number of years, the authors’ interest was rekindled by the casual discovery by SRS that these matrices are connected with algebraic geometry over the mythical field of one element. Circulant matrices are prevalent in many parts of mathematics (see, for example, [8]). We point the reader to the elegant treatment given in [4, §5.2], and to the monograph [1] devoted to the subject. These matrices appear naturally in areas of mathematics where the roots of unity play a role, and some of the reasons for this to be so will unfurl in our presentation. However ubiquitous they are, many facts about these matrices can be proven using only basic linear algebra. This makes the area quite accessible to undergraduates looking for research problems, or mathematics teachers searching for topics of unique interest to present to their students. We concentrate on the discussion of necessary and sufficient conditions for circulant matrices to be non-singular, and on various distinct representations they have, goals that allow us to lay out the rich mathematical structure that surrounds them. Our treatement though is by no means exhaustive. We expand on their connection to the algebraic geometry over a field with one element, to normal curves, and to Toeplitz’s operators. The latter material illustrates the strong presence these matrices have in various parts of modern and classical mathematics. Additional connections to other mathematics may be found in [11]. The paper is organized as follows. In §2 we introduce the basic definitions, and present two models of the space of circulant matrices, including that as a

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On Circulant Matrices

"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.

/pdf/matrix-mathematics-theory-facts-and-formulas-with-8swhnd659u.pdf

Matrix Mathematics: Theory, Facts, and Formulas with Application to Linear Systems Theory

Linear Systems and Operators in Hilbert Space

Preliminaries.- Linear Spaces.- Determinants.- Linear Transformations.- The Shift Operator.- Structure Theory of Linear Transformations.- Inner Product Spaces.- Quadratic Forms.- Stability.- Elements of System Theory.- Hankel Norm Approximation.

/pdf/a-polynomial-approach-to-linear-algebra-tzvb8g4gls.pdf

A Polynomial Approach to Linear Algebra

A systematic development of the realization theory of finite dimensional constant linear systems is presented which synthesizes the various currently available approaches. Based on representation theorems for submodules and quotient modules of spaces of polynomial matrices and vectors, this paper combines the abstract algebraic ideas centering around module theory, the use of coprime factorizations of rational transfer functions and state space equations into a unified theory.

/pdf/algebraic-system-theory-an-analyst-s-point-of-view-484w0t5yru.pdf

Algebraic system theory: an analyst's point of view

It is shown that if a natural state space model is associated with each polynomial system matrix then the similarity of the models is equivalent to the strict system equivalence (s.s.e.) of the system matrices. A minor departure from Rosenbrock's definition of s.s.e. is needed.

https://www.cs.bgu.ac.il/~paf/paulijc1977.pdf

On strict system equivalence and similarity

/pdf/on-the-corona-theorem-and-its-application-to-spectral-4ow2r6hqwz.pdf

Paul A. Fuhrmann

Papers

Linear Systems and Operators in Hilbert Space

A Polynomial Approach to Linear Algebra

Algebraic system theory: an analyst's point of view

On strict system equivalence and similarity

On the corona theorem and its application to spectral problems in Hilbert space