This book describes the Schur complement as a rich and basic tool in mathematical research and applications and discusses many significant results that illustrate its power and fertility. Coverage includes historical development, basic properties, eigenvalue and singular value inequalities, matrix inequalities in both finite and infinite dimensional settings, closure properties, and applications in statistics, probability, and numerical analysis.

In this monograph, we combine operator techniques with state space methods to solve factorization, spectral estimation, and interpolation problems arising in control and signal processing. We present both the theory and algorithms with some Matlab code to solve these problems. A classical approach to spectral factorization problems in control theory is based on Riccati equations arising in linear quadratic control theory and Kalman ?ltering. One advantage of this approach is that it readily leads to algorithms in the non-degenerate case. On the other hand, this approach does not easily generalize to the nonrational case, and it is not always transparent where the Riccati equations are coming from. Operator theory has developed some elegant methods to prove the existence of a solution to some of these factorization and spectral estimation problems in a very general setting. However, these techniques are in general not used to develop computational algorithms. In this monograph, we will use operator theory with state space methods to derive computational methods to solve factorization, sp- tral estimation, and interpolation problems. It is emphasized that our approach is geometric and the algorithms are obtained as a special application of the theory. We will present two methods for spectral factorization. One method derives al- rithms based on ?nite sections of a certain Toeplitz matrix. The other approach uses operator theory to develop the Riccati factorization method. Finally, we use isometric extension techniques to solve some interpolation problems.

This volume contains six peer-refereed articles written on the occasion of the workshop Operator theory, system theory and scattering theory: multidimensional generalizations and related topics, held at the Department of Mathematics of the Ben-Gurion University of the Negev in June, 2005. The book will interest a wide audience of pure and applied mathematicians, electrical engineers and theoretical physicists.

The NATO Advanced Research Workshop on Signal Processing and Pattern Recognition in Nondestructive Evaluation (NOE) of Materials was held August 19-22, 1987 at the Manoir St-Castin, Lac Beauport, Quebec, Canada. Modern signal processing, pattern recognition and artificial intelligence have been playing an increasingly important role in improving nondestructive evaluation and testing techniques. The cross fertilization of the two major areas can lead to major advances in NOE as well as presenting a new research area in signal processing. With this in mind, the Workshop provided a good review of progress and comparison of potential techniques, as well as constructive discussions and suggestions for effective use of modern signal processing to improve flaw detection, classification and prediction, as well as material characterization. This Proceedings volume includes most presentations given at the Workshop. This publication, like the meeting itself, is unique in the sense that it provides extensive interactions among the interrelated areas of NOE. The book starts with research advances on inverse problems and then covers different aspects of digital waveform processing in NOE and eddy current signal analysis. These are followed by four papers of pattern recognition and AI in NOE, and five papers of image processing and reconstruction in NOE. The last two papers deal with parameter estimation problems. Though the list of papers is not extensive, as the field of NOE signal processing is very new, the book has an excellent collection of both tutorial and research papers in this exciting new field.

Much of the importance of mathematics lies in its ability to provide theories which are useful in widely different fields of endeavour. A good example is the large and amorphous body of knowledge known as the theory of linear operators or operator theory, which came to life about a century ago as a theory to encompass properties common to matrix, differential, and integral operators. Thus, it is a primary purpose of operator theory to provide a coherent body of knowledge which can explain phenomena common to the enormous variety of problems in which such linear operators play a part. The theory is a vital part of functional analysis, whose methods and techniques are one of the major advances of twentieth century mathematics and now play a pervasive role in the modeling of phenomena in probability, imaging, signal processing, systems theory, etc, as well as in the more traditional areas of theoretical physics and mechanics. This book is based on lectures presented at a meeting on operator theory and its applications held at the Fields Institute in 1994.

This volume contains a collection of recent original research papers in operator theory in Krein spaces, on generalized Nevanlinna functions, which are closely connected with this theory, and on nonlinear eigenvalue problems. Key topics include: spectral theory for normal operators; perturbation theory for self-adjoint operators in Krein spaces; and, models for generalized Nevanlinna functions.