This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering. Over 100 exercises and problems with solutions help deepen the knowledge. This new edition has a new chapter on filtering communication networks and data processing, together with new exercises and new real-time applications.

This textbook, apart from introducing the basic aspects of applied mathematics, focuses on recent topics such as information data manipulation, information coding, data approximation, data dimensionality reduction, data compression, time-frequency and time scale bases, image manipulation, and image noise removal. The methods treated in more detail include spectral representation and "frequency" of the data, providing valuable information for, e.g. data compression and noise removal. Furthermore, a special emphasis is also put on the concept of "wavelets" in connection with the "multi-scale" structure of data-sets. The presentation of the book is elementary and easily accessible, requiring only some knowledge of elementary linear algebra and calculus. All important concepts are illustrated with examples, and each section contains between 10 an 25 exercises. A teaching guide, depending on the level and discipline of instructions is included for classroom teaching and self-study.

This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering. Over 100 exercises and problems with solutions help deepen the knowledge. This new edition has a new chapter on filtering communication networks and data processing, together with new exercises and new real-time applications.

A knowledge of linear systems provides a firm foundation for the study of optimal control theory and many areas of system theory and signal processing. State-space techniques developed since the early sixties have been proved to be very effective. The main objective of this book is to present a brief and somewhat complete investigation on the theory of linear systems, with emphasis on these techniques, in both continuous-time and discrete-time settings, and to demonstrate an application to the study of elementary (linear and nonlinear) optimal control theory. An essential feature of the state-space approach is that both time-varying and time-invariant systems are treated systematically. When time-varying systems are considered, another important subject that depends very much on the state-space formulation is perhaps real-time filtering, prediction, and smoothing via the Kalman filter. This subject is treated in our monograph entitled "Kalman Filtering with Real-Time Applications" published in this Springer Series in Information Sciences (Volume 17). For time-invariant systems, the recent frequency domain approaches using the techniques of Adamjan, Arov, and Krein (also known as AAK), balanced realization, and oo H theory via Nevanlinna-Pick interpolation seem very promising, and this will be studied in our forthcoming monograph entitled "Mathematical Ap proach to Signal Processing and System Theory." The present elementary treatise on linear system theory should provide enough engineering and mathe of these two subjects."

"Signal Processing and Systems Theory" is concerned with the study of H-optimization for digital signal processing and discrete-time control systems. The first three chapters present the basic theory and standard methods in digital filtering and systems from the frequency-domain approach, followed by a discussion of the general theory of approximation in Hardy spaces. AAK theory is introduced, first for finite-rank operators and then more generally, before being extended to the multi-input/multi-output setting. This mathematically rigorous book is self-contained and suitable for self-study. The advanced mathematical results derived here are applicable to digital control systems and digital filtering.

"Kalman Filtering with Real-Time Applications" presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. The last two topics are new additions to this third edition. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge.

Discrete "H"A Optimization is concerned with the study of "H"A optimization for digital signal processing and discrete-time control systems. The first three chapters present the basic theory and standard methods in digital filtering and systems from the frequency-domain approach, followed by a discussion of the general theory of approximation in Hardy spaces. AAK theory is introduced, first for finite-rank operators and then more generally, before being extended to the multi-input/multi-output setting. This mathematically rigorous book is self-contained and suitable for self-study. The advanced mathematical results derived here are applicable to digital control systems and digital filtering.

An Introduction to Wavelets is the first volume in a new series, WAVELET ANALYSIS AND ITS APPLICATIONS. This is an introductory treatise on wavelet analysis, with an emphasis on spline wavelets and time-frequency analysis. Among the basic topics covered in this book are time-frequency localization, integral wavelet transforms, dyadic wavelets, frames, spline-wavelets, orthonormal wavelet bases, and wavelet packets. In addition, the author presents a unified treatment of nonorthogonal, semiorthogonal, and orthogonal wavelets. This monograph is self-contained, the only prerequisite being a basic knowledge of function theory and real analysis. It is suitable as a textbook for a beginning course on wavelet analysis and is directed toward both mathematicians and engineers who wish to learn about the subject. Specialists may use this volume as a valuable supplementary reading to the vast literature that has already emerged in this field.
Key Features
* This is an introductory treatise on wavelet analysis, with an emphasis on spline-wavelets and time-frequency analysis
* This monograph is self-contained, the only prerequisite being a basic knowledge of function theory and real analysis
* Suitable as a textbook for a beginning course on wavelet analysis

Survey papers written by experts in the fields of Abstract and Classical Analysis, along with contributed research papers.

Topics include:

biharmonic splines
cardinal L-splines
discrete splines
exterior BVPs
financial optimization
framelets
FSI generators
Gabor frames
moving least squares
multiwavelets
nonstationary wavelets
non-MSF wavelets
orthogonal wavelets
penalized least squares
refinable functions
SAR interferometry
smoothing splines
spline bases
spline interpolation
Sturm-Liouville problems
subdivision
thin plate splines
wavelet packets

Survey papers written by experts in the fields of Wavelets, Splines, and Applications, along with contributed research papers.

Topics include:

approximation of eigenvalues
approximation with weights
Bernstein inequalities
Chebyshev centers
generalized polynomials
Haar sets
kernels on manifolds
linear operators
Markov inequalities
minimal projections
multivariate interpolation
nonlinear approximation
one-sided approximation
orthogonal polynomials
polynomial approximation
rational approximation
shift invariant spaces
uni-modular polynomials
zero-increasing transformations

This meticulously edited selection of papers comes out of the Ninth International Symposium on Approximation Theory held in Nashville, Tennessee, in January, 1998. Each volume contains several invited survey papers written by experts in the field, along with contributed research papers.

This book should be of great interest to mathematicians, engineers, and computer scientists working in approximation theory, wavelets, computer-aided geometric design (CAGD), and numerical analysis.

Among the topics included in the books are the following:

adaptive approximation
approximation by harmonic functions
approximation by radial basis functions
approximation by ridge functions
approximation in the complex plane
Bernstein polynomials
bivariate splines
constructions of multiresolution analyses
convex approximation
frames and frame bases
Fourier methods
generalized moduli of smoothness
interpolation and approximation by splines on triangulations
multiwavelet bases
neural networks
nonlinear approximation
quadrature and cubature
rational approximation
refinable functions
subdivision schemes
thin plate splines
wavelets and wavelet systems

This meticulously edited selection of papers comes out of the Ninth International Symposium on Approximation Theory held in Nashville, Tennessee, in January, 1998. Each volume contains several invited survey papers written by experts in the field, along with contributed research papers.

This book should be of great interest to mathematicians, engineers, and computer scientists working in approximation theory, wavelets, computer-aided geometric design (CAGD), and numerical analysis.

Among the topics included in the books are the following:

adaptive approximation
approximation by harmonic functions
approximation by radial basis functions
approximation by ridge functions
approximation in the complex plane
Bernstein polynomials
bivariate splines
constructions of multiresolution analyses
convex approximation
frames and frame bases
Fourier methods
generalized moduli of smoothness
interpolation and approximation by splines on triangulations
multiwavelet bases
neural networks
nonlinear approximation
quadrature and cubature
rational approximation
refinable functions
subdivision schemes
thin plate splines
wavelets and wavelet systems