Estimation theory is a product of need and technology. As a result, it is an integral part of many branches of science and engineering. To help readers differentiate among the rich collection of estimation methods and algorithms, this book describes in detail many of the important estimation methods and shows how they are interrelated. Written as a collection of lessons, this book introduces readers o the general field of estimation theory and includes abundant supplementary material.
The purpose of this book is to explore several specific areas of research in two distinct but related fields: digital signal processing and modern control and estimation theory. There are enough similarities "and" differences in the philosophies, goals, and analytical techniques of the two fields to indicate that a concerted effort to understand these better might lead to some useful interaction and collaboration among researchers.The author writes that his examination "will in general not be result-oriented. Instead, I have been most interested in understanding the goals of the research and the methods and approach used. Understanding the goals may help us to see why the techniques used in the two disciplines differ. Inspecting the methods and approaches may allow one to see areas in which concepts in one field may be usefully applied in the other. The book undoubtedly has a control-oriented flavor, since it reflects the author's background and also since the original purpose of this study was to present a control theorist's point of view at the 1976 Arden House Workshop on Digital Signal Processing. However, an effort has been made to explore avenues in both disciplines in order to encourage researchers in the two fields to continue along these lines."Indeed, the book contains numerous suggestions for new research directions and speculations on possible new results, all of them a direct result of the purposeful mixing of the ideas of the two disciplines. For the benefit of researchers who may wish to follow up some of these suggestions and speculations, the author has assembled a comprehensive bibliography, consisting of more than 600 references.In order to achieve his unique perspective of viewing each field in the context of the other, the author examines such topics as stability analysis of feedback control systems and digital filters subject to the effects of finite wordlength arithmetic; linear prediction, parameter identification, and relationships involving Kalman filtering and "fast" algorithms; system synthesis, realization, and implementation; two-dimensional filtering, decentralized control and estimation, and some of their connections with image processing; and aspects of nonlinear system theory, including homomorphic and bilinear systems.
Master the basic concepts and methodologies of digital signal processing with this systematic introduction, without the need for an extensive mathematical background. The authors lead the reader through the fundamental mathematical principles underlying the operation of key signal processing techniques, providing simple arguments and cases rather than detailed general proofs. Coverage of practical implementation, discussion of the limitations of particular methods and plentiful MATLAB illustrations allow readers to better connect theory and practice. A focus on algorithms that are of theoretical importance or useful in real-world applications ensures that students cover material relevant to engineering practice, and equips students and practitioners alike with the basic principles necessary to apply DSP techniques to a variety of applications. Chapters include worked examples, problems and computer experiments, helping students to absorb the material they have just read. Lecture slides for all figures and solutions to the numerous problems are available to instructors.
This text introduces digital control systems and demonstrates how to analyze and design these systems. It shows how to use DSPs to implement controllers designed with both classical frequency domain techniques and modem state variable methods. Computer-aided analysis and design tools, like MATLAB, are used throughout, and the basic mathematics of digital control systems are presented early, so users have the grounding they need to solve real-world problems. Classical design techniques for compensators are explained, as is the use of DSPs to implement compensator transfer functions. The book closes with a detailed look at modern state space techniques like pole placement state estimation; the optimal linear quadratic regulator; and a brief discussion of fuzzy logic design.
"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.
An essential task in radar systems is to find an appropriate solution to the problems related to robust signal processing and the definition of signal parameters. Signal Processing in Radar Systems addresses robust signal processing problems in complex radar systems and digital signal processing subsystems. It also tackles the important issue of defining signal parameters. The book presents problems related to traditional methods of synthesis and analysis of the main digital signal processing operations. It also examines problems related to modern methods of robust signal processing in noise, with a focus on the generalized approach to signal processing in noise under coherent filtering. In addition, the book puts forth a new problem statement and new methods to solve problems of adaptation and control by functioning processes. Taking a systems approach to designing complex radar systems, it offers readers guidance in solving optimization problems. Organized into three parts, the book first discusses the main design principles of the modern robust digital signal processing algorithms used in complex radar systems. The second part covers the main principles of computer system design for these algorithms and provides real-world examples of systems. The third part deals with experimental measurements of the main statistical parameters of stochastic processes. It also defines their estimations for robust signal processing in complex radar systems. Written by an internationally recognized professor and expert in signal processing, this book summarizes investigations carried out over the past 30 years. It supplies practitioners, researchers, and students with general principles for designing the robust digital signal processing algorithms employed by complex radar systems.
This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.
This volume presents the fundamentals of data signal processing, ranging from data conversion to z-transforms and spectral analysis. In addition to presenting basic theory and describing the devices, the material is complemented by real examples in specific case studies.
Exploring signals and systems, this work develops continuous-time and discrete-time concepts, highlighting the differences and similarities. Two chapters deal with the Laplace transform and the Z-transform. Basic methods such as filtering, communication an
