Adaptive Filter Theory (5th Edition)
Adaptive Filter Theory, 5e, is ideal for courses in Adaptive Filters.
Haykin examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons. In its fifth edition, this highly successful book has been updated and refined to stay current with the field and develop concepts in as unified and accessible a manner as possible.
Algorithms for Statistical Signal Processing
Keeping pace with the expanding, ever more complex applications of DSP, this authoritative presentation of computational algorithms for statistical signal processing focuses on advanced topics ignored by other books on the subject. Algorithms for Convolution and DFT. Linear Prediction and Optimum Linear Filters. Least-Squares Methods for System Modeling and Filter Design. Adaptive Filters. Recursive Least-Squares Algorithms for Array Signal Processing. QRD-Based Fast Adaptive Filter...
Handbook for Digital Signal Processing
Discusses important topics in modern digital signal processing. Designed to fill the needs of practicing engineers and designers of hardware systems and software. The editors present the principal applications of the subject, followed by coverage of such topics as linear time-invariant discrete-time systems, finite- and infinite- impulse response digital filter design, digital filter implementation considerations, signal conditioning and interface circuits, hardware and architecture,...
Detection, Estimation, and Modulation Theory, Optimum Array Processing (Part IV) Part IV edition by Van Trees, Harry L.
Fundamentals of Adaptive Filtering
This book is based on a graduate level course offered by the author at UCLA and has been classed tested there and at other universities over a number of years. This will be the most comprehensive book on the market today providing instructors a wide choice in designing their courses. Offers computer problems to illustrate real life applications for students and professionals alike An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the...
Space-Time Adaptive Processing for Radar
Based on a time-tested course taught in industry, government and academia, this second edition reviews basic STAP concepts and methods, placing emphasis on implementation in real-world systems
Linear Estimation
This original work offers the most comprehensive and up-to-date treatment of the important subject of optimal linear estimation, which is encountered in many areas of engineering such as communications, control, and signal processing, and also several other fields, e.g., econometrics and statistics. The book not only highlights the most significant contributions to this field during the 20th century, including the works of Weiner and Kalman, but it does so in an original and novel manner...
Statistical Digital Signal Processing and Modeling
The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering. Scores of worked examples illustrate fine points, compare techniques and algorithms and facilitate comprehension of fundamental concepts. Also features an abundance of interesting and challenging problems at the end of every chapter.
Adaptive Signal Processing
A treatment of adaptive signal processing featuring frequent use of examples.
Optimum Signal Processing
This revised edition is an unabridged and corrected republication of thesecond edition of this book published by McGraw-Hill Publishing Company,New York, NY, in 1988 (ISBN 0-07-047794-9), and also published earlierby Macmillan, Inc., New York, NY, 1988 (ISBN 0-02-389380-X). Allcopyrights to this work reverted to Sophocles J. Orfanidis in 1996.The content of the 2007 republication remains the same as that of the1988 edition, except for some corrections, the deletion from theAppendix of the...
Digital Signal Processing with Kernel Methods (Wiley - IEEE)
A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can...
Bayesian Signal Processing: Classical, Modern, and Particle Filtering Methods (Adaptive and Cognitive Dynamic Systems: S
Presents the Bayesian approach to statistical signal processing for a variety of useful model sets
This book aims to give readers a unified Bayesian treatment starting from the basics (Baye’s rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of...
Digital Signal Processing: with selected topics: Adaptive Systems, Time-Frequency Analysis, Sparse Signal Processing
This book is a result of author's thirty-three years of experience in teaching and research in signal processing. The book will guide you from a review of continuous-time signals and systems, through the world of digital signal processing, up to some of the most advanced theory and techniques in adaptive systems, time-frequency analysis, and sparse signal processing. It provides simple examples and explanations for each, including the most complex transform, method, algorithm or approach...
Stochastic Systems: Estimation, Identification, and Adaptive Control (Classics in Applied Mathematics)
Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area.
This book provides succinct and rigorous treatment...
Space-Time Adaptive Processing for Radar
Based on a time-tested course taught in industry, government and academia, this second edition reviews basic STAP concepts and methods, placing emphasis on implementation in real-world systems
Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB®
Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB® covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area―the least mean square (LMS) adaptive filter.
This largely self-contained text:
Principles of System Identification: Theory and Practice
Master Techniques and Successfully Build Models Using a Single Resource
Vital to all data-driven or measurement-based process operations, system identification is an interface that is based on observational science, and centers on developing mathematical models from observed data. Principles of System Identification: Theory and Practice is an introductory-level book that presents the basic foundations and underlying methods relevant to system identification. The overall scope of the book...
Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks)
Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in...
Adaptive Filter Theory (5th Edition)
Adaptive Filter Theory, 5e, is ideal for courses in Adaptive Filters.
Haykin examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons. In its fifth edition, this highly successful book has been updated and refined to stay current with the field and develop concepts in as unified and accessible a manner as possible.
High Frequency Over-the-Horizon Radar: Fundamental Principles, Signal Processing, and Practical Applications
THE MOST COMPLETE GUIDE TO HIGH FREQUENCY OVER-THE-HORIZON RADAR SYSTEMS
Written by a leading global expert on the topic, High Frequency Over-the-Horizon Radar provides in-depth coverage of the signal processing models and techniques that have significantly advanced OTH radar technology. This pioneering work describes the fundamental principles of OTH radar design and operation, and then delves into the mathematical modeling of HF signals received by actual OTH radar systems based on...
