Independent Component Analysis

Book Description

A comprehensive introduction to ICA for students and practitioners
Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more.
Independent Component Analysis is divided into four sections that cover:
* General mathematical concepts utilized in the book
* The basic ICA model and its solution
* Various extensions of the basic ICA model
* Real-world applications for ICA models
Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

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A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more. Independent Component Analysis is divided into four sections that cover: * General mathematical concepts utilized in the book * The basic ICA model and its solution * Various extensions of the basic ICA model * Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

Customer Reviews:

Comprehensive Book.......2001-10-30

Independent Component Analysis is a young and interesting topic that gained attention and still receiving more of it.

Until now this is the best introduction that has been written.
It is comprehensive, clear and unbiased.

I think that the book is a step toward making the subject not only a common field of research but also a reference for those looking for new challenging topics.

What worths mentioning is that the authors are very envolved in the development of the theory of ICA ,other books are good but are deviated by their author's own approachs and this is normal but unhealthy for a first book on any field.

What constitutes a great help for understanding ICA are the relatively easy concepts if one just intend to pick an algorithm(ex:FastICA), but this is not the case regarding its theory.

One colleague once argued that ICA should have emerged long before the begining of the 90's, claiming that Gaussian forms
(Central Limit-Theorem) killed the idea of dealing with other kinds of distributions and therefore the signal processing community went assuming every thing was gaussian (noise was gaussian,signals are gaussian),but the emerge of HOS relaxed the gaussian restriction and ICA became possible and no longer 'blind' .

I think this should prepare researchers to deal with coming challengs more intelligently and efficiently .That is why I recommend this book since it tries to give a broad view to the subject .

Nice and detailed description of ICA.......2001-10-27

This is a nice and self-contained book on the subject of independent component analysis (ICA). The authors start with relevant mathematical and statistical background (in Part I) to prepare readers for the derivations of ICA (though seasoned researchers may want to skip the first part of this book). The authors discuss the motivation behind ICA and present several ways to derive ICA (since this subject has been approached by several communities). The authors also compare and discuss the pros and cons of these approaches. The authors discuss several applications using ICA in Part III.

Book Description

A unique treatment of signal processing using a model-based perspective

Signal processing is primarily aimed at extracting useful information, while rejecting the extraneous from noisy data. If signal levels are high, then basic techniques can be applied. However, low signal levels require using the underlying physics to correct the problem causing these low levels and extracting the desired information. Model-based signal processing incorporates the physical phenomena, measurements, and noise in the form of mathematical models to solve this problem. Not only does the approach enable signal processors to work directly in terms of the problem's physics, instrumentation, and uncertainties, but it provides far superior performance over the standard techniques. Model-based signal processing is both a modeler's as well as a signal processor's tool.

Model-Based Signal Processing develops the model-based approach in a unified manner and follows it through the text in the algorithms, examples, applications, and case studies. The approach, coupled with the hierarchy of physics-based models that the author develops, including linear as well as nonlinear representations, makes it a unique contribution to the field of signal processing.

The text includes parametric (e.g., autoregressive or all-pole), sinusoidal, wave-based, and state-space models as some of the model sets with its focus on how they may be used to solve signal processing problems. Special features are provided that assist readers in understanding the material and learning how to apply their new knowledge to solving real-life problems.
* Unified treatment of well-known signal processing models including physics-based model sets
* Simple applications demonstrate how the model-based approach works, while detailed case studies demonstrate problem solutions in their entirety from concept to model development, through simulation, application to real data, and detailed performance analysis
* Summaries provided with each chapter ensure that readers understand the key points needed to move forward in the text as well as MATLAB(r) Notes that describe the key commands and toolboxes readily available to perform the algorithms discussed
* References lead to more in-depth coverage of specialized topics
* Problem sets test readers' knowledge and help them put their new skills into practice

The author demonstrates how the basic idea of model-based signal processing is a highly effective and natural way to solve both basic as well as complex processing problems. Designed as a graduate-level text, this book is also essential reading for practicing signal-processing professionals and scientists, who will find the variety of case studies to be invaluable.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department

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Model-Based Signal Processing develops the ""model-based approach"" to signal processing for a variety of useful model sets including the popularly termed ""physics-based"" models. It presents a unique viewpoint of signal processing from the model-based perspective. A wide variety of case studies are included to demonstrate the applicability of the approach to real-world problems. This book presents a unified treatment of the model-based approach and includes numerous case studies to demonstrate applicability of method to real-world situations, as well as MATLAB notes.

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Practical advice for selecting adaptive control products

Techniques for Adaptive Control

Manufacturer: Butterworth-Heinemann
ProductGroup: Book
Binding: Paperback

Motivational | Management & Leadership | Business & Investing | Subjects | Books

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ASIN: 0750674954

Book Description

Techniques for Adaptive Control compiles chapters from a team of expert contributors that allow readers to gain a perspective into a number of different approaches to adaptive control. In order to do this, each contributor provides an overview of a particular product, how it works, and reasons why a user would want it as well as an in depth explanation of their particular method.

This is one of the latest technologies to emerge in the instrumentation and control field. These latest control methodologies offer a means to revolutionize plant and process efficiency, response time and profitability by allowing a process to be regulated by a form of rule-based AI, without human intervention.

Rather than the common academic-based approach that books on this subject generally take, the contributions here outline practical applications of adaptive control technology allowing for a real look inside the industry and the new technologies available.

* Written by a team of contributors from the industry's best-known product manufacturers and software developers
* Provides real insight into new technologies available in the industry
* Outlines practical applications of adaptive control technology

Customer Reviews:

Practical advice for selecting adaptive control products.......2002-11-10

I've been debating which of several adaptive control software products to apply to my distillation tower temperature loops. This book provided an overview of the technology behind every product I'd been considering and then some. Some of the material presented was a little too mathematical to really mean anything to me, but I got a general idea of how and why each product works. I found the introduction by the editor particularly helpful in comparing the various approaches to adaptive control. I now have a much better feel for which of the available commercial software products is likely to give me the results I want with the information I have available.

Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques

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Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques
Jeffrey T. Spooner , Manfredi Maggiore , Raúl Ordóñez , and Kevin M. Passino
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover

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ASIN: 0471415464

Book Description

Includes a solution manual for problems.
Provides MATLAB code for examples and solutions.
Deals with robust systems in both theory and practice.

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Includes a solution manual for problems.
* Provides MATLAB code for examples and solutions.
* Deals with robust systems in both theory and practice.

Signal Processing for Intelligent Sensor Systems (SIGNAL PROCESSING AND COMMUNICATIONS)

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Signal Processing for Intelligent Sensor Systems (SIGNAL PROCESSING AND COMMUNICATIONS)
David C. Swanson
Manufacturer: CRC
ProductGroup: Book
Binding: Hardcover

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ASIN: 0824799429

Book Description

"Integrates a broad range of physics, algorithms, and sensing techniques for development of intelligent systems. Highlights adaptive least-squared error modeling. Covers complex sampling, physical system modeling using digital filters, frequency domain processing, beamforming, and much more."

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Intelligent Signal Processing

Manufacturer: Wiley-IEEE Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 0780360109

Book Description

"IEEE Press is proud to present the first selected reprint volume devoted to the new field of intelligent signal processing (ISP). ISP differs fundamentally from the classical approach to statistical signal processing in that the input-output behavior of a complex system is modeled by using intelligent or model-free techniques, rather than relying on the shortcomings of a mathematical model. Information is extracted from incoming signal and noise data, making few assumptions about the statistical structure of signals and their environment.

Intelligent Signal Processing explores how ISP tools address the problems of practical neural systems, new signal data, and blind fuzzy approximators. The editors have compiled 20 articles written by prominent researchers covering 15 diverse, practical applications of this nascent topic, exposing the reader to the signal processing power of learning and adaptive systems.

This essential reference is intended for researchers, professional engineers, and scientists working in statistical signal processing and its applications in various fields such as humanistic intelligence, stochastic resonance, financial markets, optimization, pattern recognition, signal detection, speech processing, and sensor fusion. Intelligent Signal Processing is also invaluable for graduate students and academics with a background in computer science, computer engineering, or electrical engineering.

About the Editors

Simon Haykin is the founding director of the Communications Research Laboratory at McMaster University, Hamilton, Ontario, Canada, where he serves as university professor. His research interests include nonlinear dynamics, neural networks and adaptive filters and their applications in radar and communications systems. Dr. Haykin is the editor for a series of books on Adaptive and Learning Systems for Signal Processing, Communications and Control (Publisher) and is both an IEEE Fellow and Fellow of the Royal Society of Canada.

Book Description

The current revolution in electronic switching and transport technologies promises a dramatic increase in the intimacy and satisfaction that users will experience over imminent telecommunications networks. However, unless there is a corresponding improvement in the technologies of the acoustics of telecommunications, this promise will soon prove empty. The sense of presence that people feel when together in a room is largely due to the psycho-acoustic cues they sense from the human binaural hearing system evolved over millennia. Modern acoustic signal processing is just now beginning to be able to deliver that same experience to users remotely located from each other. This includes the ability to communicate in full duplex with wider bandwidths and multiple audio streams (e.g. stereo, 3D audio). It also involves locating and separating audio sources, suppressing noise, and using sound to automatically steer video cameras.
Acoustic Signal Processing for Telecommunication presents digital signal processing techniques for telecommunications acoustics that are both cutting-edge and practical. Each chapter presents material that has not appeared in book form before and yet is easily realizable in today's technology. To this end, both new theory and new implementation techniques are presented. Topics include new adaptive filtering algorithms, multi-channel acoustic echo cancellation, noise control, virtual sound, sound source localization for camera tracking, source separation, and microphone arrays.

Customer Reviews:

Good coverage but too simple results.......2001-03-30

Topics are carefully selected. Good coverage of both traditional and cutting-edge new theories and algorithms. Less errors than a normal technique book. Only key derivations are outlined with others just omitted. This makes it easy to follow for an engineer like me but i suppose an academic researcher may dislike it somewhat. Unfortunately, too few results are given for each algorithm. Readers don't know if the algorithms have the potential to meet the various requirements of EC, i.e., residue error, convergence rate, complexity, numerical stability. (By the way, even a simple touch of industry standard of AEC might be helpful for this book) Anyway, for anyone who is interested in either accademic research or implementation of EC, i guess this book gives him/her a solid starting point.

Adaptive Control and Optimization Techniques

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Adaptive Control and Optimization Techniques
Virgil W. Eveleigh
Manufacturer: McGraw-Hill
ProductGroup: Book
Binding: Hardcover
ASIN: B000W7NAP8

Adaptive control and optimization techniques (McGraw-Hill electrical and electronic engineering series)

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Adaptive control and optimization techniques (McGraw-Hill electrical and electronic engineering series)
Virgil W Eveleigh
Manufacturer: McGraw-Hill
ProductGroup: Book
Binding: Unknown Binding

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Airborne Radar Interference Suppression Using Adaptive Three-Dimensional Techniques

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Airborne Radar Interference Suppression Using Adaptive Three-Dimensional Techniques

Manufacturer: Storming Media
ProductGroup: Book
Binding: Spiral-bound

Product Description

This is a AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING AND MANAGEMENT report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A755204. The abstract provided by the Pentagon follows: This research advances adaptive interference suppression techniques for airborne radar, addressing the problem of target detection within severe interference environments characterized by high ground clutter levels, levels, noise jammer infiltration, and strong discrete interferers. Two-dimensional (2D) Space-Time Adaptive Processing (STAP) concepts are extended into three- dimensions (3D) by casting each major 2D STAP research area into a 3D framework. The work first develops an appropriate 3D data model with provisions for range ambiguous clutter returns. Adaptive 3D development begins with two factored approaches, 3D Factored Time-Space (3D-FTS) and Elevation-Joint Domain Localized (Elev-JDL). The 3D adaptive development continues with optimal techniques, i.e., joint domain methods. First, the 3D matched Filter (3D-MF) is derived followed by a 3D Adaptive Matched Filter (3D-AMF) discussion focusing on well established practical limitations consistent with the 2D case. Finally, a 3D-JDL method is introduced. Proposed 3D Hybrid methods extend current state-of-the-art 2D hybrid methods. The initial 3D hybrid, a functional extension of the 2D technique, exhibits distinct performance advantages in heterogeneous clutter. The final 3D hybrid method is virtually impervious to discrete interference.

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