Independent Component Analysis

A Tutorial Introduction

Author: James V. Stone

Publisher: MIT Press

ISBN: 9780262693158

Category: Mathematics

Page: 193

View: 2912

A tutorial-style introduction to a class of methods for extracting independent signals from a mixture of signals originating from different physical sources; includes MatLab computer code examples.
Posted in Mathematics

Independent Component Analysis

Theory and Applications

Author: Te-Won Lee

Publisher: Springer Science & Business Media

ISBN: 1475728514

Category: Computers

Page: 210

View: 6821

Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, blind source separation by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, telecommunications, medical signal-processing and several data mining issues. This book presents theories and applications of ICA and includes invaluable examples of several real-world applications. Based on theories in probabilistic models, information theory and artificial neural networks, several unsupervised learning algorithms are presented that can perform ICA. The seemingly different theories such as infomax, maximum likelihood estimation, negentropy maximization, nonlinear PCA, Bussgang algorithm and cumulant-based methods are reviewed and put in an information theoretic framework to unify several lines of ICA research. An algorithm is presented that is able to blindly separate mixed signals with sub- and super-Gaussian source distributions. The learning algorithms can be extended to filter systems, which allows the separation of voices recorded in a real environment (cocktail party problem). The ICA algorithm has been successfully applied to many biomedical signal-processing problems such as the analysis of electroencephalographic data and functional magnetic resonance imaging data. ICA applied to images results in independent image components that can be used as features in pattern classification problems such as visual lip-reading and face recognition systems. The ICA algorithm can furthermore be embedded in an expectation maximization framework for unsupervised classification. Independent Component Analysis: Theory and Applications is the first book to successfully address this fairly new and generally applicable method of blind source separation. It is essential reading for researchers and practitioners with an interest in ICA.
Posted in Computers

Advances in Independent Component Analysis and Learning Machines

Author: Ella Bingham,Samuel Kaski,Jorma Laaksonen,Jouko Lampinen

Publisher: Academic Press

ISBN: 0128028076

Category: Technology & Engineering

Page: 328

View: 7858

In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithm Unsupervised deep learning Machine vision and image retrieval A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning. A diverse set of application fields, ranging from machine vision to science policy data. Contributions from leading researchers in the field.
Posted in Technology & Engineering

Independent Component Analysis

Principles and Practice

Author: Stephen Roberts,Richard Everson

Publisher: Cambridge University Press

ISBN: 9780521792981

Category: Computers

Page: 338

View: 3027

Independent Component Analysis (ICA) has recently become an important tool for modelling and understanding empirical datasets. It is a method of separating out independent sources from linearly mixed data, and belongs to the class of general linear models. ICA provides a better decomposition than other well-known models such as principal component analysis. This self-contained book contains a structured series of edited papers by leading researchers in the field, including an extensive introduction to ICA. The major theoretical bases are reviewed from a modern perspective, current developments are surveyed and many case studies of applications are described in detail. The latter include biomedical examples, signal and image denoising and mobile communications. ICA is discussed in the framework of general linear models, but also in comparison with other paradigms such as neural network and graphical modelling methods. The book is ideal for researchers and graduate students in the field.
Posted in Computers

Independent Component Analysis

Author: Aapo Hyvärinen,Juha Karhunen,Erkki Oja

Publisher: Wiley-Interscience

ISBN: 9780471405405

Category: Science

Page: 504

View: 8553

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.
Posted in Science

Independent Component Analysis

Author: Aapo Hyvärinen,Juha Karhunen,Erkki Oja

Publisher: John Wiley & Sons

ISBN: 0471464198

Category: Science

Page: 504

View: 2968

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.
Posted in Science

Handbook of Blind Source Separation

Independent Component Analysis and Applications

Author: Pierre Comon,Christian Jutten

Publisher: Academic Press

ISBN: 9780080884943

Category: Technology & Engineering

Page: 856

View: 6778

Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, R&D engineers and graduates wishing to learn the core principles, methods, algorithms, and applications of Blind Source Separation. Covers the principles and major techniques and methods in one book Edited by the pioneers in the field with contributions from 34 of the world’s experts Describes the main existing numerical algorithms and gives practical advice on their design Covers the latest cutting edge topics: second order methods; algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communications Shows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications
Posted in Technology & Engineering

Advances in Independent Component Analysis

Author: Mark Girolami

Publisher: Springer Science & Business Media

ISBN: 1447104439

Category: Computers

Page: 284

View: 3572

Independent Component Analysis (ICA) is a fast developing area of intense research interest. Following on from Self-Organising Neural Networks: Independent Component Analysis and Blind Signal Separation, this book reviews the significant developments of the past year. It covers topics such as the use of hidden Markov methods, the independence assumption, and topographic ICA, and includes tutorial chapters on Bayesian and variational approaches. It also provides the latest approaches to ICA problems, including an investigation into certain "hard problems" for the very first time. Comprising contributions from the most respected and innovative researchers in the field, this volume will be of interest to students and researchers in computer science and electrical engineering; research and development personnel in disciplines such as statistical modelling and data analysis; bio-informatic workers; and physicists and chemists requiring novel data analysis methods.
Posted in Computers

Independent Component Analysis and Signal Separation

7th International Conference, ICA 2007, London, UK, September 9-12, 2007, Proceedings

Author: Mike E. Davies,Christopher C. James,Samer A. Abdallah,Mark D. Plumbley

Publisher: Springer Science & Business Media

ISBN: 3540744932

Category: Computers

Page: 847

View: 9240

This book constitutes the refereed proceedings of the 7th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2007, held in London, UK, in September 2007. It covers algorithms and architectures, applications, medical applications, speech and signal processing, theory, and visual and sensory processing.
Posted in Computers

On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling

Author: Addisson Salazar

Publisher: Springer Science & Business Media

ISBN: 3642307523

Category: Technology & Engineering

Page: 186

View: 3569

A natural evolution of statistical signal processing, in connection with the progressive increase in computational power, has been exploiting higher-order information. Thus, high-order spectral analysis and nonlinear adaptive filtering have received the attention of many researchers. One of the most successful techniques for non-linear processing of data with complex non-Gaussian distributions is the independent component analysis mixture modelling (ICAMM). This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which unifies a certain number of pattern recognition tasks allowing generalization. The versatile and powerful framework developed in this work can deal with data obtained from quite different areas, such as image processing, impact-echo testing, cultural heritage, hypnograms analysis, web-mining and might therefore be employed to solve many different real-world problems.
Posted in Technology & Engineering

Independent Component Analysis and Blind Signal Separation

6th International Conference, ICA 2006, Charleston, SC, USA, March 5-8, 2006, Proceedings

Author: Justinian Rosca,Deniz Erdogmus,Jose C. Principe,Simon Haykin

Publisher: Springer Science & Business Media

ISBN: 9783540326304

Category: Computers

Page: 980

View: 3984

This book constitutes the refereed proceedings of the 6th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2006, held in Charleston, SC, USA, in March 2006. The 120 revised papers presented were carefully reviewed and selected from 183 submissions. The papers are organized in topical sections on algorithms and architectures, applications, medical applications, speech and signal processing, theory, and visual and sensory processing.
Posted in Computers

Independent Component Analysis and Signal Separation

8th International Conference, ICA 2009, Paraty, Brazil, March 15-18, 2009, Proceedings

Author: Tulay Adali,Christian Jutten,Joao Marcos Travassos Romano

Publisher: Springer Science & Business Media

ISBN: 3642005985

Category: Computers

Page: 785

View: 1032

This book constitutes the refereed proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation, ICA 2009, held in Paraty, Brazil, in March 2009. The 97 revised papers presented were carefully reviewed and selected from 137 submissions. The papers are organized in topical sections on theory, algorithms and architectures, biomedical applications, image processing, speech and audio processing, other applications, as well as a special session on evaluation.
Posted in Computers

Independent Component Analysis and Blind Signal Separation

Fifth International Conference, ICA 2004, Granada, Spain, September 22-24, 2004, Proceedings

Author: Carlos G. Puntonet,Alberto Prieto

Publisher: Springer

ISBN: N.A

Category: Computers

Page: 1266

View: 909

This book constitutes the refereed proceedings of the 5th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2004, held in Granada, Spain, in September 2004. The 156 revised papers presented were carefully reviewed and selected from 203 submissions. The papers are organized in topical sections on theory and foundations, linear models, covolutive models, nonlinear models, speech processing applications, image processing applications, biomedical applications, and other applications.
Posted in Computers

Self-Organising Neural Networks

Independent Component Analysis and Blind Source Separation

Author: Mark Girolami

Publisher: Springer Science & Business Media

ISBN: 1447108256

Category: Computers

Page: 271

View: 8481

The conception of fresh ideas and the development of new techniques for Blind Source Separation and Independent Component Analysis have been rapid in recent years. It is also encouraging, from the perspective of the many scientists involved in this fascinating area of research, to witness the growing list of successful applications of these methods to a diverse range of practical everyday problems. This growth has been due, in part, to the number of promising young and enthusiastic researchers who have committed their efforts to expanding the current body of knowledge within this field of research. The author of this book is among one of their number. I trust that the present book by Dr. Mark Girolami will provide a rapid and effective means of communicating some of these new ideas to a wide international audience and that in turn this will expand further the growth of knowledge. In my opinion this book makes an important contribution to the theory of Independent Component Analysis and Blind Source Separation. This opens a range of exciting methods, techniques and algorithms for applied researchers and practitioner engineers, especially from the perspective of artificial neural networks and information theory. It has been interesting to see how rapidly the scientific literature in this area has grown.
Posted in Computers

Independent Component Analysis of Edge Information for Face Recognition

Author: Kailash J. Karande,Sanjay Talbar

Publisher: Springer Science & Business Media

ISBN: 8132215125

Category: Technology & Engineering

Page: 81

View: 4270

The book presents research work on face recognition using edge information as features for face recognition with ICA algorithms. The independent components are extracted from edge information. These independent components are used with classifiers to match the facial images for recognition purpose. In their study, authors have explored Canny and LOG edge detectors as standard edge detection methods. Oriented Laplacian of Gaussian (OLOG) method is explored to extract the edge information with different orientations of Laplacian pyramid. Multiscale wavelet model for edge detection is also proposed to extract edge information. The book provides insights for advance research work in the area of image processing and biometrics.
Posted in Technology & Engineering

Independent component analysis

a two-phase nonparametric algorithm and testing for statistical independence

Author: Chin-Jen Ku

Publisher: N.A

ISBN: N.A

Category:

Page: 370

View: 4389

Posted in

Independent Component Analysis and Blind Signal Separation

Fifth International Conference, ICA 2004, Granada, Spain, September 22-24, 2004, Proceedings

Author: Carlos G. Puntonet,Alberto Prieto

Publisher: Springer Science & Business Media

ISBN: 3540230564

Category: Computers

Page: 1266

View: 1625

tionsalso,apartfromsignalprocessing,withother?eldssuchasstatisticsandarti?cial neuralnetworks. As long as we can ?nd a system that emits signals propagated through a mean, andthosesignalsarereceivedbyasetofsensorsandthereisaninterestinrecovering the originalsources,we have a potential?eld ofapplication forBSS and ICA. Inside thatwiderangeofapplicationswecan?nd,forinstance:noisereductionapplications, biomedicalapplications,audiosystems,telecommunications,andmanyothers. This volume comes out just 20 years after the ?rst contributionsin ICA and BSS 1 appeared . Thereinafter,the numberof research groupsworking in ICA and BSS has been constantly growing, so that nowadays we can estimate that far more than 100 groupsareresearchinginthese?elds. Asproofoftherecognitionamongthescienti?ccommunityofICAandBSSdev- opmentstherehavebeennumerousspecialsessionsandspecialissuesinseveralwell- 1 J.Herault, B.Ans,“Circuits neuronaux à synapses modi?ables: décodage de messages c- posites para apprentissage non supervise”, C.R. de l'Académie des Sciences, vol. 299, no. III-13,pp.525–528,1984.
Posted in Computers

Independent component analyses, wavelets, unsupervised nano-biomimetic sensors, and neural networks V

10-13 April 2007, Orlando, Florida, USA

Author: Harold H. Szu,Jack Agee

Publisher: Society of Photo Optical

ISBN: 9780819466983

Category: Computers

Page: 452

View: 7432

Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature.
Posted in Computers