Advances in Independent Component Analysis

Multidimensional independent component analysis. In Proc. IEEE Int. Conf. on
Acoustics, Speech and Signal Processing (ICASSP'98), Seattle, WA, 1998. . J. F.
Cardoso. Entropic contrasts for source separation. In S. Haykin, editor, Adaptive ...

Author: Mark Girolami

Publisher: Springer Science & Business Media

ISBN: 1447104439

Category: Computers

Page: 284

View: 481

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.

Advances in Independent Component Analysis and Learning Machines

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 ...

Author: Ella Bingham

Publisher: Academic Press

ISBN: 0128028076

Category: Technology & Engineering

Page: 328

View: 490

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.

Independent Component Analysis

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.

Author: Aapo Hyvärinen

Publisher: John Wiley & Sons

ISBN: 0471464198

Category: Science

Page: 504

View: 750

A comprehensive introduction to ICA for students andpractitioners Independent Component Analysis (ICA) is one of the most excitingnew topics in fields such as neural networks, advanced statistics,and signal processing. This is the first book to provide acomprehensive introduction to this new technique complete with thefundamental mathematical background needed to understand andutilize it. It offers a general overview of the basics of ICA,important solutions and algorithms, and in-depth coverage of newapplications in image processing, telecommunications, audio signalprocessing, and more. Independent Component Analysis is divided into four sections thatcover: * 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 theircontributions to the development of ICA and here cover all therelevant theory, new algorithms, and applications in variousfields. Researchers, students, and practitioners from a variety ofdisciplines will find this accessible volume both helpful andinformative.

Independent Component Analysis and Blind Signal Separation

C . Jutten and J . Karhunen , “ Advances in nonlinear blind source separation , "
in Proc . of the 4th Int . Symp . on Independent Component Analysis and Blind
Signal Separation ( ICA 2003 ) , pp . 245 - 256 , 2003 . Invited paper in the
special ...

Author:

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Category: Electronic noise

Page:

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Semiparametric Inference for Independent Component Analysis

Advances in Independent Component Analysis . Springer - Verlag . [ 43 ] Golub ,
G. ( 1996 ) . Matrix computation . Johns Hopkins University Press . ( 44 ) Hall , P.
and Morton , S. ( 1993 ) . On the estimation of entropy . Ann . Inst . Statist . Math .

Author: Aiyou Chen

Publisher:

ISBN:

Category:

Page: 230

View: 644


Blind Source Separation

The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications.

Author: Ganesh R. Naik

Publisher: Springer

ISBN: 3642550169

Category: Technology & Engineering

Page: 551

View: 167

Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications. Furthermore, the research results previously scattered in many journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms and applications of BSS. Dr. Ganesh R. Naik works at University of Technology, Sydney, Australia; Dr. Wenwu Wang works at University of Surrey, UK.

The IEEE 2000 Adaptive Systems for Signal Processing Communications and Control Symposium AS SPCC October 1 4 2000 Chateau Lake Louise Lake Louise Alberta Canada

Several authors have tried to generalize linear ICA and blind source separation
for nonlinear models ; see ( 10 , 14 ) for further information and references . In
particular ... In M . Girolami , editor , Advances in Independent Component
Analysis .

Author:

Publisher: Institute of Electrical & Electronics Engineers(IEEE)

ISBN:

Category: Adaptive control systems

Page: 480

View: 822

The proceedings of the Symposium on Adaptive Systems for Signal Processing, Communications, and Control, 2000. It addresses fundamentals of adaptive and learning systems; signal processing; radar/sonar; wireless communications; pattern recognition; chaos; and more.

Bayesian Inference and Maximum Entropy Methods in Science and Engineering

A . Hyvarinen , J . Karhunen , E . Oja , Independent Component Analysis , John
Wiley & Sons , 2001 . 2 . A . K . Barros , “ The Independence Assumption :
Dependent Component Analysis , ” in Advances in Independent Component
Analysis ...

Author: Kevin H. Knuth

Publisher: American Inst. of Physics

ISBN: 9780735402928

Category: Science

Page: 564

View: 723

All papers were peer-reviewed. For over 25 years the MaxEnt workshops have explored Bayesian and Maximum Entropy methods in scientific, engineering, and signal processing applications. This proceedings volume covers all aspects of probabilistic inference such as techniques, applications, and foundations. Applications include physics, space science, earth science, biology, imaging, graphical models and source separation.

Advances in Communications Computing Networks and Security Volume 8

In this paper, a fixed point algorithm of Independent Component Analysis (ICA)
was used to separate linearly mixed stationary and non-stationary mixed audio
signals. Also, an attempt was made to solve the permutation problem oflinearly ...

Author: Paul Dowland

Publisher: Lulu.com

ISBN: 1841022934

Category:

Page:

View: 595


Artificial Neural Networks

Hidden Markov Independent Components Analysis. In M. Girolami, editor,
Advances in Independent Component Analysis. Springer, 2000. 8. W.D. Penny,
S.J. Roberts, and R. Everson. ICA: model order selection and dynamic source
models.

Author:

Publisher:

ISBN:

Category: Neural networks (Computer science)

Page:

View: 377


Advances in Neural Networks

The majority of existing Independent Component Analysis (ICA) algorithms are
based on maximizing or minimizing a certain objective function with the help of
gradient learning methods. However, it is rather difficult to prove whether there is
no ...

Author: Fuchun Sun

Publisher: Springer Science & Business Media

ISBN: 3540877312

Category: Computers

Page: 908

View: 472

(Bayreuth University, Germany), Jennie Si (Arizona State University, USA), and Hang Li (MicrosoftResearchAsia, China). Besides the regularsessions andpanels, ISNN 2008 also featured four special sessions focusing on some emerging topics.

Smart Engineering System Design

Hyvarinen A , Karhunen J , Oja E ( 2001 ) Independent Component Analysis .
John Wiley & Sons , Toronto . Joachims T ( 1999 ) Making large - scale SVM
learning practical . Advances in Kernel Methods - Support Vector Learning ,
Schölkopf ...

Author: Cihan H. Dagli

Publisher: Intelligent Engineering System

ISBN: 9780791802403

Category: Computers

Page: 894

View: 773

The newest volume in this series presents refereed papers in the following categories and their applications in the engineering domain: Neural Networks; Complex Networks; Evolutionary Programming; Data Mining; Fuzzy Logic; Adaptive Control; Pattern Recognition; Smart Engineering System Design. These papers are intended to provide a forum for researchers in the field to exchange ideas on smart engineering system design.

Advances in Neural Networks ISNN

937 6 Component Analysis Guided GA - ICA Algorithms . . . . . . . . . . . . . . 943 Juan
Manuel Górriz , Carlos García Puntonet , Angel Manuel Gómez , and Oscar
Pernía A Cascaded Ensemble Learning for Independent Component Analysis .

Author:

Publisher:

ISBN:

Category: Neural computers

Page:

View: 993


Neural Computation

Independent component analysis in the presence of gaussian noise by
maximizing joint likelihood. Neurocomputing, 22 ... In M. Kearns, M. Jordan, & S.
Solla (Eds.), Advances in neural information processing systems, 10 (pp. 273-
279).

Author:

Publisher:

ISBN:

Category: Neural computers

Page:

View: 132


Advances in Chemical Engineering III

Dependent component analysis (DCA), which is an extension of independent
component analysis (ICA) for blind source separation (BSS) and requires no
assumption on the distributions of the sources, was used to directly estimate
source ...

Author: Lin Yu

Publisher: Trans Tech Publications Ltd

ISBN: 3038261947

Category: Technology & Engineering

Page: 3138

View: 419

Selected, peer reviewed papers from the 3rd International Conference on Chemical Engineering and Advanced Materials (CEAM 2013), July 6-7, 2013, Guangzhou, China

Advances in Neural Networks ISNN 2005

We focuss our attention on theoretical analysis of convergence including a formal
prove on the convergence of the well-known GA-ICA algorithms. In addition we
introduce guiding operators, a new concept in the genetic algorithms scenario, ...

Author: Jun Wang

Publisher: Springer Science & Business Media

ISBN: 3540259120

Category: Computers

Page: 1055

View: 235

This book and its sister volumes constitute the proceedings of the 2nd International Symposium on Neural Networks (ISNN 2005). ISNN 2005 was held in the beautiful mountain city Chongqing by the upper Yangtze River in southwestern China during May 30-June 1, 2005, as a sequel of ISNN 2004 successfully held in Dalian, China. ISNN emerged as a leading conference on neural computation in the region with - creasing global recognition and impact. ISNN 2005 received 1425 submissions from authors on ?ve continents (Asia, Europe, North America, South America, and Oc- nia), 33 countries and regions (Mainland China, Hong Kong, Macao, Taiwan, South Korea, Japan, Singapore, Thailand, India, Nepal, Iran, Qatar, United Arab Emirates, Turkey, Lithuania, Hungary, Poland, Austria, Switzerland, Germany, France, Sweden, Norway, Spain, Portugal, UK, USA, Canada, Venezuela, Brazil, Chile, Australia, and New Zealand). Based on rigorous reviews, 483 high-quality papers were selected by the Program Committee for presentation at ISNN 2005 and publication in the proce- ings, with an acceptance rate of less than 34%. In addition to the numerous contributed papers, 10 distinguished scholars were invited to give plenary speeches and tutorials at ISNN 2005.

Data Mining Intrusion Detection Information Assurance and Data Networks Security

[ 13 ] Aapo Hyvärinen , Erkki Oja : Independent component analysis : algorithms
and applications . Neural Networks 13 ( 45 ) : 411 - 430 , 2000 [ 14 ] T . Kolenda ,
L . K . Hansen , S . Sigurdsson , Indepedent Components in Text . Advances in ...

Author:

Publisher:

ISBN:

Category: Data mining

Page:

View: 271


Advances in Neural Information Processing Systems 15

... Abstract Recent algorithms for sparse coding and independent component
analysis ( ICA ) have demonstrated how localized features can be learned from
natural images . However , these approaches do not take image transformations
into ...

Author: Suzanna Becker

Publisher: MIT Press

ISBN: 9780262025508

Category: Computers

Page: 1687

View: 666

Proceedings of the 2002 Neural Information Processing Systems Conference. The annual Neural Information Processing (NIPS) meeting is the flagship conference on neural computation. The conference draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists--and the presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and applications. Only about thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2002 conference.

First International Conference on Advances in Medical Signal and Information Processing

C James ' * and D Lowe ' ABSTRACT We present a system for isolating seizure
components in segments of ictal EEG . Through the implementation of
Independent Component Analysis ( ICA ) we first separate multichannel EEG
segments into ...

Author:

Publisher: Inst of Engineering & Technology

ISBN:

Category: Technology & Engineering

Page: 332

View: 277

The 48 papers in this volume are taken from the International Conference on Advances in Medical Signal and Information Processing (MEDSIP 2000).

Advances in Intelligent Signal Processing and Data Mining

... Rao Blackwellization, to the biologically inspired paradigm of Neural Networks
and decomposition techniques such as Empirical Mode Decomposition,
Independent Component Analysis (ICA) and Singular Spectrum Analysis.
Advances and ...

Author: Petia Georgieva

Publisher: Springer

ISBN: 3642286968

Category: Technology & Engineering

Page: 354

View: 528

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.