ENGLISH

Advances in Independent Component Analysis

By William D. Penny , PhD , CEng , MSc , BA , MIEE , Mark Girolami BSc (Hons) , Richard M. Everson , Stephen J. Roberts (auth.) , MIMechE (eds.)

Book information

Publisher
Springer-Verlag London
Year
2000
ISBN
978-1-85233-263-1, 978-1-4471-0443-8
DOI
10.1007/978-1-4471-0443-8
Language
english
Format
PDF
Filesize
12 MB (12291002 bytes)
Series
Perspectives in Neural Computing
Edition
1
Pages
284\285
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00
Artificial Intelligence (incl. Robotics); Computer

Description

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.

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