Evolving Connectionist Systems: Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines

Kasabov, Nikol;a

ISBN 10: 1852334002 / ISBN 13: 9781852334000

Published by Springer, London, 2003

About this Item

An ex-library copy in original paper covers, with the usual ex-libris markings. The binding is sound (with no spine creasing), the text is clean/unmarked, and there is little cover wear.

Seller Inventory # 062809

Bibliographic Details

• Title: Evolving Connectionist Systems: Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines
• Publisher: Springer, London
• Publication Date: 2003
• Language: English
• ISBN 10: 1852334002
• ISBN 13: 9781852334000
• Binding: Trade Paperback
• Edition: First Edition.
• Condition: Good
• Dust Jacket Condition: No Dust Jacket
• Book Type: Book

About this title

Synopsis

Many methods and models have been proposed for solving difficult problems such as prediction, planning and knowledge discovery in application areas such as bioinformatics, speech and image analysis. Most, however, are designed to deal with static processes which will not change over time. Some processes - such as speech, biological information and brain signals - are not static, however, and in these cases different models need to be used which can trace, and adapt to, the changes in the processes in an incremental, on-line mode, and often in real time. This book presents generic computational models and techniques that can be used for the development of evolving, adaptive modelling systems. The models and techniques used are connectionist-based (as the evolving brain is a highly suitable paradigm) and, where possible, existing connectionist models have been used and extended. The first part of the book covers methods and techniques, and the second focuses on applications in bioinformatics, brain study, speech, image, and multimodal systems. It also includes an extensive bibliography and an extended glossary. Evolving Connectionist Systems is aimed at anyone who is interested in developing adaptive models and systems to solve challenging real world problems in computing science or engineering. It will also be of interest to researchers and students in life sciences who are interested in finding out how information science and intelligent information processing methods can be applied to their domains.