Evolving Connectionist Systems

Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines

N. Kasabov

308 pages, parution le 02/12/2002

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Résumé

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.

Contents

Part I Evolving Connectionist Systems: Methods and Techniques
1 Evolving Processes and Evolving Connectionist Systems
2 Evolving Connectionist Systems for Unsupervised Learning
3 Evolving Connectionist Systems for Supervised Learning
4 Recurrent Evolving Systems, Reinforcement Learning and Evolving Automata
5 Evolving Neuro-Fuzzy Inference Systems
6 Evolutionary Computation and Evolving Connectionist Systems
7 Evolving Connectionist Machines – Framework, Biological Motivation and Implementation Issues
Part II Evolving Connectionist Systems: Applications in Bioinformatics, Brain Study, and intelligent Systems
8 Data Analysis, Modelling and Knowledge Discovery in Bioinformatics
9 Dynamic Modelling of Brain Functions and Cognitive Processes
10 Modelling the Emergence of Acoustic Segments (Phonemes) in Spoken Languages
11 On-Line Adaptive Speech Recognition
12 On-Line Image and Video Data Processing
13 Evolving Systems for Integrated Multi-Modal Information Processing

L'auteur - N. Kasabov

University of Otago, Dunedin, New Zealand

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	N. Kasabov
Parution	02/12/2002
Nb. de pages	308
Format	15,5 x 23,5
Couverture	Broché
Poids	485g
Intérieur	Noir et Blanc
EAN13	9781852334000
ISBN13	978-1-85233-400-0