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Computer Science

Evolving Connectionist Systems
The Knowledge Engineering Approach

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Contents
ESM

I-XXI
Front matter
15-228
Part 1 / Evolving Connectionist Methods
15-228
Front matter
15-52
Feature Selection, Model Creation, and Model Validation
53-82
Evolving Connectionist Methods for Unsupervised Learning
83-126
Evolving Connectionist Methods for Supervised Learning
127-140
Brain Inspired Evolving Connectionist Models
141-176
Evolving Neuro-Fuzzy Inference Models
177-202
Population-Generation-Based Methods: Evolutionary Computation
203-228
Evolving Integrated Multimodel Systems
231-403
Part 2 / Evolving Intelligent Systems
231-403
Front matter
231-273
Adaptive Modelling and Knowledge Discovery in Bioinformatics
275-302
Dynamic Modelling of Brain Functions and Cognitive Processes
303-323
Modelling the Emergence of Acoustic Segments in Spoken Languages
325-340
Evolving Intelligent Systems for Adaptive Speech Recognition
341-359
Evolving Intelligent Systems for Adaptive Image Processing
361-380
Evolving Intelligent Systems for Adaptive Multimodal Information Processing
381-391
Evolving Intelligent Systems for Robotics and Decision Support
393-403
What Is Next: Quantum Inspired Evolving Intelligent Systems?
405-457
Back matter

About This Book

Title

Evolving Connectionist Systems
The Knowledge Engineering Approach

Author

Nikola Kasabov(1)

Author Affiliations

Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand

Collection

Computer Science

Subjects

Copyright Year

2007

DOI

10.1007/978-1-84628-347-5

ISBN

978-1-84628-345-1 (Print) 978-1-84628-347-5 (Online)

Additional Links

About This Book

Publisher

Springer London

SpringerLink Date

Thursday, August 23, 2007

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