Kasabov Evolving Connectionist Systems

The Knowledge Engineering Approach
2. Auflage 2007
ISBN: 978-1-84628-347-5
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 451 Seiten, Web PDF

Reihe: Computer Science (R0)

Zielgruppe

Research

Autoren/Hrsg.

Kasabov, Nikola K.

Inhaltsverzeichnis

Evolving Connectionist Methods.- Feature Selection, Model Creation, and Model Validation.- Evolving Connectionist Methods for Unsupervised Learning.- Evolving Connectionist Methods for Supervised Learning.- Brain Inspired Evolving Connectionist Models.- Evolving Neuro-Fuzzy Inference Models.- Population-Generation-Based Methods: Evolutionary Computation.- Evolving Integrated Multimodel Systems.- Evolving Intelligent Systems.- Adaptive Modelling and Knowledge Discovery in Bioinformatics.- Dynamic Modelling of Brain Functions and Cognitive Processes.- Modelling the Emergence of Acoustic Segments in Spoken Languages.- Evolving Intelligent Systems for Adaptive Speech Recognition.- Evolving Intelligent Systems for Adaptive Image Processing.- Evolving Intelligent Systems for Adaptive Multimodal Information Processing.- Evolving Intelligent Systems for Robotics and Decision Support.- What Is Next: Quantum Inspired Evolving Intelligent Systems?.

Über Autor(innen)

Professor Nik Kasabov is the Founding Director and Chief Scientist of the Knowledge Engineering and Discovery Research Institute, Auckland, NZ. He holds a number of key positions, including Chair of the Adaptive Systems Task Force of the Neural Network Technical Committee of the IEEE. He has published extensively, and been Programme Chair of over 50 high-profile conferences.