Evolving Connectionist Systems (eBook)
XXII, 451 Seiten
Springer London (Verlag)
978-1-84628-347-5 (ISBN)
This second edition of the must-read work in the field presents generic computational models and techniques that can be used for the development of evolving, adaptive modeling systems, as well as new trends including computational neuro-genetic modeling and quantum information processing related to evolving systems. New applications, such as autonomous robots, adaptive artificial life systems and adaptive decision support systems are also covered.
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.
This second edition of the must-read work in the field presents generic computational models and techniques that can be used for the development of evolving, adaptive modeling systems, as well as new trends including computational neuro-genetic modeling and quantum information processing related to evolving systems. New applications, such as autonomous robots, adaptive artificial life systems and adaptive decision support systems are also covered.
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.
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?.
| Erscheint lt. Verlag | 23.8.2007 |
|---|---|
| Zusatzinfo | XXII, 451 p. 185 illus. |
| Verlagsort | London |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Software Entwicklung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Naturwissenschaften ► Biologie | |
| Technik | |
| Schlagworte | Adaptive Time-Series Analysis • Artificial Life • Bioinformatics • Connectionist Systems • Fuzzy Logic • Image Processing • Information Processing • Intelligence • Intelligent Systems • Knowledge Engineering • Learning Systems • Modeling • Neural networks • Robotics • Speech Recognition |
| ISBN-10 | 1-84628-347-7 / 1846283477 |
| ISBN-13 | 978-1-84628-347-5 / 9781846283475 |
| Haben Sie eine Frage zum Produkt? |
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