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Produktdetails
- Verlag: Springer London
- Erscheinungstermin: 23. August 2007
- Englisch
- ISBN-13: 9781846283475
- Artikelnr.: 37341386
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?.
From the contents
Part 1 Evolving Connectionist Systems: Methods and Techniques Introduction: Evolving Information Processes and Evolving Intelligence Feature selection, Model Creation and Model Validation: Statistical Learning Approaches Unsupervised Learning: Clustering and Vector Quantisation Supervised Learning in Connectionist Systems Recurrent Neural Networks. Finite Automata. Spiking Neural Networks Neuro-Fuzzy Inference Systems Evolutionary Computation for Model and Feature Optimisation - Evolving Integrated Multi-modal Systems Part II Inspiration from-, and Applications to Natural Biological Systems Data Analysis, Modelling and Knowledge Discovery in Bioinformatics Dynamic Modelling of Brain Functions and Cognitive Processes Modelling the Emergence of Acoustic Segments from Spoken Languages Part III Evolving Intelligent Systems Adaptive Speech Recognition Adaptive Image Processing Adaptive Multi-modal Systems Evolving Robotics and Socio-Economic Systems.
Part 1 Evolving Connectionist Systems: Methods and Techniques Introduction: Evolving Information Processes and Evolving Intelligence Feature selection, Model Creation and Model Validation: Statistical Learning Approaches Unsupervised Learning: Clustering and Vector Quantisation Supervised Learning in Connectionist Systems Recurrent Neural Networks. Finite Automata. Spiking Neural Networks Neuro-Fuzzy Inference Systems Evolutionary Computation for Model and Feature Optimisation - Evolving Integrated Multi-modal Systems Part II Inspiration from-, and Applications to Natural Biological Systems Data Analysis, Modelling and Knowledge Discovery in Bioinformatics Dynamic Modelling of Brain Functions and Cognitive Processes Modelling the Emergence of Acoustic Segments from Spoken Languages Part III Evolving Intelligent Systems Adaptive Speech Recognition Adaptive Image Processing Adaptive Multi-modal Systems Evolving Robotics and Socio-Economic Systems.
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?.
From the contents
Part 1 Evolving Connectionist Systems: Methods and Techniques Introduction: Evolving Information Processes and Evolving Intelligence Feature selection, Model Creation and Model Validation: Statistical Learning Approaches Unsupervised Learning: Clustering and Vector Quantisation Supervised Learning in Connectionist Systems Recurrent Neural Networks. Finite Automata. Spiking Neural Networks Neuro-Fuzzy Inference Systems Evolutionary Computation for Model and Feature Optimisation - Evolving Integrated Multi-modal Systems Part II Inspiration from-, and Applications to Natural Biological Systems Data Analysis, Modelling and Knowledge Discovery in Bioinformatics Dynamic Modelling of Brain Functions and Cognitive Processes Modelling the Emergence of Acoustic Segments from Spoken Languages Part III Evolving Intelligent Systems Adaptive Speech Recognition Adaptive Image Processing Adaptive Multi-modal Systems Evolving Robotics and Socio-Economic Systems.
Part 1 Evolving Connectionist Systems: Methods and Techniques Introduction: Evolving Information Processes and Evolving Intelligence Feature selection, Model Creation and Model Validation: Statistical Learning Approaches Unsupervised Learning: Clustering and Vector Quantisation Supervised Learning in Connectionist Systems Recurrent Neural Networks. Finite Automata. Spiking Neural Networks Neuro-Fuzzy Inference Systems Evolutionary Computation for Model and Feature Optimisation - Evolving Integrated Multi-modal Systems Part II Inspiration from-, and Applications to Natural Biological Systems Data Analysis, Modelling and Knowledge Discovery in Bioinformatics Dynamic Modelling of Brain Functions and Cognitive Processes Modelling the Emergence of Acoustic Segments from Spoken Languages Part III Evolving Intelligent Systems Adaptive Speech Recognition Adaptive Image Processing Adaptive Multi-modal Systems Evolving Robotics and Socio-Economic Systems.