Adaptive learning methods for nonlinear system modeling. (2018)

• Record Type: Book
• Further Information: Note: Edited by Danilo Comminiello, Jose C. Principe.
• Editors: Comminiello, Danilo; Príncipe, J. C (José C.)
• Contents: 1. Introduction PART I – LINEAR-IN-THE-PARAMETERS NONLINEAR FILTERS 2. Orthogonal LIP Nonlinear Filters 3. Spline Adaptive Filters: Theory and Applications 4. Recent Advances on LIP Nonlinear Filters and Their Applications: Efficient Solutions and Significance Aware Filtering PART II – ADAPTIVE ALGORITHMS IN THE REPRODUCING KERNEL HILBERT SPACE 5. Maximum Correntropy Criterion Based Kernel Adaptive Filters 6. Kernel Subspace Learning for Pattern Classification 7. A Random Fourier Features Perspective of KAFs with Application to Distributed Learning over Networks 8. Kernel-based Inference of Functions over Graphs PART III – NONLINEAR MODELING WITH MULTIPLE LEARNING MACHINES 9. Online Nonlinear Modeling via Self-Organizing Trees 10. Adaptation and Learning Over Networks for Nonlinear System Modeling 11. Cooperative Filtering Architectures for Complex Nonlinear Systems PART IV – NONLINEAR MODELING BY NEURAL NETWORKS 12. Echo State Networks for Multidimensional Data: Exploiting Noncircularity and Widely Linear Models 13. Identification of Short-Term and Long-Term Functional Synaptic Plasticity from Spiking Activities 14. Adaptive H ∞ Tracking Control of Nonlinear Systems using Reinforcement Learning 15. Adaptive Dynamic Programming for Optimal Control of Nonlinear Distributed Parameter Systems
• Publisher Details: Amsterdam : Butterworth-Heinemann
• Publication Date: 2018
• Extent: 1 online resource
• Subjects: 629.836; Nonlinear systems -- Mathematical models; Adaptive control systems
• Languages: English
• ISBNs: 9780128129777
• Related ISBNs: 9780128129760
• Notes: Note: Description based on CIP data; resource not viewed.
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