Reservoir Computing : Theory, Physical Implementations, and Applications /

This book is the first comprehensive book about reservoir computing (RC). RC is a powerful and broadly applicable computational framework based on recurrent neural networks. Its advantages lie in small training data set requirements, fast training, inherent memory and high flexibility for various ha...

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Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Nakajima, Kohei (Editor), Fischer, Ingo (Editor)
Format:	eBook
Language:	English
Published:	Singapore : Springer Singapore : Imprint: Springer, 2021.
Edition:	1st ed. 2021.
Series:	Natural Computing Series
Subjects:	Artificial intelligence. Control engineering. Robotics. Mechatronics. Machine learning. Neural networks (Computer science) . Quantum computers. Spintronics. Artificial Intelligence. Control, Robotics, Mechatronics. Machine Learning. Mathematical Models of Cognitive Processes and Neural Networks. Quantum Information Technology, Spintronics. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Chapter 1: The cerebral cortex: A delay coupled recurrent oscillator network?
Chapter 2: Cortico-Striatal Origins of Reservoir Computing, Mixed Selectivity and Higher Cognitive Function
Chapter 3: Reservoirs learn to learn
Chapter 4: Deep Reservoir Computing
Chapter 5: On the characteristics and structures of dynamical systems suitable for reservoir computing
Chapter 6: Reservoir Computing for Forecasting Large Spatiotemporal Dynamical Systems
Chapter 7: Reservoir Computing in Material Substrates
Chapter 8: Physical Reservoir Computing in Robotics
Chapter 9: Reservoir Computing in MEMS
Chapter 10: Neuromorphic Electronic Systems for Reservoir Computing
Chapter 11: Reservoir Computing using Autonomous Boolean Networks Realized on Field-Programmable Gate Arrays
Chapter 12: Programmable Fading Memory in Atomic Switch Systems for Error Checking Applications
Chapter 13: Reservoir computing leveraging the transient non-linear dynamics of spin-torque nano-oscillators
Chapter 14: Reservoir computing based on spintronics technology
Chapter 15: Reservoir computing with dipole-coupled nanomagnets
Chapter 16: Performance improvement of delay-based photonic reservoir computing
Chapter 17: Computing with integrated photonic reservoirs
Chapter 18: Quantum reservoir computing
Chapter 19: Towards NMR Quantum Reservoir Computing.