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Reservoir Computing

Theory, Physical Implementations, and Applications
BuchGebunden
458 Seiten
Englisch
Springererschienen am06.08.20211st ed. 2021
It originated from computational neuroscience and machine learning but has, in recent years, spread dramatically, and has been introduced into a wide variety of fields, including complex systems science, physics, material science, biological science, quantum machine learning, optical communication systems, and robotics.mehr
Verfügbare Formate
BuchGebunden
EUR181,89
E-BookPDF1 - PDF WatermarkE-Book
EUR171,19

Produkt

KlappentextIt originated from computational neuroscience and machine learning but has, in recent years, spread dramatically, and has been introduced into a wide variety of fields, including complex systems science, physics, material science, biological science, quantum machine learning, optical communication systems, and robotics.
Zusammenfassung
The first comprehensive book on reservoir computing

Provides an introduction and cutting-edge research in a wide range of domains

Contributed by leading researchers in the field
Details
ISBN/GTIN978-981-13-1686-9
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2021
Erscheinungsdatum06.08.2021
Auflage1st ed. 2021
ReiheNatural Computing Series
Seiten458 Seiten
SpracheEnglisch
Gewicht871 g
IllustrationenXIX, 458 p. 161 illus., 127 illus. in color.
Artikel-Nr.15800565

Inhalt/Kritik

Inhaltsverzeichnis
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.mehr

Schlagworte

Autor

Kohei Nakajima is a project associate professor at the Graduate School of Information Science and Technology in the University of Tokyo.
Ingo Fisher is a professor at the Institute for Cross-Disciplinary Physics and Complex Systems IFISC (UIB-CSIC), Palma de Mallorca, Spain.
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Herausgegeben von Nakajima, Kohei