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Reservoir Computing : Theory , Physical Implementations , and Applications / Editors Kohei Nakajima , Ingo Fischer - New York : Springer , 2021 - 477 Pages ; 30 cm - Natural Computing Series .

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 hardware implementations. 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. Reviewing the current state of the art and providing a concise guide to the field, this book introduces readers to its basic concepts, theory, techniques, physical implementations and applications

ISBN: 9789811316869 9789811316876

ISSN: 16197127

Subjects--Topical Terms:
Artificial intelligence
Computational complexity

LC Class. No.: Q342 / .R47 2021