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Reservoir Computing : Theory , Physical Implementations , and Applications / Editors Kohei Nakajima , Ingo Fischer

Contributor(s): Material type: TextTextLanguage: English Series: Natural Computing SeriesPublication details: New York : Springer , 2021Description: 477 Pages ; 30 cmISBN:
  • 9789811316869
  • 9789811316876
ISSN:
  • 16197127
Subject(s): LOC classification:
  • Q342 .R47 2021
Summary: 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
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Item type Current library Call number Copy number Status Barcode
Books Books Fayza Aboulnaga Central Library | مكتبة فايزة أبو النجا المركزية بالحرم الجامعي Q342 .R47 2021 (Browse shelf(Opens below)) C. 1 Available 10003569

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

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