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Handbook of Memristor Networks

  • Covers all aspects of memristor networks in detail
  • Explains how to realise computing devices from memristors
  • Presents the latest developments in the field of memristor networks

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Table of contents (47 chapters)

  1. Front Matter

    Pages i-xiv
  2. The Fourth Element

    • Leon Chua
    Pages 1-14
  3. Aftermath of Finding the Memristor

    • R. Stanley Williams
    Pages 159-163
  4. Three Fingerprints of Memristor

    • Shyam Prasad Adhikari, Maheshwar Pd. Sah, Hyongsuk Kim, Leon O. Chua
    Pages 165-196
  5. The Detectors Used in the First Radios were Memristors

    • Gaurav Gandhi, Varun Aggarwal, Leon O. Chua
    Pages 231-245
  6. Why are Memristor and Memistor Different Devices?

    • Shyam Prasad Adhikari, Hyongsuk Kim
    Pages 247-265
  7. The Art and Science of Constructing a Memristor Model: Updated

    • Suhas Kumar, Gary Gibson, Catherine E. Graves, Matthew D. Pickett, John Paul Strachan, R. Stanley Williams
    Pages 267-285
  8. Brains Are Made of Memristors

    • Maheshwar Pd. Sah, Hyongsuk Kim, Leon Chua
    Pages 315-350
  9. Synapse as a Memristor

    • Weiran Cai, Ronald Tetzlaff
    Pages 351-367
  10. Self-organization and Emergence of Dynamical Structures in Neuromorphic Atomic Switch Networks

    • Adam Z. Stieg, Audrius V. Avizienis, Henry O. Sillin, Renato Aguilera, Hsien-Hang Shieh, Cristina Martin-Olmos et al.
    Pages 391-427
  11. Spike-Timing-Dependent-Plasticity with Memristors

    • Teresa Serrano-Gotarredona, Timothée Masquelier, Bernabe Linares-Barranco
    Pages 429-467
  12. Designing Neuromorphic Computing Systems with Memristor Devices

    • Amr Mahmoud Hassan, Chenchen Liu, Chaofei Yang, Hai (Helen) Li, Yiran Chen
    Pages 469-494
  13. Brain-Inspired Memristive Neural Networks for Unsupervised Learning

    • Daniele Ielmini, Valerio Milo
    Pages 495-525

About this book

This Handbook presents all aspects of memristor networks in an easy to read and tutorial style. Including many colour illustrations, it covers the foundations of memristor theory and applications, the technology of memristive devices, revised models of the Hodgkin-Huxley Equations and ion channels, neuromorphic architectures, and analyses of the dynamic behaviour of memristive networks. It also shows how to realise computing devices, non-von Neumann architectures and provides future building blocks for deep learning hardware.

With contributions from leaders in computer science, mathematics, electronics, physics, material science and engineering, the book offers an indispensable source of information and an inspiring reference text for future generations of computer scientists, mathematicians, physicists, material scientists and engineers working in this dynamic field.





Editors and Affiliations

  • Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA

    Leon Chua

  • Democritus University of Thrace, Xanthi, Greece

    Georgios Ch. Sirakoulis

  • Department of Computer Science and Creative Technologies, University of the West of England, Bristol, UK

    Andrew Adamatzky

About the editors

Leon Chua is a Professor in Electrical and Computer Science at Berkeley. His research interests include Cellular Neural/Nonlinear Networks, Nonlinear Circuits and Systems, Nonlinear Dynamics, Bifurcation and Chaos.

Dr. Georgios Ch. Sirakoulis is an Associate Professor with tenure in the Department of Electrical and Computer Engineering, Democritus University of Thrace. His research interests include Nanoelectronics and nanotechnology, future and emergent electronic devices, circuits, models and architectures (memristors, quantum cellular automata etc.), Novel and Emergent micro-nano systems and circuits, beyond CMOS computing devices and circuits, Memristors, Green and Unconventional computing, High performance Computing, Novel paradigms of computing, Cyber-Physical and Embedded Systems, Bioinspired computation/ biocomputation and bioengineering, Cellular Automata Theory and Applications, FPGAs, Modelling and Simulation, Complex systems. 

Andrew Adamatzky is a Professor in Unconventional Computing in the Department of Computer Science, Director of the Unconventional Computing Centre, and a member of Bristol Robotics Lab. His research is in reaction-diffusion computing, cellular automata, physarum computing, massive parallel computation, applied mathematics, collective intelligence and robotics.

Bibliographic Information

  • Book Title: Handbook of Memristor Networks

  • Editors: Leon Chua, Georgios Ch. Sirakoulis, Andrew Adamatzky

  • DOI: https://doi.org/10.1007/978-3-319-76375-0

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Hardcover ISBN: 978-3-319-76374-3Published: 26 November 2019

  • eBook ISBN: 978-3-319-76375-0Published: 12 November 2019

  • Edition Number: 1

  • Number of Pages: XIV, 1368

  • Number of Illustrations: 175 b/w illustrations, 615 illustrations in colour

  • Topics: Computer Hardware, Theory of Computation, Circuits and Systems

Buy it now

Buying options

eBook USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access