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Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications - 1st Edition - ISBN: 9780128211847

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

1st Edition

Editors: Christos Volos Viet-Thanh Pham
Paperback ISBN: 9780128211847
Imprint: Academic Press
Published Date: 1st July 2021
Page Count: 500
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Table of Contents

Section I
1. The Fourth Circuit Element was Found: A Brief History
2. Implementing Memristor Emulators in Hardware
3. On the FPGA Implementation of Chaotic Oscillators based on Memristive Circuits
4. Microwave Memristive Components for Smart RF Front-end Modules
5. The Modelling of Memcapacitor Oscillator Motion with ANN and its Nonlinear Control Application
6. Rich Dynamics of Memristor based Lienard Systems
7. Hidden Extreme Multistability Generated from a Novel Memristive Two-scroll Chaotic System
8. Extreme multistability, hidden chaotic attractors and amplitude controls in an absolute memristor Van der Pol-Duffing circuit: Dynamical analysis and electronic implementation
9. Memristor based novel 4D chaotic system without equilibria: Analysis and Projective Synchronization
10. An Absolute Memristor Helmholtz Oscillator: Dynamical Analysis, Electronic Implementation and Synchronization
11. Design Guidelines for Physical Implementation of Fractional Order Integrators and Its Application in Memristive Systems
12. Control of Bursting Oscillations in Memristor Based Wien-Bridge Oscillator

Section II
13. Memristor, Mem-Systems and Neuromorphic Applications: A Review
14. Guidelines for Benchmarking Non-Ideal Analog Memristive Crossbars for Neural Networks
15. Bipolar Resistive Switching in Biomaterials: Case Studies of DNA and Melanin based BioMemristive Devices
16. Nonvolatile Memristive Logic: A Road to InMemory Computing
17. Implementation of Organic RRAM with Ink-Jet Printer: From Design to Using in RFID-Based Applications
18. Neuromorphic Vision Networks for Face Recognition
19. Synaptic Devices based on HfO2 Memristors
20. Analog Circuit Integration of Backpropagation Learning in Memristive HTM Architecture
21. Multi-stable patterns coexisting in memristor synapse-coupled Hopfield neural network
22. Fuzzy Memristive Networks
23. Synchronization of Memristive Neural Networks Using a Novel Fuzzy Integral Sliding Mode Method
24. Robust Adaptive Control of Fractional-Order Memristive Neural Networks
25. Learning Memristive Spiking Neurons and Beyond


Description

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling.

As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields.

Key Features

  • Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence
  • Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor)
  • Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence

Readership

Researchers from academia and industry, who are working in the research areas—dynamical systems, artificial intelligence, electrical engineering, computer science, information technology and neuromorphic systems .
Graduate or advanced undergraduate level as a textbook or major reference for courses such as electrical circuits, nonlinear dynamical systems, mathematical modelling, computational science, numerical simulation, and many others. Graduate students and young researchers in the following fields: Biomedical Engineering; Computational biology; Computer science; Computational Physics; Engineering Mathematics, Electrical and Electronic Engineering; Mathematics; Physics


Details

No. of pages:
500
Language:
English
Copyright:
© Academic Press 2021
Published:
1st July 2021
Imprint:
Academic Press
Paperback ISBN:
9780128211847

Ratings and Reviews


About the Editors

Christos Volos

Christos Volos

Christos Volos received the Physics Diploma degree, the M.Sc. degree in electronics, and the Ph.D. degree in chaotic electronics from the Physics Department, Aristotle University of Thessaloniki, in 1999, 2002, and 2008, respectively. He is currently an Associate Professor with the Physics Department, Aristotle University of Thessaloniki, Greece and a member of the Laboratory of Nonlinear Circuits – Systems & Complexity (LaNSCom).

Affiliations and Expertise

Associate Professor, Aristotle University of Thessaloniki, Greece

Viet-Thanh Pham

Viet-Thanh Pham

Viet-Thanh Pham is the Director of Research at Faculty of Electrical and Electronic Engineering, Phenikaa Institute for Advanced Study (PIAS), Phenikaa University, Vietnam. He received the degree in electronics and telecommunications from the Hanoi University of Technology, Vietnam, in 2005, and the Ph.D. degree in electronics, automation and control of complex systems engineering from the University of Catania, Italy, in 2013. He was a postdoctoral researcher at the Division of Dynamics, Lodz University of Technology, Poland.

Affiliations and Expertise

Director of Research, Phenikaa Institute for Advanced Study (PIAS), Phenikaa University, Vietnam