Intelligence in Chip

Integrated Sensors and Memristive Computing
1. Auflage 2024
ISBN: 978-87-7022-834-3
Verlag: River Publishers

Buch, Englisch, 340 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 836 g

Intelligence in Chips: Integrated Sensors and Memristive Computing is an authoritative resource that navigates the exciting landscape of in-memory computing, neuromorphic circuits, and memristive technologies. This book curates expert insights from leading researchers like Abu Sebastian, Alex James, Alon Ascoli, Arindam Basu, Cory Merkel, Fernando Corinto, Jason Eshraghian, Rainer Waser, Spiros Nikolaidis, Stephan Menzel, and Vishal Saxena, highlighting some of the important contributions in the field. Through a comprehensive collection of talks, readers will gain deep insights into how memristive neural computing is revolutionizing artificial intelligence.

The book covers the latest innovations in memristor array computing, brain-inspired circuits, neuromorphic event-driven vision, bio-inspired computing, and nonlinear phenomena in biological systems. Each chapter is authored by a distinguished expert, offering a multi-perspective analysis on how emerging technologies are pushing the boundaries of edge-AI and mixed-signal hardware.

Whether you're a researcher, engineer, or student, this book is an essential guide that explores the confluence of circuit theory, artificial intelligence, and memristor technology, providing readers with practical methodologies and visionary outlooks for the future.

Zielgruppe

Academic, Postgraduate, and Professional Practice & Development

Autoren/Hrsg.

James, Alex

Ascoli, Alon

Choubey, Bhaskar

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Bauelemente, Schaltkreise
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

SECTION 1: MEMRISTIVE DEVICES 1. Overview of redox-based resistive RAM (ReRAM) – Physico-chemical background and history, by Rainer Waser 2. Deep learning inference with in-memory computing, by Abu Sebastian 3. Modeling of Memristive Devices, by Stepphan Menzel SECTION 2: NONLINEAR MEMRISTIVE CIRCUITS 4. Analog Neural Computing Under Variability Intense Memristor Arrays, by Alex James 5. Edge of Chaos Clarifies the Origin for Yet-Unexplained Nonlinear Phenomena in Biological Systems, by Alon Ascoli 6. Memristor Computing Systems: at the crossroad between Circuit Theory and Artificial Intelligence, by Fernando Corinto SECTION 3: MEMRISTIVE CIRCUIT APPLICATIONS 7. Aspects of Digital Circuit Design using Memristor Ratioed Logic (MRL), by Spiros Nikolaidis 8. Neuromorphic Computing with Memristors: From Circuits to Algorithms, by Cory Merkel 9. In-memory computing meets Neuromorphic Event-Driven Vision, by Arindam Basu SECTION 4: MEMRISTIVE SYSTEMS 10. Open-Source RRAM Neuromorphic Accelerators, by Jason Eshraghian 11. Mixed-Signal Neuromorphic Computing: Devices Algorithms and Circuits, by Vishal Saxena About the Editors About the Authors

Über Autor(innen)

Alex James (Senior Member, IEEE) received the Ph.D. degree in electronics engineering from the Queensland Micro and Nanotechnology Center, Griffith University, Brisbane, QLD, Australia.,He is a Professor of AI hardware with the School of Electronic Systems and Automation and Dean (Academic), Digital University Kerala, Trivandrum, India. He is a Prof-in-Charge of Maker Village that supports more than 80 hardware startups. He is the Chief Investigator with the Center for Intelligent IoT Sensors and the India Innovation Centre for Graphene, developing new products to the market. His research interests include broad range of brain-inspired systems, memristive systems, intelligent semiconductor devices, analog circuits, and imaging systems.,Dr. James was the Founding Chair of IEEE Kerala Section Circuits and Systems Society. He is a Member of the IEEE CASS Technical Committee on Nonlinear Circuits and Systems, IEEE CASS Technical Committee on Cellular Nanoscale Networks and Memristor Array Computing, IEEE Consumer Technology Society Technical Committee on Quantum in Consumer Technology (QCT), Technical Committee on Machine Learning, Deep Learning and AI in CE (MDA), and Member of BCS Fellows Technical Advisory Group (F-TAG). He was an Editorial Member of the Information Fusion, Elsevier, IEEE Transactions on Emerging Topics in Computational Intelligence (2017–18) (Guest Associate Editor) and IEEE Transactions on Circuits and Systems 1 (2018–2023). He is currently an Associate EIC of IEEE Open Journal of Circuits and Systems (2024–present), Associate Editor for IEEE Transactions on Biomedical Circuits and Systems (2024–present), Associate Editor for Frontiers in Neuroscience (Section: Neuromorphic Systems) and IEEE ACCESS. He is a Life Member of ACM, Senior Fellow of HEA, Fellow of the British Computer Society (FBCS), and Fellow of IET (FIET).(Based on document published on 6 February 2024).

Alon Ascoli (Senior Member, IEEE) received the Ph.D. degree in electronic engineering from University College Dublin in 2006. He was conferred the Habilitation title as a Full (Associate) Professor in electrical circuit theory from the Italian Ministry of Education in 2023 (2017) and the Habilitation title as a Full Professor in nonlinear circuit theory from TU Dresden in 2022. Since December 2023, he is an Associate Professor with the Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy. From December 2012 to November 2023, he was affiliated with the Faculty of Electrical and Computer Engineering, Technische Universität Dresden (TU Dresden). He develops circuit- and system-theoretic methods for the analysis and design of bio-inspired memristive circuits, enabling to deepen our understanding of biological systems and/or to extend the functionalities of traditional electronic systems. He was honored with the Darlington Best Paper Award from TCAS in 2023, the Best Paper Award from IJCTA in 2007, and the Best Paper Award from MOCAST in 2022 and 2020. He was the President of the IEEE Cellular Nanoscale Networks and Array (and Memristor Array) Computing Technical Committee, from 2019 to 2021 and from 2021 to 2023. He has been serving as an Associate Editor for IEEE Transactions on Circuits and Systems—I: Regular Papers, since 2023

Bhaskar Choubey received the D.Phil. degree from the University of Oxford and the B.Tech. degree from the Regional Engineering College, Warangal, India. He is currently the Chair of Analogue Circuits and Image Sensors with Siegen University. In the past, he was with the University of Glasgow, Somerville College, and the University of Oxford. He received the Rhodes Scholar for the D.Phil. degree. He also received the IEEE Sensors Council GOLD Early Career Achievement Award and the Myril B. Reed Best Paper Award from the IEEE Midwest Symposium of Circuits and Systems. He is currently the Chair of the IEEE EPPC Working Group on ICT in Europe. He is an Associate Editor of the IEEE Sensors Journal.