Memristors have provided a new direction of thinking for circuit designers to overcome the limits of scalability and for thinking of building systems beyond Moore’s law. Over the last decade, there has been a significant number of innovations in using memristors for building neural networks through analog computing, in-memory computing, and stochastic computing approaches. The emergence of intelligent integrated circuits is inevitable for the future of integrated circuit applications.
This book provides a collection of talks conducted as part of the IEEE Seasonal School on Circuits and System, having a focus on Intelligence in Chip: Tomorrow of Integrated Circuits. Technical topics discussed in the book include
Edge of Chaos Theory Explains Complex Phenomena in Memristor Circuits
Analog Memristive Computing
Designing energy efficient neo-cortex system with on-device learning
Integrated sensors
Challenges and recent advances in NVM based Neuromorphic Computing ICs
In-memory Computing (for deep learning)
Deep learning with Spiking Neural Networks
Computational Intelligence for Designing Integrated Circuits and Systems
Neurochip Design, Modeling, and Applications
Author(s): Alex James, Bhaskar Choubey
Series: Tutorials in Electronic Materials, Circuits and Devices
Publisher: River Publishers
Year: 2023
Language: English
Pages: 249
City: Gistrup
Cover
Title Page
Series Page
Copyright Page
Table of Contents
Introduction
Chapter 1: Edge of Chaos Theory Explains Complex Phenomena in Memristor Circuits
Chapter 2: Analog Memristive Computing
Chapter 3: Designing Energy Efficient Neocortex-Inspired Systems with On-device Learning
Chapter 4: Integrated Sensors
Chapter 5: Challenges and Recent Advances in NVM-based Neuromorphic Computing ICs
Chapter 6: In-memory Computing (for Deep Learning)
Chapter 7: Deep Learning with Spiking Neural Nets
Chapter 8: Computational Intelligence for Designing Integrated Circuits and Systems
Chapter 9: Neurochip Design, Modeling, and Applications
Appendix
About the Editors
About the Authors
