Contents

## **Preface XI**




Preface

The growth in internet of things, devices and systems has resulted in the need to develop energy-efficient near-sensor processing devices and circuits. This requires the development of alternative computing implementations such as neuromorphic computing, quantum com‐ puting and approximate computing. Memristor devices and their natural properties to change states can be used to mimic neural circuits and neural networks. It is estimated that these networks can be scaled in the future to create large-scale neurocomputing solution. This book covers a range of models, circuits and systems built with memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications. The resistive switching property is an important aspect of the memristors, and there are several designs of this discussed in this book, such as in metal oxide/organic semiconductor nonvolatile memories, nanoscale switching and degradation of resistive random access memory and graphene oxide-based memristor. The modelling of the memristors is required to ensure that the devices can be put to use and improve emerg‐ ing application. In this book, various memristor models are discussed, from a mathematical framework to implementations in SPICE and verilog, that will be useful for the practitioners and researchers to get a grounding on the topic. The applications of the memristor models in various neuromorphic networks are discussed covering various neural network models, im‐

This book is a response to the growing field of memristor networks and applications, pro‐ viding insights into a collection of topics in memristor devices, circuits and systems. It is suitable for the introductory studies and equally useful for the researchers to discuss the

> **Alex Pappachen James** Nazarbayev University

> > Kazakhstan

plementations in A/D converter and hierarchical temporal memories.

emerging topics in the memristor networks.

Chapter 14 **Neural Network-Based Analog-to-Digital Converters 297** Aigerim Tankimanova and Alex Pappachen James
