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Home > Computing and Information Technology > Computer science > Artificial intelligence > Neural networks and fuzzy systems > Resistive Switching Systems for In-Memory Computation and Artificial Intelligence: (IOP ebooks)
Resistive Switching Systems for In-Memory Computation and Artificial Intelligence: (IOP ebooks)

Resistive Switching Systems for In-Memory Computation and Artificial Intelligence: (IOP ebooks)


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About the Book

This book provides a detailed review on neuromorphic system theory and its practical realization along with hardware-level implementations. This book will allow readers to understand the new fundamental concepts related to memristive systems and their ongoing and futuristic applications. In summary, this is a comprehensive description of emerging memristor memory technology with its fundamentals, behaviour modeling, physical modeling and potential applications. This book will facilitate classroom adaptations, and its content makes it suitable for advanced diploma, under-graduate and post-graduate courses in various universities.

Key Features:

  • Includes fundamental theoretical concepts as well as materials and device properties, physical and analytical modelling, algorithmic aspects, circuits, and architectures.
  • Encompasses a broad range of applications such as brain-inspired computing, in-memory computation tasks, logic circuit realization and image computation and processing.
  • Interdisciplinary approach embracing material science, VLSI circuit and systems, electrical and computer engineering, mathematics and physics.


Table of Contents:

Preface

Acknowledgments

Author biography

1 Introduction to resistive switching devices

2 Integrated selector-based resistive random-access memory (RRAM) and memristors

3 Memristive devices in brain-inspired computing

4 Memristive devices as computational memory

5 Memristor-based in-memory logic operation and applications

6 Vector multiplications using memristive devices

7 Stochasticity in memristive systems

8 Integration of neuromorphic chips at the system level

9 Memristive systems in image processing and artificial intelligence



About the Author :

Shaibal Mukherjee completed his PhD in Electrical and Computer Engineering, University of Oklahoma, USA in 2009 followed by his postdoctoral research work in the Center of Quantum Devices, Electrical Engineering and Computer Science, Northwestern University, USA. In September 2010, he joined IIT Indore and currently is a Professor in the Department of Electrical Engineering at IIT Indore. The Hybrid Nanodevice Research Group (HNRG) led by Shaibal at IIT Indore explores new physics of micro- and nano-structured materials, and to apply this knowledge in realizing advanced tools and devices for chemical, biological, optical, electronic and energy applications. He has published 145+ research articles in peer-reviewed journals, 110+ international conference proceedings, 11 book/book chapters and 16 patents (Granted: 14 and Filed/Published: 2). He is the recipient of various prestigious awards such as “2025 Friedrich Wilhelm Bessel Research Award by Alexander von Humboldt Foundation”, “2024 Microelectronic Engineering Journal Middle Career Investigator Award and Lectureship”, “2024 TIH-IoT CHANAKYA Faculty Fellowship, IIT Bombay”, “2023 Japan Society for the Promotion of Science (JSPS) Invitational Fellowship Award”, “2021 JSPS Invitational Fellowship Award”, “2020 DUO-India Professor Fellowship Award”, “2019 DAAD Fellowship Award”, “2018 Materials Research Society of India (MRSI) Medal”, “2016 Young Faculty Research Fellowship (YFRF) under Visvesvaraya PhD Scheme for Electronics and IT”. He is an Associate Editor for IEEE Sensors Journal, a senior member of IEEE, a regular member of Optical Society of America and Life Fellow of MRSI and Optical Society of India. He is a fellow of IoP, JSPS, Humboldt Foundation, RSC and IET. He is the founding Chair of IEEE Madhya Pradesh (MP) Section Electron Devices Society (EDS) chapter. He is also the Director, Co-Founder and Mentor of QuanTechL2M Innovations Pvt. Ltd.


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Product Details
  • ISBN-13: 9780750361675
  • Publisher: Institute of Physics Publishing
  • Publisher Imprint: Institute of Physics Publishing
  • Height: 254 mm
  • Series Title: IOP ebooks
  • Width: 178 mm
  • ISBN-10: 0750361670
  • Publisher Date: 06 Jan 2026
  • Binding: Hardback
  • Language: English
  • Series Title: IOP Series in Next Generation Computing


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