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Primer to Neuromorphic Computing
- 1st Edition - November 1, 2024
- Editors: Harish Garg, Jyotir Moy Chatterjee, R Sujatha, Shatrughan Modi
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 1 4 8 0 - 6
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 1 4 8 2 - 0
Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientifi… Read more
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Request a sales quotePrimer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning, and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture.
Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains.
- Discusses potential neuromorphic applications in computing
- Presents current trends and models in neuromorphic computing and neural network hardware architectures
- Shows the development of novel devices and hardware to enable neuromorphic computing
- Offers information about computation and learning principles for neuromorphic systems
- Provides information about Neuromorphic implementations of neurobiological learning algorithms
- Discusses biologically inspired neuromorphic systems and devices (including adaptive bio interfacing and hybrid systems consisting of living matter and synthetic matter)
IT industry professionals, academic professors, research scholars, system modelling and simulation experts. This book on the neuromorphic computing can be offered as an elective course for graduate students
1. Review of existing neuromorphic systems
2. Integrating neuromorphic components
3. Evolution and goals of neuromorphic systems
4. Neuromorphic systems vs artificial neural network
5. Hardware based on physical properties for neuromorphic computers
6. Contrasting neuromorphic system from other systems
7. Neuromorphic systems for Autonomous vehicles
8. Neuromorphic systems for smart home devices
9. Neuromorphic systems for natural language understanding
10. Neuromorphic systems for data analytics
11. Neuromorphic systems for process optimization
12. Neuromorphic systems for real-time image processing
13. Technological limitations in building and employing neuromorphic systems
14. Analysis on physical, electronic, and technological limitations in building neuromorphic systems
2. Integrating neuromorphic components
3. Evolution and goals of neuromorphic systems
4. Neuromorphic systems vs artificial neural network
5. Hardware based on physical properties for neuromorphic computers
6. Contrasting neuromorphic system from other systems
7. Neuromorphic systems for Autonomous vehicles
8. Neuromorphic systems for smart home devices
9. Neuromorphic systems for natural language understanding
10. Neuromorphic systems for data analytics
11. Neuromorphic systems for process optimization
12. Neuromorphic systems for real-time image processing
13. Technological limitations in building and employing neuromorphic systems
14. Analysis on physical, electronic, and technological limitations in building neuromorphic systems
- No. of pages: 370
- Language: English
- Edition: 1
- Published: November 1, 2024
- Imprint: Academic Press
- Paperback ISBN: 9780443214806
HG
Harish Garg
Dr. Garg is one of the pioneer researchers in the world. He ranks in the World's Top 2% Scientist List and Rank #1 in India & World Rank #229 published by Stanford University in the consecutive three years 2020, 2021, and 2022. He is the recipient of the Obada-Prize 2022 – Young Distinguished Researchers. He is also the recipient of the Top-Cited paper by an India-based author (2015 – 2019) from Elsevier Publisher. He also serves as an advisory board member of the Universal Scientific Education and Research Network (USERN).
Dr. Garg's research interests include Computational Intelligence, Multi-criteria decision making, Evolutionary algorithms, Reliability analysis, Expert systems, and decision support systems, Computing with words, and Soft Computing. He has authored more than 400 papers (over 350 are SCI) published in refereed International Journals including IEEE Transactions, Elsevier, Springer, etc. He has also authored seven book chapters. Also, he edited 8 books from Elsevier, Springer, and other publishers. His Google citations are over 17650 with an H-index of- 75. Dr. Garg also serves on editorial boards of several leading international journals, this includes the Founding Editor-in-Chief of the Journal of Computational and Cognitive Engineering. He is also the Associate Editor of IEEE Transaction of Fuzzy Systems, Soft Computing, Alexandria Engineering Journal, Journal of Intelligent & Fuzzy Systems, Complex and Intelligent Systems, Journal of Industrial & Management Optimization, CAAI Transactions on Intelligence Technology, etc.
Dr. Garg also shared his knowledge (Teaching as well as Research) with the whole world through their YouTube channel https://www.youtube.com/c/DrHarishGarg. For more details about him, kindly follow his webpage https://sites.google.com/site/harishg58iitr/home
Affiliations and expertise
Associate Professor, School of Mathematics, Thapar Institute of Engineering and Technology, Patiala, Punjab, IndiaJM
Jyotir Moy Chatterjee
Jyotir Moy Chatterjee received M. Tech in Computer Science & Engineering from Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha in 2016, and a B. Tech in Computer Science & Engineering from Dr. MGR Educational & Research Institute, Maduravoyal, Chennai in 2013. His research interests include Machine Learning, Deep Learning, and the Internet of Things. He is credited with 26 SCIE journal papers, 9 Scopus journal papers, 43 Google Scholar journal papers, 5 international conference papers, 3 authored books, 21 edited books, 26 book chapters, and 1 Indian patent (published). He is currently serving as a Commissioning Editor of the Journal of Information Technology Research (JITR- IGI Global) and Academic Editor of the Computational Intelligence and Neuroscience (Hindawi). He is also serving as a reviewer for various prestigious Elsevier, Springer, IEEE, and Techpress journals and is also associated with various international conferences as a reviewer, TPC, Advisory board, etc. He is also the book series editor of the Scrivener Publishing- MACHINE LEARNING IN BIOMEDICAL SCIENCE AND HEALTHCARE INFORMATICS (https://www.scrivenerpublishing.com/series.php?id=Machine%20Learning%20in%20Biomedical%20Science%20and%20Healthcare%20Informatics), CRC Press- Chapman & Hall/CRC Cyber-Physical Systems (https://www.routledge.com/Chapman--HallCRC-Cyber-Physical-Systems/book-series/CHCPS), CRC Press- Artificial Intelligence in Smart Healthcare Systems(https://www.routledge.com/Artificial-Intelligence-in-Smart-Healthcare-Systems/book-series/CRCAISHS?publishedFilter=alltitles&pd=published,forthcoming&pg=1&pp=48&so=pub&view=list).
For more details about him, kindly follow his webpage https://sites.google.com/view/jyotirmoychatterjee
Affiliations and expertise
Assistant Professor, Department of Information Technology, Lord Buddha Education Foundation, Kathmandu, NepalRS
R Sujatha
Dr. R. Sujatha received the B.E. degree in computer science from Madras University, in 2001, the M.E. degree in computer science from Anna University, in 2009, with university ninth rank, the master’s degree in financial management from Pondicherry University, in 2005, and the Ph.D. degree in data mining from the Vellore Institute of Technology (VIT), Vellore, in 2017. She has 15 years of teaching experience and has been serving as an Associate Professor with the School of Information Technology and Engineering, VIT. She has organized and attended several workshops and faculty development programs. She actively involves herself in the growth of the institute by contributing to various committees at both academic and administrative levels. She gives technical talks in colleges for the symposium and various sessions. She acts as an advisory, editorial member, and technical committee member in conferences conducted in other educational institutions and in-house too. She has published a book Software Project Management for college students. Also, she has published research articles and papers in reputed journals. She used to guide projects for undergraduate and postgraduate students and currently guides doctoral students. She is interested in learning upcoming things and gets herself acquainted with the student’s level. Her areas of research interests include data mining, machine learning, software engineering, soft computing, big data, deep learning, and blockchain.
Affiliations and expertise
Associate Professor, School of Information Technology Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, IndiaSM
Shatrughan Modi
Dr. Shatrughan Modi is an Assistant Professor at Department of Computer Science, Indian Institute of Information Technology Una, India. Prior to that he worked at a Computer Science and Engineering Department of Thapar University, Patiala. He has more than 9 years of teaching experience and 2 years of industry experience. Her areas of research interests include data mining, neural network, pattern recognition, Autonomous vehicles, software engineering, machine learning, deep learning.
Affiliations and expertise
Assistant Professor, Department of Computer Science, Indian Institute of Information Technology, Una, Himachal Pradesh, India