Neuromorphic Computing Systems for Industry 4.0 - Softcover

Softcover

ISBN 10: 1668465973 ISBN 13: 9781668465974

Publisher: Engineering Science Reference, 2023

Synopsis

As artificial intelligence (AI) processing moves from the cloud to the edge of the network, battery-powered and deeply embedded devices are challenged to perform AI functions such as computer vision and voice recognition. Microchip Technology Inc., via its Silicon Storage Technology (SST) subsidiary, is addressing this challenge by significantly reducing power with its analog memory technology, the memBrain Memory Solution. The memBrain solution is being adopted by today's companies looking to advance machine learning capacities in edge devices. Due to its ability to significantly reduce power, this analog in-memory computer solution is ideal for an AI application.

Neuromorphic Computing Systems for Industry 4.0 covers the available literature in the field of neural computing-based microchip technology. It provides further research opportunities in this dynamic field. Covering topics such as emotion recognition, biometric authentication, and neural network protection, this premier reference source is an essential resource for technology developers, computer scientists, engineers, students and educators of higher education, librarians, researchers, and academicians.

About this title

About the Authors

S. Dhanasekar received his Bachelor of Engineering degree in Electrical and Electronics Engineering from K.S.Rangasamy College of Technology, Erode, Tamilnadu, India in 2004 and received his M.S Degree in VLSI CAD from Manipal Centre for Information Sciences, MAHE, Manipal, Karnataka, India in 2006. He worked as R & D Engineer (VLSI and DSP Division) in Scientech Technologies Pvt. Ltd, Indore, Madhya Pradesh, India. He has completed his Ph.D. degree in Information and Communication Engineering from Anna University, Chennai, India in 2019. He is currently working as Associate Professor in Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamilnadu. He has 14 years of Teaching Experience and 2 years of Industry Experience. He had published more 30 articles in the reputed SCI, Scopus and Web of Science Journals. He is reviewer of Scopus and Web of Science Journals. He is an active member in IEEE and various professional bodies. His teaching & research interests includes low power VLSI design, signal processing communication systems and Artificial Neural Networks.

Dr. Martin Sagayam received his PhD in Electronics and Communication Engineering (Signal image processing using machine learning algorithms) from Karunya University, Coimbatore, India. He received his both ME in Communication Systems and BE in Electronics and Communication Engineering from Anna University, Chennai. Currently, he is working as Assistant Professor in the Department of ECE, Karunya Institute Technology and Sciences, Coimbatore, India. He has authored/ co-authored more number of referred International Journals. He has also presented more number of papers in reputed international and national conferences. He has authored 2 edited book, 2 authored book, book series and more than 15 book chapters with reputed international publishers. He has three Indian patents and two Australian patents for his innovations and intellectual property right. He is an active IEEE member. His area of interest includes Communication systems, signal and image processing, machine learning and virtual reality.

Edition details

• Publisher: Engineering Science Reference
• Publication date: 2023
• Language: English
• ISBN 10: 1668465973
• ISBN 13: 9781668465974
• Binding: Paperback
• Number of pages: 377
• Editor: Dhanasekar S., Sagayam K. Martin, Vijh Surbhi, Tyagi Vipin, Norta Alex