VLSI Implementation of Artificial Neural Networks— Asurvey

Abstract

Artificial neural networks (ANNs) are simplified models of human brain. These are networks of computing elements that have the ability to respond to input stimuli and generate the corresponding output. To obtain a desirable output, the network weights must be trained upon the available data many times. Hence the software realization of ANN takes many hours to learn a particular example. On the other hand, neural network (NN) in hardware can speed up the training by several orders of magnitude, due to the faster nature of the hardware. Different types of VLSI implementation of ANN are found in the literature. This paper provides a brief survey of digital and pulsed neurohardware. It highlights the important issues related and shows the possible direction of future research.

Key Words:

• Artificial neural networks
• VLSI implementation
• digital neurohard-ware
• pulsed neurohardware

Additional information

Notes on contributors

M. Nirmaladevi

M. Nirmaladevi received her B.E. degree in Electronics and Communication Engineering and M.E. degree in Applied Electronics from the Bharathiar University, Coimbatore, India in 1990 and 1996 respectively. She has obtained her Ph.D. degree from Anna University, Chennai, India. Her area of research includes Artificial Neural Networks, Soft Computing and VLSI Design. She has authored around 25 papers in National and International Conferences and Journals. She is a member of ISTE, BMESI, IETE and VLSI society of India.

S. Arumugam

S. Arumugam received his Ph.D. degree in Computer Science and Engineering from Anna University, Chennai in 1990. He also obtained his B.E. (Electrical and Electronics Engineering) and M.Sc. (Engg.) (Applied Electronics) degrees from P.S.G. ColI lege of Technology, Coimbatore at University of Madras in 1971 and 1973 respectively. He has held various positions from associate lecturer, lecturer, assistant professor, professor and principal from 1974. He held the post of Additional Director in the Directorate of Technical Education, Government of Tamilnadu. Presently, he is working as the Chief Executive Officer, at Nandha Engineering College, Tamilnadu, India. He has guided 12 Ph.D. scholars and guiding 15 Ph.D. scholars. He has published around 120 technical papers in international and national journals and conferences. His area of interest includes network security, biometrics and neural networks.