DocumentCode
295967
Title
The impact of VLSI technologies on neural networks
Author
Moini, A. ; Eshraghian, K. ; Bouzerdoum, A.
Author_Institution
Centre for Gallium Arsenide VLSI Technol., Adelaide Univ., SA, Australia
Volume
1
fYear
1995
fDate
Nov/Dec 1995
Firstpage
158
Abstract
This paper reviews the current VLSI technologies and their utilization in the implementation of neural networks. The scaling of different technologies, and its limitations are described. Requirements of neural networks in terms of VLSI resources are identified, and the advantages and disadvantages of each technology in offering solutions to these requirements are explained
Keywords
BiCMOS integrated circuits; CMOS integrated circuits; VLSI; charge-coupled devices; neural chips; VLSI technologies; neural networks; scaling; Australia; BiCMOS integrated circuits; CMOS process; CMOS technology; Charge coupled devices; Educational institutions; Gallium arsenide; Neural network hardware; Neural networks; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488085
Filename
488085
Link To Document