Premium
A CNN UNIVERSAL CHIP IN CMOS TECHNOLOGY
Author(s) -
ESPEJO S.,
CARMONA R.,
DOMÍNGUEZCASTRO R.,
RODRÍGUEZVÁZQUEZ A.
Publication year - 1996
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/(sici)1097-007x(199601/02)24:1<93::aid-cta906>3.0.co;2-m
Subject(s) - cmos , robustness (evolution) , chip , computer science , cellular neural network , artificial neural network , embedded system , electronic engineering , topology (electrical circuits) , computer architecture , computer hardware , engineering , artificial intelligence , electrical engineering , telecommunications , biochemistry , chemistry , gene
This paper describes the design of a programmable cellular neural network (CNN) chip with added functionalities similar to those of the CNN universal machine. The prototype contains 1024 cells and has been designed in a 1·0 μm, n‐well CMOS technology. Careful selection of the topology and design parameters has resulted in a cell density of 31 cells mm −2 and around 7–8 bits accuracy in the weight values. Adaptive techniques have been employed to ensure accurate external control and system robustness against process parameter variations.