DocumentCode
418093
Title
High density VLSI implementation of a bipolar CNN with reduced programmability
Author
Paasio, Ari ; Flak, Jacek ; Laiho, Mika ; Halonen, Kari
Author_Institution
Microelectron. Lab, Turku Univ., Finland
Volume
3
fYear
2004
fDate
23-26 May 2004
Abstract
In this paper a VLSI implementation of a bipolar CNN with a reduced programmability is described. The programmability of the weights and the bias term is reduced to one bit. Since the programming is digital, the template write time is fast. While losing some generality in the programming, the cell array is still able to perform most of the bipolar CNN templates presented so far. The proposed structure yields a very compact realization in a dense layout. The cell size using a 0.18μm digital CMOS process was 155μm2.
Keywords
CMOS digital integrated circuits; VLSI; cellular neural nets; 0.18 micron; VLSI implementation; bipolar CNN; cell array; cellular neural network; digital CMOS process; digital programming; CMOS process; Cellular neural networks; Circuits; Energy consumption; Hardware; Laboratories; Nonlinear equations; Switches; Variable structure systems; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2004. ISCAS '04. Proceedings of the 2004 International Symposium on
Print_ISBN
0-7803-8251-X
Type
conf
DOI
10.1109/ISCAS.2004.1328673
Filename
1328673
Link To Document