DocumentCode
303315
Title
Implementation of cellular neural network operating with bipolar images
Author
Paasio, Ari ; Dawidziuk, Adam ; Porra, Veikko
Author_Institution
Electron. Circuit Design Lab., Helsinki Univ. of Technol., Espoo, Finland
Volume
2
fYear
1996
fDate
3-6 Jun 1996
Firstpage
898
Abstract
The paper presents a 16×16 cellular neural network chip implementation. The circuit has been processed with 1.2 micron technology. Cell nonlinearity is based on a high gain sigmoid and this allows processing of black and white images. The layout of the design is discussed and finally measurement results which show almost fully correct behavior are presented
Keywords
CMOS analogue integrated circuits; analogue processing circuits; cellular neural nets; edge detection; integrated circuit layout; neural chips; piecewise-linear techniques; 1.2 micron technology; 1.2 mum; 16×16 cellular neural network chip implementation; analog CMOS; bipolar images; cell nonlinearity; high gain sigmoid; inverse edge detection; piecewise linear sigmoid; Cellular neural networks; Circuit topology; Electronic circuits; Electronic mail; Integrated circuit measurements; Laboratories; Paper technology; Semiconductor device measurement; Switches; Turing machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1996., IEEE International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-3210-5
Type
conf
DOI
10.1109/ICNN.1996.549016
Filename
549016
Link To Document