Fast and Compact 16 by 16 Cellular Neural Network Implementation

Ari Paasio , Adam Dawidziuk , Kari Halonen , Veikko Porra

Abstract

The paper presents a Cellular Neural Network implementation based on a high gain sigmoid operation. The required simplifications to the original theory are described that allow the use of high gain. With this design black and white images can be processed. The basic building blocks in a cell are described. A 16×16 cells network has been designed and processed with 1.2 micron CMOS technology. Measurement results which show the operation of the network are presented.
Author Ari Paasio
Ari Paasio,,
-
, Adam Dawidziuk (FEIT / PE)
Adam Dawidziuk,,
- The Institute of Electronic Systems
, Kari Halonen
Kari Halonen,,
-
, Veikko Porra
Veikko Porra,,
-
Journal seriesAnalog Integrated Circuits and Signal Processing, ISSN 0925-1030, 1573-1979
Issue year1997
Vol12
No1
Pages59-70
Keywords in Englishbipolar image processing, cellular neural network, Electronic and Computer Engineering, Implementation, signal processing
DOIDOI:10.1023/A:1013230918396
URL http://link.springer.com/article/10.1023/A%3A1013230918396
Score (nominal)0
Citation count*13 (2015-03-03)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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