DocumentCode :
921419
Title :
Autowaves for image processing on a two-dimensional CNN array of excitable nonlinear circuits: flat and wrinkled labyrinths
Author :
Pérez-Muñuzuri, V. ; Pérez-villar, V. ; Chua, Leon O.
Author_Institution :
Dept. Fisica de la Mater. Condensada, Univ. of Santiago de Compostela, Spain
Volume :
40
Issue :
3
fYear :
1993
fDate :
3/1/1993 12:00:00 AM
Firstpage :
174
Lastpage :
181
Abstract :
A two-dimensional (2-D) cellular neural network (CNN) array of resistively coupled Chua circuits which can be designed to implement some elementary aspects of spatial recognition, namely, distinguishing open curves from closed ones and locating the shortest path between two locations, is described. In the latter, two situations are analyzed: flat and wrinkled surfaces. The 2-D CNN array of Chua circuits is shown to be capable of finding the shortest path between two points on a wrinkled labyrinth. The performance of this parallel processing approach was examined using computer simulations, although this method can be implemented in real time via VLSI technology
Keywords :
VLSI; image recognition; neural chips; nonlinear network analysis; VLSI technology; cellular neural network; closed curves; excitable nonlinear circuits; flat surfaces; image processing; open curves; parallel processing approach; resistively coupled Chua circuits; spatial recognition; two-dimensional CNN array; wrinkled labyrinths; Cellular neural networks; Computer simulation; Coupling circuits; Image processing; Neural networks; Neurons; Nonlinear circuits; Parallel processing; Signal processing; Very large scale integration;
fLanguage :
English
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7122
Type :
jour
DOI :
10.1109/81.222798
Filename :
222798
Link To Document :
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