DocumentCode :
2178804
Title :
Cellular neural network in image filtration tasks
Author :
Khryasshyov, Vladimir V. ; Sautov, Eugene Yu ; Sokolenko, Egor A.
Author_Institution :
Yaroslavl State Univ., Russia
fYear :
2002
fDate :
2002
Firstpage :
267
Lastpage :
270
Abstract :
The mathematical model of cellular neural network (CNN) working in discrete time is considered. The possibility of such devices for computation of the convolution of two-dimensional digital signal with a given kernel is shown. The algorithm of construction of a difference equation with constant coefficient, which has the solution of the demanded convolution is given. The hardware implementation of this equation is given the structure of CNN. Model of an exponential smoothing filter of two-dimensional digital signal is considered.
Keywords :
cellular neural nets; convolution; difference equations; filtering theory; image representation; cellular neural network; constant coefficient; convolution; difference equation; discrete time; exponential smoothing filter; hardware implementation; image filtration tasks; kernel; mathematical model; two-dimensional digital signal; Cellular neural networks; Concurrent computing; Convolution; Difference equations; Filtration; Image processing; Intelligent networks; Smoothing methods; Telecommunication computing; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems for Communications, 2002. Proceedings. ICCSC '02. 1st IEEE International Conference on
Print_ISBN :
5-7422-0260-1
Type :
conf
DOI :
10.1109/OCCSC.2002.1029093
Filename :
1029093
Link To Document :
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