Title :
Template design of cellular neural networks using code theory for object counting
Author :
Fukumoto, Masaharu ; Oh, Min-Ai ; Tanaka, Mamoru
Author_Institution :
Fac. of Sci. & Technol., Sophia Univ., Tokyo, Japan
Abstract :
Cellular neural networks can perform parallel signal processing in real time. They are imbued with some global properties because of the propagation effects of the local interactions during the transient regime. Using cellular neural networks for some pattern matching, it is very useful to give a simple target, such as feature-point extraction. In this paper pattern learning is done by using graph and code theories. Some simulation results are given
Keywords :
cellular arrays; encoding; feature extraction; graph theory; learning (artificial intelligence); neural nets; parallel processing; real-time systems; cellular neural networks; code theory; feature-point extraction; global properties; graph theory; object counting; parallel signal processing; pattern learning; simulation; template design; Blood; Cellular networks; Cellular neural networks; Circuits; Error correction; Image processing; Neural networks; Output feedback; Pattern matching; Signal processing;
Conference_Titel :
Singapore ICCS/ISITA '92. 'Communications on the Move'
Print_ISBN :
0-7803-0803-4
DOI :
10.1109/ICCS.1992.255061
