Title :
Cellular neural networks considering hysteresis characteristic
Author :
Namba, M. ; Kawabata, H. ; Kanagawa, A. ; Zhang, Z.
Author_Institution :
Fac. of Comput. Sci. & Syst. Eng., Okayama Prefectural Univ., Japan
Abstract :
The Cellular Neural Network (CNN) has been widely used for associative memory, but has a problem called indeterminate cell. In this paper, we have proposed a CNN considering hysteresis characteristic as one of the methods to avoid the indeterminate cell problem, and confirmed its effectiveness in simulations
Keywords :
cellular neural nets; content-addressable storage; hysteresis; CNN; associative memory; cellular neural networks; hysteresis characteristic; indeterminate cell problem; Analog circuits; Associative memory; Cellular neural networks; Circuit simulation; Computer industry; Computer science; Differential equations; Hysteresis; Programmable control; Systems engineering and theory;
Conference_Titel :
Circuits and Systems, 2000. IEEE APCCAS 2000. The 2000 IEEE Asia-Pacific Conference on
Conference_Location :
Tianjin
Print_ISBN :
0-7803-6253-5
DOI :
10.1109/APCCAS.2000.913507
