Title :
Simplicial RTD-based cellular nonlinear networks
Author :
Julián, Pedro ; Dogaru, Radu ; Itoh, Makoto ; Hänggi, Martin ; Chua, Leon O.
Author_Institution :
Dept. of Appl. Electron. & Inf. Eng., Polytech. Univ. of Bucharest, Romania
fDate :
4/1/2003 12:00:00 AM
Abstract :
Recently, a novel structure called the simplicial cellular neural network (CNN) has been introduced , which permits one to implement any Boolean/Gray-level function of any number of variables. This paper is devoted to explore novel circuit architectures for the implementation of the simplicial CNN based on resonant tunneling diodes. The final objective is to implement a fully programmable CNN in a hardware platform based on nanoelectronic devices.
Keywords :
Boolean functions; cellular neural nets; nanoelectronics; neural chips; neural net architecture; piecewise linear techniques; resonant tunnelling diodes; Boolean function; Gray-level function; RTD-based cellular nonlinear networks; circuit architectures; fully programmable CNN; nanoelectronic device based hardware platform; resonant tunneling diodes; simplicial PWL algorithm; simplicial RTD CNN; simplicial cellular neural network; Boolean functions; Cellular networks; Cellular neural networks; Diodes; Hardware; Nanoscale devices; Neural networks; Nonlinear equations; RLC circuits; Resonant tunneling devices;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
DOI :
10.1109/TCSI.2003.809819
