Title :
VLSI implementation of a double-layer single cell RD-CNN for motion control
Author :
Branciforte, M. ; Giustolisi, G. ; Nicotra, V. ; Palumbo, Gaetano
Author_Institution :
STMicroelectronics, Catania, Italy
Abstract :
In this paper a solution for a VLSI implementation of a double-layer single cell reaction-diffusion cellular neural network (RD-CNN) for motion control is presented, and a particular attention is focused on the realisation of both the nonlinearity block and the resistor implemented by means of the same transconductor in order to minimise the tolerance variations. Moreover, two solutions are given to obtain very large time constants due to the very low frequency involved in motion control. The approaches are validated by simulating both of them with ELDO and by comparing the results with a Matlab simulation
Keywords :
CMOS integrated circuits; VLSI; cellular neural nets; motion control; neural chips; CMOS; VLSI; cellular neural network; double-layer single cell; motion control; nonlinearity; partial differential equations; reaction-diffusion type; simulation; time constants; Actuators; Biological tissues; Cellular neural networks; Computational modeling; Image processing; Motion control; Resistors; Robots; Transconductors; Very large scale integration;
Conference_Titel :
Cellular Neural Networks and Their Applications, 2000. (CNNA 2000). Proceedings of the 2000 6th IEEE International Workshop on
Conference_Location :
Catania
Print_ISBN :
0-7803-6344-2
DOI :
10.1109/CNNA.2000.877351
