Hardware Implementations

Artificial Neural Networks

Volume 540 of the series Lecture Notes in Computer Science pp 260-267

Date:

Cmos implementation of a cellular neural network with dynamically alterable cloning templates

  • M. AnguitaAffiliated withDepartamento de Electrónica y Tecnología de Computadores Facultad de Ciencias, Universidad de Granada
  • , A. PrietoAffiliated withDepartamento de Electrónica y Tecnología de Computadores Facultad de Ciencias, Universidad de Granada
  • , F. J. PelayoAffiliated withDepartamento de Electrónica y Tecnología de Computadores Facultad de Ciencias, Universidad de Granada
  • , J. OrtegaAffiliated withDepartamento de Electrónica y Tecnología de Computadores Facultad de Ciencias, Universidad de Granada
  • , A. DiazAffiliated withDepartamento de Electrónica y Tecnología de Computadores Facultad de Ciencias, Universidad de Granada

* Final gross prices may vary according to local VAT.

Get Access

Abstract

An analog CMOS implementation of a Cellular Neural Network with modifiable cloning templates is proposed. One of the most important difficulties to hardware implement neural networks is their topological complexity which implies a high number of interconnections among cells. Nevertheless, as in cellular neural network each cell is only connected to its neighbour cells, their hardware implementation is easier. Even though the reduced connectivity of cellular neural networks, they are suitable for different tasks in the domain of image processing. For each particular application, the cloning templates that characterise the cellular network have to be changed. The circuit here presented allows the online modification of cloning templates, and is integrable using a conventional CMOS process. Some simulation results of the designed circuits are also presented.