VLSI implementation of a Cellular Neural Network with programmable control operator
G.C. Cardarilli, R. Lojacono, Mário Sérgio Salerno, F. Sargeni · 2002
Cellular Neural Networks (CNN) are a particular class of neural networks based on a regular structure. Using this property a suitable architecture can be designed for a very efficient analog implementation. The core of a cellular neuron is an analog multiplier that can be implemented by using different approaches. In particular, if the CNN is used for conventional applications, as for example Connected Component Detector (CCD), different solutions are possible in terms of fixed or programmable cloning template. In this paper a VLSI implementation of programmable CNN with control operator B and symmetrical and anti symmetrical feedback operator A is presented.>