SCNN: a universal simulator for cellular neural networks
R. Kunz, Ronald Tetzlaff, Dietrich E. Wolf · 2002
In this paper a universal simulator for cellular neural network (CNN) is presented. CNN with nonlinear and delay-type templates can be simulated precisely with SCNN, practically without any limitations. Furthermore different training algorithms for networks with translation variant and invariant templates are implemented in SCNN. As an example, parameter deviations of a template have been reduced by training. Simulation and training results are discussed in detail.