Evaluation of CNN template robustness towards VLSI implementation

In this paper a method for the evaluation of the static robustness of cellular neural network (CNN) templates is proposed. From this evaluation the circuit accuracy specifications for a VLSI implementation can be derived which allows the designer to optimize the performance. Moreover, from this evaluation method guidelines for robust template designs can be derived and parameter testing templates can be developed.<<ETX>>