Design methods for CNN spatial filters with circular symmetry

We propose an efficient method for designing circularly-symmetric spatial linear filters implemented on cellular neural networks. The proposed method is relatively simple, relying on a 1D prototype filter, for which the templates are determined, and on a spatial frequency transformation. Some design examples are given, for 2D low-pass and band-pass filters (both of FIR and IIR type) with imposed cut-off or peak frequency and a specified selectivity.