Training-based SLM-realizable composite filter design

Majority-granted nonlinearity-based training for the synthesis of a composite filter is proposed. The motivation is the limited modulation capability of the spatial light modulator (SLM) which is incorporated as a design constraint in the form of a simple thresholding scheme. The technique is simple, and less computationally extensive nevertheless resulting in a robust enough SLM-realizable distortion-invariant correlator. Simulation results are provided for the case of rotation invariant character recognition, which shows better correlation discrimination and robust recognition for a range of distorted characters.