Neural network based face recognition by using diffraction pattern sampling with a digital ring-wedge detector

Use of neural networks (NNs) and diffraction pattern sampling by a ring-wedge detector leads to easier and faster algorithms for pattern recognition. An estimation was made of the optimum dimensions of a digital ring-wedge detector for sampling Fourier transform of random matrices through simulation of digital ring-wedge detector. The modulus squared Fourier transforms of facial images were sampled by ring-wedge geometry, and used for training a neural net for multi-face recognition. Fourier spectral intensities obtained by simulation and experiment were both tested for training and generalization of the network which was studied as a function of learning rate and number of