Neural network designed volume holographic wavelet correlator for pattern recognition

Neural network (NN) techniques have been introduced to design wavelet filters and wavelet transform systems for pattern recognition. Based on the theory of wavelet matched filtering and the associative characteristic of volume holographic storage in a photo refractive crystal, a novel volume holographic wavelet correlator is constructed. A neural network is proposed to optimize parameters of the wavelet filters to improve recognition performance of the system. Simulation and experimental results are given to testify the effect of optimization. Its application in human face recognition is studied. Use of the neural network to refine parameters of filters is attractive.