STUDY OF SPECTRAL DATA REPRESENTATION AND CLASSIFICATION FOR WAVELET NEURAL NETWORK

A model of neural network based on wavelet analysis wavelet neural network, is introduced in the paper here. The chemical substance infrared spectral compression representation and classification are realized with adaptive network structure and daughter wavelet.The experimental results show that the original spectra can be recovered well, the place and intensity of absorptive peaks can be defined exactly, and the data can be compressed greatly with the wavelet network.The resolution ratio and the characteristic collection ability of the wavelet network are better than that of other networks in classification. A comparison of the two training results of the wavelet and BP networks indicates that the wavelet network has better adaptability and faster convergence speed and can shield random noise. The wavelet network can be applied to the study and analysis of nonstationary and nonlinear signals, so it holds a bright future in spectra processing.