A LOCAL ADAPTIVE WAVELET AND GAUSS NEURAL NETWORK SYNTHESIS CLASSIFICATION SYSTEM
局域自适应子波高斯神经网络综合分类系统

In this paper, an efficient engineering classification of ship noises based on a local adaptive wavelet and Gauss neural network synthesis classification system is presented. The classification systems combine two methods of feature extraction and classification, which are adaptive wavelet neural network and adaptive Gauss neural network. It is capable of learning new types of signals and not destroying the learned network. The classification system is used to extract automatically feature from and classify for noises radiated from actual three types of ships. The classified results are encouraging, and this method is proved to be superior and efficient engineering application in the future.