基于小波神经网络的混沌模式提取

Chaotic Pattern Distinction Based on Wavelet Neural Network

分析了小波基函数对于确定模式、混沌模式及随机模式所表现出来的不同的收敛特性，提出构造一个小波神经网络及相应学习算法．利用小波网络在学习过程中神经元的不同增长趋势来反映上述收敛性的差异，从而将３种不同的模式予以区分，并将混沌模式从中提取出来．

The features of constringencies of deterministic pattern, chaotic pattern and random pattern are analyzed. A wavelet neural network is constructed and its learning algorithm is studied. The difference of increase trend of neurons in wavelet network are used to reflecting the difference of constringencies of the pat-terns above mentioned. Owing to there differences, the chaotic pattern can be distinct.