基于小波神经网络的新型算法用于化学信号处理

A Novel Algorithm Based on the Wavelet Neural Network for Processing Chemical Signals

基于紧支集正交小波神经网络的构造思想 ,用具有紧支集的 B-样条函数的伸缩和平移替代小波函数 ,提出了一种新型算法 ,并将其应用于化学信号的处理 ,实现了信号的压缩和滤噪 ,与自适应小波神经网络相比 。

A wavelet neural network based on wavelet analysis can be used to represent chemical signals. The adaptive wavelet neural network using the continuous wavelet transform has problems of a high redundancy and slow training, and the compactly supported orthogonal wavelet neural network using the discrete wavelet transform is difficult to be applied, because the compactly supported orthogonal wavelet function with analytic form is hard to build. Based on the idea of the compactly supported orthogonal wavelet network, a novel algorithm using the compactly supported B spline function instead of the compactly supported orthogonal wavelet function is proposed. It has been applied to the compression and de noising of chemical signals. Compared with the adaptive wavelet neural network, the speed of our algorithm was enhanced greatly. [WT5HZ]