基于RBF网络的小波变换模极大值重构算法

Algorithm of Signal Reconstruction from Modulus Maximum of Signal′s Wavelet Transform Based on Radial Basis Function (RBF) Network

本文根据交替投影的基本思想 ,提出了一种基于径向基函数网络的小波变换模极大值重构方法 .该方法利用径向基函数网络 (RBFN)在其基函数宽度很大时具有较好的线性映射这一特性来加快收敛速度 ,提高重构精度 .它不仅能较好地重构信号的边缘 ,而且能准确地重构出信号的峰值 .大量仿真实验表明 ,该方法对各种信号是普遍适用的 ,具有收敛速度快 。

Based on the principle of alternative projection,the paper presents an algorithm of signal reconstruction from modulus maximum of signal's wavelet transform based on radial basis function (RBF) network.The algorithm accelerates convergence and improves reconstruction precision by taking advantage of RBF network's good linear property which occurs while the width of the basis function is very large.The algorithm can not only reconstruct signal's edges very well,but also recover signal's climax precisely.A lot of simulation experiments show that the algorithm is also effective to different kinds of signals and has characteristics of both fast convergence and high precision.