基于二进小波变换极大模法的土壤腐殖酸NMR谱信号滤噪

DE-NOISING OF THE NMR SIGNAL BASED ON THE MODULE MAXIMUM OF BINARY WAVELET TRANSFER

实验数据的滤噪在分析化学领域中具有重要的意义。小波变换技术具有很强的信号分离能力容易把随机噪声从信号中分离出来 ,从而提高信号的信噪比。本文使用的滤噪方法不同于传统离散小波变换方法 ,而是通过引入二进小波变换和李氏指数的概念 ,根据噪声与有用信号的极大模截然不同的特征 ,实现信号滤噪。

Filter of the experiment data have an important part in analytical chemistry filed.Wavelet Transfer(WT) is a powerful technique in signal separation.It is very easy for WT to improve the signal-to-noise(SNR) by separating the random noise and useful signal.The method in the paper is different from the traditional method of the discrete wavelet transfer in analytical chemistry signal processing.We introduce the concept of the binary wavelet transfer and the Lipschitz exponent.According to the completely different performance of the maximum module between the noise and the useful signal,we can get the appropriate filter.The simulation of the experiment data has proved the feasibility of the method.