二进小波变换极大模法用于分析化学信号的滤噪

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。实验数据的仿真结果研究也证明该方法的可行性。

De-noising of analytical signals based on the maximum module of binary wavelet transfer

Wavelet transfer(WT) is a powerful technique in signal separation and can improve the signal to noise ratio by separating the random noise and useful signal. The method in the paper introduced the concepts of binary wavelet transfer and Lipschitz exponent. According to the performance of maximum module between the noise and signal, the appropriate filter was realized. The simulation data demonstrated the feasibility of the method.