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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。
Filter noise of experimental data in the field of analytical chemistry is of great significance. Wavelet transform technology has a strong signal separation capability, easy to separate random noise from the signal, thereby enhancing the signal to noise ratio. In this paper, the filter method is different from the traditional discrete wavelet transform method, but through the introduction of the concept of binary wavelet transform and Lee’s index, according to the noise and useful signal very different from the maximum modulus of the signal filtering. The simulation results of experimental data also prove the feasibility of the method.