EMD_Adaptive Filter Combined with Kaiser Window Filter for Denoising of Noise-Containing Frequencies

This study focuses on the key problem of audio signal denoising processing. With the rapid development of information technology, audio signals are widely used in many fields, but the acquisition, transmission and storage processes are often interfered by noise, and traditional denoising methods such as those based on filters and wavelet transforms have limitations. In this study, an innovative method combining empirical mode decomposition (EMD), adaptive filter and Kaiser window filter is proposed. The experimental design process of the method and its principles are firstly described in detail. Then the wavelet transform denoising, EMD combined with adaptive filter denoising, and the method proposed in this study are used to process the noise-containing signals through experimental comparative analysis, respectively. The results show that the first two methods have problems such as incomplete denoising and signal distortion, while the method proposed in this study excels in denoising effect. In summary, the method combining EMD, adaptive filter and Kaiser window filter in this study provides an effective solution for denoising audio signals. The method not only demonstrates good denoising performance, but also reflects the advantages of the Kaiser window filter in precisely controlling the frequency response, adjusting the parameters and maintaining numerical stability, which provides an important reference for further research and practical applications in the field of signal processing.