小波分解可以使人们在任意尺度观察信号，只需所采用的小波函数的尺度合适。小波分解将信号分解为近似分量和细节分量，它们在应用中分别有不同的特点。比如，对含有噪声的信号，噪声分量的主要能量集中在小波分解的细节分量中，对细节分量做进一步处理，比如阈值处理，可以过滤噪声。(Wavelet decomposition allows people to observe signals at any scale, just the size of the wavelet function is appropriate. The wavelet decomposition decomposes the signal into approximate and detail components, and they have different characteristics in application. For example, for noisy signals, the main energy of the noise component is concentrated in the detail components of wavelet decomposition, and further processing the detail components, such as threshold processing, can filter the noise.)