题目

英语翻译
The most interesting dissimilarity between these two kinds of transforms is that individual wavelet functions are localized in space.Fourier sine and cosine functions are not.This localization feature,along with wavelets' localization of frequency,makes many functions and operators using wavelets "sparse" when transformed into the wavelet domain.This sparseness,in turn,results in a number of useful applications such as data compression,detecting features in images,and removing noise from time series.

提问时间：2020-12-28

答案

这两种变换之间最有趣的不同在于每个小波函数在空间上都是局域化的.而傅里叶正弦和余弦函数则不是.这个局域化特征,和小波的频率局域化一起,使得很多使用小波变换的函数和算符在变换到小波定义域后变得“稀疏”.这种稀疏,反过来,又产生了一些有用的应用诸如数据压缩,图像特征检测和时间序列的噪音去除.
嗯,能给点分不?翻译,打字还是有点累的说.