多尺度细化分析 meaning in Chinese
multiscale analysis
Examples
- The method analyzes initial data at different scales carefully , extracts independent signals according to the information maximization criterion , and monitors the process in real time in a low - dimensional subspace of data
该方法对初始数据进行多尺度细化分析，并根据信息最大化准则提取独立元信号，在数据的低维子空间上对过程进行实时监控。 - Wavelet transform becomes a superior timefrequency localization method due to its mathematical property itself it has muiti - resolution characteristics . by flexing and moving a base wavelet , which must satisfy some condition , we can analyze signals in multi - scale finely , so it is called " math microscope "
它具有多分辨分析的特点，通过某个满足一定要求的基小波的伸缩和平移等运算功能对信号进行多尺度细化分析，因而能聚焦到信号分析的任何细节，被誉为“数学显微镜” 。 - Wavelet transform is a time and frequency local transformation and it can withdraw the information from the signal . through the calculate function making the muti - scale analysis it resolves many difficult problems which fourier transformation ca n ' t resolve . in recent years the researches and the applications of wavelet transform on the image compression are flourish , but because wavelet transform is very complicated and its apply has certain localizations
小波变换是一个时间和频率的局域变换，因而能有效的从信号中提取信息，通过伸缩和平移等运算功能对函数或信号进行多尺度细化分析，解决了fourier变换不能解决的许多困难问题。近年来小波变换在图像压缩的研究和应用都十分活跃，但是由于小波的理论很复杂，因此应用起来就有一定的局限性。 - Wavelets are a very interesting class of functions because of their special properties . the orthonormal bases can be constructed by translation and dilation of a mother wavelet . wavelets have local property in time domain and frequency domain , so we can extract information from signals using wavelets
小波变换通过伸缩和平移等运算功能对函数或信号进行多尺度细化分析，是时间和频率的局部变换，能有效地从信号中提取信息，因而成为当前一种新兴的信号处理技术。 - The wavelet transform is a new subject developed quickly in the past ten years . compared with fourier transform and gabor transform , the wavelet transform is a part of time - frequency transform , so the message can be obtained from the signals effectively . by means of the fractionized multi - resolution analysis to the signals , many problems unable to be solved by fourier transform have been solved in this way
小波变换是近10年来迅速发展起来的学科，它与fourier变换、 gabor变换相比，是一个时间和频率的局部变换，能有效地从信号中提取信息，通过对信号进行多尺度细化分析，解决了fourier变换不能解决的许多问题。