| 1. | In the signal treatment domain , there occurs a new method , more advanced " digital microscope " - - wavelet analysis . wavelet analysis aims at the treatment of non - stationary signal
而在信号分析、处理领域，出现了更为先进的号称为“数学显微镜”的小波分析，给我们带来了新的工具。 |
| 2. | Because of " self - adaptable " and " focus - adjustable " , wavelet analysis ( wa ) is called " mathematics microscope " and plays an important role in processing the non - stationary signal
而小波变换具有良好的“自适应性”和“变焦特性” ，被誉为“数学显微镜” ，在处理非稳定信号上有其特殊的地位和功能。 |
| 3. | The wavelet method used in economic forecast depends on its " mathematics microscope " property . it does the layer analysis and forecast to indicators . it can improve forecast precision , what ' s more it can search and express the structural feature of data such as development cycle , second cycle , especially to some sudden change data which will provide effective and reliable warranty to the complexity and violent fluctuant data indicators in enterprise
基于小波进行经济预测的方法依靠其“数学显微镜”的特性，对待分析的预测指标进行逐层分析和预测，在提高预测精度的基础上，能对分析数据对象的结构特征进行挖掘，分析数据特征如发展主周期、次周期等，尤其对具有突变性质的数据具有很好的表征分析能力，这对于企业中复杂的变动剧烈的数据指标的预测能提供有效可靠的保证。 |
| 4. | 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” 。 |
| 5. | A wavelet analysis is introduced to detect and diagnose faults occurred in the ehs system . as well known , wavelet analysis is referred to as a mathematical microscope . it takes advantage to fourier transform in its multi - resolution analysis both in time domain and in frequency domain
众所周知，由于小波分析具有良好良好的时?频特性，即在低频部分具有较高的频率分辨率和较低的时间分辨率，在高频部分具有较高的时间分辨率和较低的频率分辨率，而被誉为“数学显微镜” 。 |
| 6. | Image edge detection based on multiresolution wavelet transform makes up these shortages before . wavelet theory has good local inspect ability in time region and frequency region , and the character multiresolution . these are theory basis that wavelet transform is applied to cell image edge detection
小波变换是80年代后期发展起来的一种变换域信号处理方法，具有时域和频域上良好的局部检测能力和多分辨率分析的特点，从而被誉为“数学显微镜” ，这是我们将小波变换应用于细胞图像边缘检测的理论依据。 |
| 7. | As a new type of time - frequency analysis media , it excels in its good localization character both in time domain and in frequency domain comparing with traditional fourier analysis . it changes its sampling steps to smaller and smaller so as to analyze high frequency part , focusing on any part of the object been analyzed . to some extent , wavelet analysis is called " math microscope "
作为一种新型的时频分析方法，它优于传统fourier变换的优点是在时域和频域同时具有良好的局部化性质，可对高频成分采用逐步精细的时域采样步长，聚焦到对象的任意细节，因此被誉为“数学显微镜” 。 |
| 8. | Wavelet has good localizing quality at time domain and frequency domain simultaneously and the characteristic of multi - resolution ratio analysis , so it can fulfill all kinds of wave - filtering needs such as low - pass , high - pass , sink wave , random noise denoising . compare with readitional wave - filtering methods , wavelet has incomparable advantage . wavelet has become an effective means of signal analysis and is intituled as math microscope of signal analysis
小波分析由于在时域频域同时具有良好的局部化性质和多分辨率分析的特点，因此不仅能满足各种去噪要求如低通、高通、陷波、随机噪音的去除等，而且与传统的去噪方法相比较，有着无可比拟的优点，成为信号分析的一个强有力的工具，被誉为分析信号的数学显微镜。 |
| 9. | The results show this approach is effective when there is massive cloud cover on the remote sense image . wavelet analysis is internationally recognized up to the minute tools for analyzing time - frequency . it is chiefly due to the " adaptive feature " and " mathematical micro - telescope feature "
小波分析是目前国际上公认的最新时间-频率分析工具，由于其“自适应性”和“数学显微镜性质”而成为许多学科共同关注的焦点，本文利用小波改善传统数字图像处理方法，取得了一定效果。 |
| 10. | The type of the base function of wavelet analysis is not single , while the ft has only the sine ( or cosine ) function or exponential function . wavelet transformation has the character of multi - resolution analysis . wavelet transformation can analyze the signal in any precision ( resolution ) at any part of time and frequency according to the different translation factors and dilatation factors
小波变换具有多分辨率分析的性质，对应于不同的伸缩因子和位移因子，小波变换能对信号的任何时间(空间)段、任何频率段进行任何精度(分辨率)的分析，在非平稳信号(包括瞬间信号)的分析中具有很大的优越性，分析时，在信号的低频部分具有较高的频率分辨率和较低的时间分辨率，在高频部分则具有较高的时间分辨率和较低的频率分辨率，被誉为“数学显微镜” 。 |
