Wavelet transform possesses excellent characteristic of time frequency localization, and provides an effective measure for analysing signal causing unstable vibration.
小波变换具有很好的时域和频域局部化特性，为以非稳态振动为特征的信号提供了有效的分析手段。
Wavelet analysis, also called wavelet transform, is a new analysis method with good time frequency localization characteristic, so it is suitable for fault analysis of power system.
小波分析(或称小波变换)是一种新的时频分析方法，它具有良好的时频局部化特性，适用于电力系统故障分析。
Wavelet transform has a good analyzing feature and a good time frequency localization. Spectrum whitening is a effective tool of frequency compensation in high resolution processing.
小波变换具有分析性质好和时—频局域化好的特性，而谱白化方法是高分辨处理中一种有效的频率补偿手段。
As a new technique of signal processing, wavelet analysis has excellent characteristics of time frequency localization and is suitable for analyzing time varying or transient signals.
作为一种日益获得广泛应用的信号处理新技术，小波分析具有良好的时频局域化特性，适应于时变和瞬变信号的分析。
Wavelet analysis is widely used in digital signal and image fields because of its good time frequency localization feature, but it doesn't do well in timely processing of long signals.
小波分析有良好的时-频局部化性能，现被广泛应用于数字信号和图像处理等领域，但其在处理有限长信号时的实时性不太理想。
Wavelet packet transform is used as an efficient tool for precisely analyzing signal property, and provides orthogonal wavelet packet bases with better time frequency localization function.
小波包变换能作为一种有效工具对信号特性进行精细分析，同时提供具有良好时频局部性的正交小波包基。
Having good time-frequency localization character, and correctly identifying singularity point in fault signal, Wavelet is the main analysis method in this paper.
小波变换具有良好的时频局部性，具有变焦距的特点，对故障信号中的奇异点能够准确识别，是论文中应用的主要分析方法。
The good localization characteristics of wavelet functions in both time and frequency space allow hierarchical multi-resolution learning of input-output data mapping.
由于小波变换在时间和频率空间具有良好的定位特性，使小波神经网络可对输入、输出数据进行多分辨的学习训练。
The wavelet transform is of good localization property in the domain of time and frequency, which provides a comprehensive application in processing acoustic wave.
小波变换同时有在时间域和频率域对信号进行局部化的特点，使其在声波信号处理中有着广泛的应用前景。
Low level image processing is the base of localization. The paper discusses time domain filtering and frequency domain filtering according to the noise disturbance in the surrounding images.
低层视觉图象处理是视觉定位的基础，针对环境图象存在噪声干扰的特点，文章分别从时域和频域上分析了图象滤波的方法。
The good localization characteristics of wavelet functions in both time and frequency space allowed hierarchical multi-resolution learning of input-output data mapping.
利用小波变换所具有的良好的时频分析特性，实现了输入输出之间映射关系的多分辨学习。
Wavelet is the best base of functions, with point singularity, and it has wide application in image processing because of its time-frequency localization and multiscale features.
小波是表示具有点奇异性函数的最优基，它由于具有时-频局部化特点和多尺度特性，在图像处理领域得到了广泛应用。
Wavelet transformation possesses excellent properties of time-frequency localization and thus provides an effective means for analyzing signals characterized by unstable vibration.
小波变换具有很好的时域和频域局部化特性，它对以非稳态振动为特征的信号提供了很好的分析手段。
At present, the joint estimation methods of time delay and frequency shift for satellite interference localization are mainly based on the principle of correlation, such as CAF algorithm.
目前，卫星干扰源时延和频移定位参数的估计主要采用基于相关原理的互模糊函数算法(CAF)进行联合估计。
The wavelet transform has favorable localization character in time domain and frequency domain, which is specially applicable in wideband signal.
介绍了连续子波变换的定义和性质：基于子波变换在时域和频域的良好局部化性质；
Due to the good localization feature of the wavelet transform both in time plane and in frequency plane, a wavelet-based de-noise method is presented for extracting EPs in single trails.
由于小波变换在时域和频域上都具有良好的局部化特性，基于小波变换的去噪方法，可以达到从单次样本中提取视觉诱发电位的目的。
The main characteristic of the WT is the dual localization property in both time domain and frequency domain, which enables WT to be a high performance signal processing technique.
由于小波变换的时 -频局部化性质 ，使其成为信号处理的强有力工具。
Wavelet analysis, as a new technique of signal processing, possesses excellent characteristic of time-frequency localization and is suitable for analysing the time-varying or transient signals.
小波分析是一种日益获得广泛应用的信号处理新技术，它具有良好的时-频局部化特性，因而非常适于分析瞬态或时变信号。
The wavelet packet method characterized by good time-frequency localization can be used to make signal reconstruction and energy analysis of blasting vibration wave.
利用小波分析良好的时频局部化性质，可以很好地对爆破地震波进行信号重构和能量分析。
Due to the good localization feature of the wavelet transform both in time plane and in frequency plane, we present a wavelet-based denoising method for extracting EPs in single trails.
由于小波变换在时域和频域上都具有良好的局部化特性，本文提出了一种基于小波变换的去噪方法，以期达到从单次样本中提取视觉诱发电位的目的。
The wavelet analysis is a key method to solve this kind of the problem because of its unique time-frequency localization characteristic, compared with traditional methods.
鉴于传统信号处理方法的局限性，小波分析以其具备时频局部特性，成为解决此类问题的一个重要方法。
The wavelet analysis is a key method to solve this kind of the problem because of its unique time-frequency localization characteristic, compared with traditional methods.
鉴于传统信号处理方法的局限性，小波分析以其具备时频局部特性，成为解决此类问题的一个重要方法。
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