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。
Having good time-frequency localization character, and correctly identifying singularity point in fault signal, Wavelet is the main analysis method in this paper.
时频分析方法是利用小波变换原理，从地震波的时间域和频率域同时对其作出分析。
Time frequency analysis method is used to analyze the time domain and frequency domain of seismic waves at the same time according to the principle of wavelet transformation.
该文利用小波包变换的时频局部分析能力，研究了非高斯分布平稳随机噪声的统计特性，揭示了非高斯噪声信号的信号结构。
By exploiting wavelet packet transform to analyze signals both in time and frequency space, this paper researches the statistic property of non-Gaussian stationary noise and its signal structure.
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。
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 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.
小波变换的主要特点是通过变换能够充分突出某些方面的特征，它是研究信号时-频分析的重要方法。
The main characteristics of wavelet transform is that some character can well outstanding by transformation and it is an important way to study signal in time-frequency domain.
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。
The good localization characteristics of wavelet functions in both time and frequency space allowed hierarchical multi-resolution learning of input-output data mapping.
讨论了基于小波变换的时频分布级数，把一种新的时频分析工具——频率-切变分布应用于时频成像。
Time-frequency distribution series based on wavelet transform is discussed., and a new time-frequency tool: frequency-shear distribution is introduced into radar imaging fields.
采用了短时傅里叶变换方法对仿真信号进行了时频分析，得到了能够较好地反映目标特征的微多普勒图像。
Short time Fourier transform was used to analyze the simulated signal in the time-frequency domain, a micro-Doppler image that can demonstrate the target characteristics was generated.
本文在分析地震反射波勘探信号时频分布特性的基础上提出了基于短时傅里叶变换的地层吸收补偿方法。
Stratigraphic absorption compensation based on short-time Fourier transform has been developed by analysing the time-frequency distribution characteristics of seismic reflection signals.
从小波变换的基本概念出发，简要介绍了小波变换在信号时-频分析中的变焦特性。
From the basic conception of wavelet transformation, we discuss briefly the zooming characteristics of wavelet transformation in time-frequency domain analysis in this paper.
然后探讨了连续小波变换、离散小波变换、小波包变换等小波理论中几种重要的变换方法，分析了这几种小波变换的时频特性。
Then it discusses several transform methods, such as continuous wavelet transform, discrete wavelet transform and wavelet packet transform of which characteristics are analyzed.
本文介绍处理非平稳信号的新型工具——小波分析、短时付氏变换两种时频分析方法。
In this paper, two kinds of new time-frequency analysis approaches for non-stationary signal processing are introduced, which are wavelet transform and short-time Fourier transform.
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。
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.
分析了移动装备发动机缸盖振动信号的时频特性，介绍了插补细分提升小波包变换算法。
The lifting wavelet package transform based on interpolating subdivision was introduced. The engine cylinder head vibration signal's time-frequency characteristics were analyzed.
利用快速四阶循环累积量算法、时频脊线分析与小波变换相结合的方法，实现了跳频频率和码速率等参数的高精度估计。
They are used to yield accurate estimation for the hop frequencies and hop rate, which are fast 4th-order cyclic cumulants algorithm, time-frequency backbone curve analysis, and wavelet transform.
利用二维快速傅立叶变换的时频分析方法，对有限元计算得到的时域信号进行了分离，得到了各个模式超声波的相速度色散曲线。
The two-dimensional fast Fourier transform (2D-FFT) method has been used to analyze the ultrasonic signals where different wave modes overlaid in the time domain.
利用二维快速傅立叶变换的时频分析方法，对有限元计算得到的时域信号进行了分离，得到了各个模式超声波的相速度色散曲线。
The two-dimensional fast Fourier transform (2D-FFT) method has been used to analyze the ultrasonic signals where different wave modes overlaid in the time domain.
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