跳频信号是典型的非平稳信号，必须采用非平稳信号处理方法。
Frequency-Hopping signal is a typical nonstationary signal and must adopt nonstationary signal processing methods.
移动的修正周期图谱估计方法在实时处理和非平稳信号处理的场合中是常用的一种有效方法。
To modify periodogram by moving is a useful and effective method for either real time signal processing or non-stable signal processing.
而小波具有“变焦距”特性，在时域和频域中具有良好的局部分析能力，适合于超声等非平稳信号处理。
The wavelet transform has a good performance of local analyzing in both time domain and frequency domain. It is fit for analyzing non-stationary signals, such as ultrasonic signal.
实验结果表明，该法是分析处理具有时变谱特性的非平稳信号的一种有效方法。
Experiments show that the technique is effective for processing unstable signals of time-variation spectra.
它可统一处理平稳或非平稳arma信号的最优滤波、平滑和预报问题。
It can handle the optimal filtering, smoothing and prediction problems of stationary or non -stationary ARMA signals in the unified framework.
验证了时间序列分析方法在非平稳随机信号处理方面的可靠性；
The reliability of the time-series analysis method in processing unsteady random signals is verited.
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.
由于小波变换有效地克服了傅氏变换在处理非平稳的复杂信号时所存在的局限性，因而在图像与信号处理领域受到了广泛的重视。
Due to wavelet transforms efficiently overcoming the limitations of Fourier transform in dealing with unstable and complicated signal, they are popular in image compression and signal processing.
研究结果表明：基于经验模式分解的时频分析方法可以很有效地提取到非平稳故障特征信号，是一种适合于非线性信号处理的方法。
The experiment result shows that the time-frequency method based on EMD can effectively extract the feature of unbalanced fault signal and is proper for non-frequency modulation signal procession.
实验结果表明，小波变换的多分辨率分析对于分析处理具有时变谱特性的非平稳信号是一种新的有效方法。
Experiments show that the multiresolution analysis of wavelet transform is an effective new method for processing unstable signals having time variant spectra.
它可统一处理滤波、平滑和预报问题，且可处理非平稳信号和噪声。
It can handle the filtering, smoothing and prediction problems in a unified framework, and can handle nonstationary signals and noises.
针对传统滤波方法处理非平稳信号的不足，提出利用经验模态分解法来处理转子启动信号，通过此方法的自适应滤波特性来提取这类信号中的低频分量。
This paper describes a method to extract the low frequency component from rotor startup signal based on empirical mode decomposition, which overcomes the difficulties of traditional filter methods.
该方法可用于复杂的非线性、非平稳信号的处理。
This method can analyze complicated non-stationary nonlinear signal.
非平稳信号作为现实生活中普遍存在的信号形式，其分析处理在现代信号处理中占有特殊重要的地位。
The analysis methods of nonstationary signals, which are widely exist in our real life, play an important role in modern signal processing.
非平稳信号广泛存在于很多实际场合中，比如如语音、雷达和声纳中的线性调频信号，时频分析是处理非平稳信号的一个强有力的工具。
The non-stationary signal is widely distributed in the reality, such as audio, radar and sonar signals. Time-frequency analysis is an effective tool to process the non-stationary signals.
EMD方法是对非平稳、非线性信号进行分析的一种新的时频分析方法。它比小波分析等方法具有更强的特性并能准确地处理非常短的数据序列。
EMD method is a new method for analyzing nonlinear and non-stationary data, which has more advantage than wavelet analysis, and it can process short time series precisely.
然而，现实中的信号大多是非线性、非平稳的，并且数据长度有限，这使得分析处理此类信号成为一项复杂的工作。
While in the real world, signals are often nonlinear and non-stationary and their length is often very short, which makes the processing of such signals a difficult task.
水力机组振动复杂，信号呈现出非线性、非平稳性。因此，振动信号的预处理在水力机组振动监测中非常重要。
It is very important for the signal pretreatment of hydraulic power vibration monitor because the situation of vibration is complicated, and the signal appears non-linear and non-stable character.
由于离心泵故障振动信号是非平稳信号，因此有必要选择恰当的适合于非平稳信号分析的信号处理方法。
Because the signal of failure centrifugal pumps are a non-stationary signal, so it is necessary to select the appropriate signal processing method which is suitable for non-stationary signal.
EMD分解法是一种自适应的信号处理方法，适用于分析非线性、非平稳过程。
The EMD method is a new method to analyze instability and nonlinearity.
时频分析作为分析时变非平稳信号的有力工具，成为现代信号处理研究的一个热点。
Now, Time-Frequency Analysis is one of the top interests in Signal Processing, and more and more research has been put on this topic.
时频分析作为分析时变非平稳信号的有力工具，成为现代信号处理研究的一个热点。
Now, Time-Frequency Analysis is one of the top interests in Signal Processing, and more and more research has been put on this topic.
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