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1)  Non-stationary signal processing
非平稳信号处理
1.
With the development of science and technology, Non-stationary signal processing and its application in engineering gain more and more attention.
随着科学技术的不断发展,非平稳信号处理方法及其在工程中的应用研究越来越受到人们的重视。
2)  nonlinear and non_stationary signal processing
非线性非稳态信号处理
3)  non-stationary signal
非平稳信号
1.
Blind separation of non-stationary signal based on non-orthogonal diagonalization algorithm;
基于非正交对角化算法的非平稳信号盲分离
2.
On-line blind source separation of non-stationary signals by multiple time-delayed decorrelation rule;
多时延解相关准则下的非平稳信号在线盲分离
3.
To solve the difficulty of time-delay estimation for non-stationary signal,an improved estimation method based on short-time Fourier transform(STFT) spectrogram correlated with frequency domain is presented.
目前的时延估计算法多数只能应用于平稳信号,针对非平稳信号时延估计,提出了一种基于短时傅立叶变换(STFT)谱图的瞬时频域相关法。
4)  non-stationary signals
非平稳信号
1.
To analyze and deal with non-stationary signals, pe.
为了分析和处理非平稳信号,人们发展了信号分析理论,提出了许多时频描述方法。
2.
And this paper introduced the advantages of those methods in analyzing non-stationary signals and explains the merits and defects of those methods by analyzing the simulation signals.
介绍了短时傅立叶变换和小波变换两种时频分析方法,通过对仿真信号的分析,阐述了两种方法在分析非平稳信号时的优势和优缺点。
5)  nonstationary signal
非平稳信号
1.
The Research on Nonstationary Signal Based on Time-Varying Autoregressive Model and Its Application in Fault Diagnosis;
基于时变自回归的非平稳信号建模及故障诊断应用研究
2.
This paper presents three methods of time-frequency analysis of nonstationary signal:Windowed Fourier Transform(WFT),Winger-Ville Distribution(WVD) and Wavelet Analysis,and illuminates their traits and limitations.
讨论了当前常用的三种非平稳信号时频分析方法,即窗口傅立叶变换(Windowed Fourier Transform)、Wigner分布(Winger-Ville Distribution)和小波分析(Wavelet Analysis)的特点,及其适用的局限性。
3.
Frequency-Hopping signal is a typical nonstationary signal and must adopt nonstationary signal processing methods.
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。
6)  nonstationary signals
非平稳信号
1.
Because of making the best of time-frequency domain characteristics of the signals, this method is suitable for not only time-invariance and stationary signals but also time-variance and nonstationary signals.
由于充分利用了信号的时频域特征,此方法既适用于时不变的、平稳信号又适用于时变的、非平稳信号,与传统的一维ESPRIT方法比较,改善了DOA估计的性能,尤其是在低信噪比和空间近角度时,性能的改善是明显的。
2.
In this paper we propose a blind source method based on Wigner Ville distribution, which can separate nonstationary signals effectively.
本文基于时频分析 ,通过利用信号的Wigner Ville分布 ,得出一种新的盲源分离方法 ,该方法能有效分离非平稳信号 。
补充资料:分析信号处理
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性质:在分析信号中,常常混杂有噪声和其他的干扰信号,噪声和干扰信号不仅会引起误差,而且直接限制了分析方法的检出能力,须加处理。分析信号处理是通过对信号的平滑、滤波、积分、求导、变换等操作消除噪声和干扰信号的影响,可靠地检出所需要的分析信号,并以人们所需要的形式记录和显示分析信号的过程。

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