傅立叶变换是分析信号奇异性的传统方法。
The Fourier transform is a classical method for analyzing signal singularities.
算法充分利用连续小波变换探测信号奇异性的能力和小波的多分辨率特性。
The new algorithm mainly recurred to the ability of detecting singularity in signal by continuous wavelet transform and multi-resolution analysis of wavelet transform.
提出了一种用于故障信号奇异性检测的小波基选择方法一按照小波规则性系数选择小波基。
A method of choosing a wavelet for the detection of singularities of a fault signal is presented. The method is to choose a wavelet by the regularities of the wavelet and the signal.
利用小波变换系数的模值与信号奇异性指数之间的关系，从调频信号中提取出调制信号的频率。
Frequency of modulated signals is extracted from frequency-modulated signals by using the relationship between the modulus of wavelet transform coefficient and the singular exponent.
为了准确客观地检测出爆裂噪声的存在，提出了基于噪声信号奇异性的光耦器件爆裂噪声检测方法。
In order to detect the presence of burst noise in optocoupler device accurately and objectively, a new method was put forward based on singularity of noise.
文章给出了基于小波分析的信号奇异性检测理论，通过对突变信号进行小波分析可以发现结构的损伤情况。
The signal singularity detection theory based on wavelets analysis is given. Through the study of those singularity, the damage situation of the structure may be discovered.
在分析小波变换物理本质和奇异性检测原理的基础上，研究了小波基和白噪声对信号奇异性检测性能的影响。
Based on analyzing the physical essence and the principle of singularity detection, this paper discusses the effect of wavelet bases and white noise on signal singularity detection.
本文利用小波变换系数的模的平方值与信号奇异性指数之间的关系，从超声回波信号中提取出了胎儿的心率。
The fetal heart rate can be extracted from the returning signal of ultrasound by way of the connection between the modulus of the wavelet transform coefficient and the singular exponent.
通过对信号奇异性的检测和对信号的消噪，提取出了被检测信号的模极大值，进而实现了行波信号的故障测距。
By detecting signal strangeness and reducing signal noise, the paper arrives at the maximum value of the detected signal, thus the fault location of the traveling wave signal is achieved.
文中对奇异性指数的求解问题进行了较详细的讨论和研究，同时对不同小波基下的信号奇异性检测情况进行了分析和比较。
The thesis has discussed the calculating of the Lipschitz exponent, and analysised and compared the condition between wavelet bases and singularity detection of signal.
在论述了小波分析、信号奇异性与小波变换模极大值性质关系的基础上，本文给出了一种基于小波变换模极大值的信号去噪算法。
Based on the wavelet transform and the relation between signal singularity and wavelet transform modular maximum, a noise removal technique is discussed.
这种方法可以在尽量保留信号奇异性穴如边缘熏纹理等雪相关信息情况下熏使得图像平滑熏噪声消除，是红外图像消噪的一种新方法。
This method can repress noise in reserving the related information, such as edge and vein etc. It is a new method of infrared image noise repression.
试验表明，系统可以发现故障机械振动信号带有的奇异性，实现旋转机械的故障诊断。
Experimentation results indicate that the singularity of the fault machinery vibration signal can be detected and the machinery fault can be discovered by the system.
研究了信号的奇异性检测问题。
基于信号的奇异性检测理论，利用小波分解的高频系数是否具有模极大值作为区分稳态和非稳态现象的判据。
Based on the theory of signal strangeness detect, the maxima modulus in high frequency of wavelet resolving can be used as a criterion to classify steady and non-steady state phenomena.
提出采用切削力信号的奇异性指数作为衡量刀具磨损的参量。
The singular index of cutting force signal is proposed as a parameter for detecting cutter's wear.
本文阐述了利用小波分析来检测信号的奇异特征的原理，并对桩基础检测信号的奇异性进行了提取。
This paper illustrates principle of the peculiarity of signal test based on wavelet analysis, and extracts the peculiarity of signal test in pile foundation.
信号的奇异性通常包含有十分重要的信息，是信号的特征之一。
Singularity signal usually contains very important information, is one of the characteristics of the signal.
根据斜拉桥结构在振动时受损部位的振动信号的奇异性，利用小波奇异性检测理论分析斜拉桥结构在受损时的振动信号，判断结构损伤情况。
Based by singularity of vibration signal of damage position on cable-stayed bridge as vibrating, we can analyze vibration signal when cable-stayed bridge is damaged to estimate structure damage.
小波分析具有空间局部化性质，利用小波分析来分析信号的奇异性及奇异性的位置和奇异度的大小是比较有效的。
Wavelet analysis has space localization property. It is very effective to analyze the signal singularity and singularity location and scale by wavelet analysis.
从工程应用的角度出发，进行信号的分解与重构、信号的奇异性检测、数据的压缩与重构、信号的消噪等若干方面的研究。
From the Angle of engineering application, the paper studies signals division and reconstruction, signals strangeness detection, data condensation and reconstruction, and signals noise reduction.
在提出脉冲提取思想的基础上，利用局部放电信号所固有的奇异性特征，将小波变换的奇异性检测原理应用于提取局部放电脉冲。
A wavelet domain singularity detection algorithm, based on the theory of pulse extraction, is applied in partial discharge (PD) pulse extraction utilizing the singularity of PD signal.
十分准确地刻画出声波信号的奇异性，并应用于交变语音信号处理中。
The strangeness of acoustic wave signals is precisely described and is applied to the processing of alternating speech signals.
并且通过从实验台采集到的实际齿轮振动信号分析，利用小波变换对其进行奇异性监测研究，取得了良好的效果。
And through gathering actual gear wheel vibration signal from laboratory, utilizing wavelet transform to study singularity monitoring, has made the good results.
测得的信号低电阻电缆故障的分析表明：这种方法可减少偏差的奇异性检测，提高了故障定位的精度。
Analysis of measured signal of low resistance cable fault shows that: the method reduces deviation of singularity detection and improves precision of fault location.
但研究发现在极低信噪比，由于观测信号的样本协方差矩阵具有奇异性，这使得ICA去噪算法中的白化处理步骤无法进行。
But in the very low SNR circumstance, because of the covariance matrix of the observed signals being singularity, the ICA denoising method can not be used.
通过对信号与噪声奇异性的分析，得出信号与噪声的小波变换模极大值在各个尺度上的表现截然相反的结论。
The singularities of signals and noises are investigated. A conclusion is drawn that the wavelet modulus maxima of signals have contrary behaviors from that of noises.
将声门闭合在语音信号中表现出相应的奇异性，与图像边缘的灰阶突变进行等价对比，直接将小波变换用于声门闭合奇异型的检测，并不会得到预期效果。
If the wavelet transform is directly implemented in pitch detection, comparing the glottal closure singularity of speech signal with image grey break, we will not obtain the anticipative result.
将声门闭合在语音信号中表现出相应的奇异性，与图像边缘的灰阶突变进行等价对比，直接将小波变换用于声门闭合奇异型的检测，并不会得到预期效果。
If the wavelet transform is directly implemented in pitch detection, comparing the glottal closure singularity of speech signal with image grey break, we will not obtain the anticipative result.
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