1) slow change singular signals
缓变奇异信号
1.
singular signals are classfied into sharp variation singular signals and slow change singular signals according to their singularity characterization in this paper,the first ones have sharp changes or the tendency of sharp changes,and the otherones have the tendency of slow changes.
按照信号的奇异性特征 ,本文将奇异信号分为剧变奇异信号和缓变奇异信号 ,前者有剧变或剧变的趋势 ,后者具有缓慢变化的趋势 。
2) time-varying signal with singular values
奇异值时变信号
3) singular signal
奇异信号
1.
The method for singular signal detection based on fractal technique is presented.
提出了基于分形的奇异信号的检测方法 ,给出了奇异信号的数学模型、检测原理和实现算法。
2.
The function of wavelet transformation in the diagnosis of singular signal is elaboraed.
阐述了小波变换在诊断奇异信号中的作用。
3.
The relationship between wavelet analysis and singular signal detecting is deduced,and the example of a pressure sensor singular signal detecting is presented.
推导了小波分析与奇异信号检测的之间的关系,并对某压力传感器的信号进行了奇异值的检测。
4) singularity signal
奇异信号
1.
By using of wavelet package transform module maxima,singularity signal of motor are detected and determined at motor stalling.
利用小波包变换模极大值原理对电机堵转时的奇异信号进行定位和确定持续时间,通过小波包分解与重构,更好地提取电机堵转时的特征信息。
2.
Gaussl wavelet is suitable for the detection of an abruptly changing singularity signal.
在分析行波信号奇异性的性质和小波基特征的基础上,提出了奇异信号检测中小波基的选择原则,针对行波信号中出现的2种不同类型的奇异信号分别选出合适的小波基。
6) Signal singularity
信号奇异性
1.
Detection of one dimension signal singularity based on Wavelet transform;
基于小波变换的一维信号奇异性检测研究
2.
According to the signal features of various automatic block systems, a signal singularity detection method based on the wavelet analysis technique is adopted in this paper to carry out singularity detection for the data recorded by the cab signaling recorder.
根据铁路目前各种自动闭塞制式的信号特点,利用基于小波分析技术的信号奇异性检测方法,通过机车信号记录器数据分析处理软件对机车信号记录器所记录的波形信号进行奇异性检测。
补充资料：缓变pn结（gradedp-njunction）
缓变pn结（gradedp-njunction）
从p区到n区掺杂浓度逐渐改变的pn结，如用固态扩散工艺制造的pn结。大多数缓变pn结数学上可作为线性缓变结处理。通常由扩散工艺制备的pn结为缓变pn结，但在浅扩散结或高反偏时它更接近于单边突变pn结。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条