蜂窝移动通信是现代通信的主流，但是这种通信系统的随机性很大，用通常的方法去估计它的通信系统的优劣是十分困难的。
The Cellular Mobile communication is Modern communications mainstream, but this communication systems has much randomicity, estimating this communication systems with the usual method is difficult.
数据处理中，采用了去极值平均滤波的数字滤波方法，有效地抑制了随机干扰及脉冲干扰，增加了系统的稳定性，提高了测量精度。
To restrain random interference and pulse interference and improve measurement accuracy and stability, the digital filtering method which average the data crossing the extremum out is adopt.
注意：为了更简单的解说所以我们采用了一个随机方法去产生一个地形，因此它每一次都不一样。
NOTE: I keep saying similar because we are using a random method for generating the terrain, so it will be different everytime.
针对强噪声背景中的弱信号检测问题，在经典随机共振处理方法的基础上，利用小波良好的去噪特点，提出了随机共振加小波去噪检测弱信号的新方法。
Concerning the detection of weak signal in stronger noise background, a novel method was proposed in terms of stochastic resonance processing and by using the better de-noise feature of wavelet.
提出了一种用随机加权的方法去逼近线性回归模型中M-估计的渐近分布。
Rao and Zhao (1992) developed the random weighting method for M-estimates in regression models.
本文方法保留了最大-最小值方法去除随机脉冲噪声的优点，且检测算法简单，去噪快速有效。
The experiments show that the proposed method retains the merits of maximum-minimum method and is simple and effective in random impulsive noise removal.
方法将80只豚鼠随机分为4组，分别为空白组、致石组、熊胆粉预防组、熊去氧胆酸(UDCA)预防组。
Methods Totally 80 guinea pigs randomly divided into 4 groups i. e. blank group, lithogenic group, prevention by bear bile powder group and UDCA group.
本文主要是使用离散二进小波变换，采用小波域阈值的去噪方法对地震信号中随机噪声进行分析和处理。
This paper mainly points out how to analyze and get rid of the random noise of seismic data by using the wavelet transform and de-noising method by threshold filter in wavelet domain.
本文主要是使用离散二进小波变换，采用小波域阈值的去噪方法对地震信号中随机噪声进行分析和处理。
This paper mainly points out how to analyze and get rid of the random noise of seismic data by using the wavelet transform and de-noising method by threshold filter in wavelet domain.
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