人们知道两种噪音模型就能充分代表大部分图像中的噪音，即高斯噪音和脉冲噪音。
Two noise models can adequately represent most noise added to images: Gaussian noise and impulse noise.
本文探讨了基于时域的语音切分算法，在前人研究的基础上，提出一种改进算法——自适应、前后搜索和检测短时脉冲噪音算法。
This paper researches on speech detection algorithm based on time domain, and describes an adaptive, both forwards and backwards search, detecting short-term pulse noise algorithm.
脉冲光会跟着一起散开，并会渗入噪音并使信号损失。
Pulses of light can bleed together, adding noise and degrading the signal.
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