为提高电压扰动信号分类识别的精度，提出了一种基于数学形态学与动态时间扭曲的新算法。
A novel algorithm based on the mathematical morphology and the dynamic time warping was proposed for improving the accuracy of voltage disturbance classification.
介绍了一种基于数学形态学和动态灰度变化方法相结合的纱线气圈边缘提取方法。
This article introduces a method of edge extraction of yarn balloon, which bases on mathematic morphology and the transformation of dynamical gray algorithm.
结合实际拍摄的动态交通图像，提出了基于数学形态学和帧差法的交通图像噪声滤除方法。
A noise-filtering algorithm of real traffic video images based on mathematical morphology and frame difference was proposed.
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