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Noise reduction, smoothing and time interval segmentation of noisy signals using an energy optimisation method

机译:使用能量优化方法降噪,平滑和时间间隔的噪声信号的平滑和时间间隔分割

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摘要

Noise reduction and time interval segmentation of a noise-contaminated piecewise continuous signal is considered by the authors as a non-linear optimisation problem. The mathematical framework of this method is presented both in continuous-time and discrete-time domains. The smoothed signal and segmented time intervals of the original noisy signal are calculated as an optimised solution for an energy functional. An algorithm similar to the level set method is developed to find the optimised solution. In this algorithm, the discontinuity points separating consecutive continuous signals are preserved while the noise is reduced. Therefore this method fundamentally exhibits a better performance compared with a traditional low-pass filter suppressing high frequency components, including discontinuity points. The results also demonstrate a better quality in noise reduction in comparison to the median and Gaussian filters.
机译:作者认为,被噪声污染的分段连续信号的降噪和时间间隔分段是非线性优化问题。在连续时间域和离散时间域中都介绍了此方法的数学框架。计算出原始噪声信号的平滑信号和分段时间间隔,作为能量功能的优化解决方案。开发了一种类似于水平集方法的算法来找到优化的解决方案。在该算法中,保留了分隔连续连续信号的不连续点,同时降低了噪声。因此,与抑制包括不连续点的高频分量的传统低通滤波器相比,该方法从根本上表现出更好的性能。结果还表明,与中值和高斯滤波器相比,降噪质量更高。

著录项

  • 作者

    S. Mahmoodi; B.S. Sharif;

  • 作者单位
  • 年度 2006
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"english","id":9}
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