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Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques

机译:基于小波技术的分子动力学模拟分析

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In this paper, I focus on describe, calculate and analyze of molecular dynamic (MD) simulations using wavelet transform (WT) techniques by analogy with its use in signal and image processing, so that I would like to talk about the theoretical background wavelet transform methods, including what properties they have, their common types, and how to operate them. Secondly, I would introduce the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations., the WT permits filtering out the high-frequency noise without completely omitting the high-frequency phenomena whose contribution is crucial in cases where the dynamics is localized in frequency and time. Medical applications could be studied in which biomedical related research requires lots of mathematical and engineering techniques to analyze data. The WT is observed to excel in reconstructing the original signal by a subset of the basis used in the analysis and in identifying the occurrence of rare phenomena by examining the wavelet energies at highresolution levels.
机译:在本文中,我将重点介绍通过使用小波变换(WT)技术来模拟,计算和分析分子动力学(MD)模拟,并将其用于信号和图像处理,因此,我想谈一谈理论背景小波变换方法,包括它们具有哪些属性,它们的常见类型以及如何操作它们。其次,我将介绍连续小波变换,它特别适合于诸如分子动力学模拟之类的时程数据。WT可以滤除高频噪声,而不会完全忽略对高频噪声起重要作用的高频现象。动态在频率和时间上局部化的情况。可以研究医学应用,其中与生物医学相关的研究需要大量的数学和工程技术来分析数据。通过分析中使用的基础的子集,可以观察到WT擅长重构原始信号,并通过检查高分辨率水平的小波能量来识别稀有现象的发生。

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