优化使用小波包树的分析波形

I. Nicolae, P. Nicolae, Daniel C. Cîrstea, Ilie Gheorghe
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引用次数: 3

摘要

当涉及到波形分析时,小波包树代表了一个越来越受欢迎的话题。它允许时频分析在更窄的频率范围内提供信息(与更快的离散小波分解相比),但是计算资源明显大于其他类型的基于小波的分析。为了允许这种类型的分析在实时应用程序中可用,也就是说,为了减少运行时间,我们构思并测试了原始算法。本文的第一部分简要介绍了以前实现的算法,以及它们的优缺点。随后,提出了一种新的运行时优化算法。详细介绍了数据结构、工作流程、测试和错误研究。该算法将使用WPT评估聚类谐波贡献的叠加定理所需的运行时间减少了59%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimized use of Wavelet Packet Trees for the analysis of electrical waveforms
Wavelet packet trees represent a topic which grows in popularity when it comes to analysis of electrical waveforms. It allows for time-frequency analysis providing information on narrower ranges of frequency (as compared to the faster Discrete Wavelet Decomposition), but the computational resources are significantly greater than that involved in other types of wavelet-based analysis. In order to allow for this type of analysis to be usable in real-time applications, that is – to reduce the runtime, original algorithms were conceived and tested. In the first part of this work, previously implemented algorithms are briefly described, along with their pros and cons. Afterward, a new runtime optimization algorithm is proposed. Details on data structures, workflow, tests and study of errors are provided. This algorithm diminishes with up to 59% the runtime required by the application of the superposition theorem in order to evaluate the contribution of clustered harmonics using WPT.
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