WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems.
WAVOS: a MATLAB toolkit for wavelet analysis and visualization of oscillatory systems.
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DOI：
10.1186/1756-0500-5-163
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发表时间：
2012-03-26
影响因子：
1.8
通讯作者：
Petzold LR
中科院分区：
文献类型：
--
作者：
Harang R;Bonnet G;Petzold LR
小波已被证明是分析周期性数据的强大技术，例如在昼夜节律振荡器分析中出现的数据。虽然连续和离散小波变换的许多实现都是可用的，但我们知道没有任何软件在设计时考虑到非技术最终用户。通过开发一个工具包，使没有丰富编程经验的最终用户也可以进行这些分析，我们希望促进小波分析的更广泛使用。我们开发了 WAVOS 工具包，用于振荡系统的小波分析和可视化。 WAVOS 具有连续 (Morlet) 和离散 (Daubechies) 小波变换功能，并在 MATLAB 中提供简单、用户友好的图形用户界面。该界面允许从多种标准文件格式导入数据、可视化、处理和分析数据，并在不使用命令行的情况下导出数据。我们的工作受到昼夜节律数据挑战的推动，因此预先选择了适合此类数据分析的默认设置，以最大程度地减少微调的需要。然而，该工具包足够灵活，可以处理各种振荡信号，并且可以在更一般的情况下使用。我们推出了 WAVOS：一个基于小波的综合 MATLAB 工具包，可轻松实现振荡数据的可视化、探索和分析。 WAVOS包括Morlet连续小波变换和Daubechies离散小波变换。我们已经说明了 WAVOS 的使用，并展示了其在生物发光和车轮运行数据的昼夜节律数据分析方面的实用性。 WAVOS 可在 http://sourceforge.net/projects/wavos/files/ 免费获取
Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been designed with the nontechnical end-user in mind. By developing a toolkit that makes these analyses accessible to end users without significant programming experience, we hope to promote the more widespread use of wavelet analysis. We have developed the WAVOS toolkit for wavelet analysis and visualization of oscillatory systems. WAVOS features both the continuous (Morlet) and discrete (Daubechies) wavelet transforms, with a simple, user-friendly graphical user interface within MATLAB. The interface allows for data to be imported from a number of standard file formats, visualized, processed and analyzed, and exported without use of the command line. Our work has been motivated by the challenges of circadian data, thus default settings appropriate to the analysis of such data have been pre-selected in order to minimize the need for fine-tuning. The toolkit is flexible enough to deal with a wide range of oscillatory signals, however, and may be used in more general contexts. We have presented WAVOS: a comprehensive wavelet-based MATLAB toolkit that allows for easy visualization, exploration, and analysis of oscillatory data. WAVOS includes both the Morlet continuous wavelet transform and the Daubechies discrete wavelet transform. We have illustrated the use of WAVOS, and demonstrated its utility for the analysis of circadian data on both bioluminesence and wheel-running data. WAVOS is freely available at http://sourceforge.net/projects/wavos/files/