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Sinusoidal signal extraction from chaotic background using wavelet packet transform

机译:使用小波包变换的混沌背景中的正弦信号提取

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In this paper, we propose a novel signal extraction algorithm from chaotic background using wavelet packet transform (WPT). It has been proved that many nature signals can be modeled as chaos. So, extracting the signals from the chaotic background is very important. Classification features of chaos are often localized both in time and frequency, so extracting the signals form them by general transform methods is very difficult. WPT can provide an arbitrary time-frequency decomposition for the signals. Therefore, by selecting a suitable basis, the signals can be extracted. This paper is mainly concerned with sinusoidal signal extraction from Lorenz chaotic background. The performance of extraction by WPT is given in the paper.
机译:在本文中,我们提出了一种使用小波包变换(WPT)的混沌背景信号提取算法。已经证明,许多自然信号可以被建模为混乱。因此,从混沌背景中提取信号非常重要。混乱的分类特征通常在时间和频率上定位,因此通过一般变换方法提取信号的提取非常困难。 WPT可以为信号提供任意时频分解。因此,通过选择合适的基础,可以提取信号。本文主要涉及Lorenz混沌背景的正弦信号提取。用WPT提取的性能在纸上给出。

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