基于自适应混沌变换的快速变化信号辨识

M. Berezowski, M. Lawnik
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引用次数: 11

摘要

讨论了强非线性快变信号辨识的自适应方法。该方法是基于信号本身的混沌映射的自适应采样设计的。所提出的采样方法可在线应用于化学反应器的自动控制(实时识别浓度和温度的波动)、医学(实时识别心电和脑电图信号)等领域。在本文中,我们提出了一种识别weerstrass函数和心电信号的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of fast-changing signals by means of adaptive chaotic transformations
The adaptive approach of strongly non-linear fast-changing signals identification is discussed. The approach is devised by adaptive sampling based on chaotic mapping in yourself of a signal. Presented sampling way may be utilized online in the automatic control of chemical reactor (throughout identification of concentrations and temperature oscillations in real-time), in medicine (throughout identification of ECG and EEG signals in real-time), etc. In this paper, we presented it to identify the Weierstrass function and ECG signal.
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