辛几何在实验数据非线性动力学分析中的应用

Min Lei, Zhizhong Wang, Zhengjin Feng
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引用次数: 8

摘要

对于实验数据的非线性动态分析,由于SVD分解的简单性,通常采用SVD分解来重构吸引子的嵌入维数。然而,奇异值分解(SVD)在实验数据的吸引子重构中很难得到很好的结果。为此,本文提出了辛几何方法来估计重构吸引子的嵌入维数。说明了该方法的可行性,并给出了动作面肌电信号的嵌入维数。
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The application of symplectic geometry on nonlinear dynamics analysis of the experimental data
For nonlinear dynamic analysis of the experiment data, one often uses SVD decomposition to reconstruct embedding dimension of attractor because of its simpleness. However, it is hardly for singular value decomposition (SVD) decomposition to get good results in the attractor reconstruction of the experiment data. For this, symplectic geometry method is proposed to estimate embedding dimension of reconstruction attractor in this paper. We illustrate the feasibility of this method and give the embedding dimension of the action surface EMG signal.
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