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The application of symplectic geometry on nonlinear dynamic analysis of the experimental data

机译:辛几何在实验数据的非线性动态分析中的应用

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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 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.
机译:对于对实验数据的非线性动态分析,通常使用SVD分解来重建吸引物的嵌入尺寸,因为其简单性。但是,对于SVD分解几乎没有得到良好的结果,在实验数据的吸引子重建中得到良好的结果。为此,提出了辛的几何方法,以估计本文重建吸引子的嵌入维度。我们说明了该方法的可行性,并给出了动作表面EMG信号的嵌入尺寸。

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