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

Abstract

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.