Nonlinear interaction of two plane acoustic waves in the (0,0) mode of a square duct is investigated from the viewpoint of chaotic dynamics. Phase-space portraits are reconstructed from time series obtained in an experiment. It is demonstrated that limit sets formed by the phase space trajectories are “attractors.” The largest Lyapunov exponent and correlation dimension of these attractors are calculated, and the results indicate that these attractors are chaotic.

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Epilepsy is a disease with chronic disorder of nervous system, which owns the characteristic of repeat attacking and difficult to cure. So, it's significant to study the forecasting method and give preventive treatment. In this paper, the approximate entropy and the maximum Lyapunov exponent based on the improved Wolf algorithm were used to extract and analyze the characteristic of nonlinear dynamics of the human epileptic electroencephalograph under different states, the results indicated that two methods can effectively predict preictal state and approximate entropy show better performance. Results calculated in the wavelet domain were compared between the two methods and better effect can be obtained under first order discrete wavelet transform. The early waning and automatic drug release system was simulated by LabVIEW Virtual Instrument, with 80% sensitivity and 90.9% specificity. The automatic process and drug-release rate controlling by characteristic value is simulated, which show important application value.Keywords-the warning system of epilepsy; approximate entropy; Lyapunov exponent; discrete wavelet transform; automatic drug release system