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Stochastic Optimal Control of Spherically Symmetric Piezoelectric Shells

ZHANG Wei;SUN Yin;YING Zu-guang;FENG Ju

2012, 32 (1): 43-46. DOI: 10.3969/j.issn.1006-1355-2012.01.010

Abstract （1433）

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The stochastic optimal control of a spherically symmetric piezoelectric shell under random boundary excitations is studied. The dynamic equilibrium equation, the kinetic equation, the charge conservative equation and the electrical and mechanical coupling constitutive equations of the piezoelectric shell are given. These equations and the performance parameters construct a stochastic optimal control problem. The electric potential integral is presented to convert the governing equations into a mechanical vibration equation. Using the displacement transformation and the Galerkin method, the partial differential vibration equation is converted into ordinary differential equations for optimal control. Based on the stochastic dynamical programming principle, the HJB equation is derived and then the optimal control electric potential for the piezoelectric shell is determined. The frequency-response function, response power spectrum density and correlation function matrices of the controlled shell system are presented for estimating the random response. Finally, numerical results are given to demonstrate the effectiveness of the stochastic optimal control of the piezoelectric shell.

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Statistical Analysis for Database Dependence in Classification of Emotional Speech by using Different Features Extraction Approaches

SUN Ying;ZHANG Xue-ying

2011, 31 (4): 132-136. DOI: 10.3969/j.issn.1006-1355-2011.04.031

Abstract （1906）

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Four approaches of feature extraction: the Linear Predictive Cepstral Coefficient (LPCC), the Teager Energy Operator (TEO), the Mel-Frequency Cepstral Coefficient (MFCC) and the Zero Crossings with Peak Amplitudes (ZCPA) are described in this paper. And these approaches are applied to emotional speech recognition. Two kinds of experiments are carried out. The first one is a kind of single language experiments with TYUT database and Berlin database. Its results show that these four approaches can represent speech emotion effectively by using single language of single database. MFCC has the best result of the four approaches. The second kind experiment is merge-database of single language. Most previous work on emotional feature extraction is based on a special language of single speech database. But in practice, the environment of the speaker is various. So the study of emotional feature extraction based on merge-database is significative. Experiments of the second kind indicate that the four features are all database dependent. ZCPA features are of the least database dependence of the four approaches.