Please use this identifier to cite or link to this item:
|Title:||Proper orthogonal decomposition and its applications - Part II: Model reduction for MEMS dynamical analysis|
|Source:||Liang, Y.C., Lin, W.Z., Lee, H.P., Lim, S.P., Lee, K.H., Sun, H. (2002-09-19). Proper orthogonal decomposition and its applications - Part II: Model reduction for MEMS dynamical analysis. Journal of Sound and Vibration 256 (3) : 515-532. ScholarBank@NUS Repository. https://doi.org/10.1006/jsvi.2002.5007|
|Abstract:||Proper orthogonal decomposition (POD) methods are popular tools for data analysis aimed at obtaining low-dimensional approximate descriptions of a high-dimensional process in many engineering fields. The applications of POD methods to model reduction for microelectromechanical systems (MEMS) are reviewed in this paper. In view of the fact that existing POD methods in the model reduction for dynamic simulation of MEMS dealt with only noise-free data, this paper proposes a neural-network-based method that combines robust principal component analysis (PCA) neural network model with Galerkin procedure for dynamic simulation and analysis of non-linear MEMS with noisy data. Simulations are given to show the performance of the proposed method in comparison with the existing method. Compared with the standard PCA neural network model, the robust PCA neural network model has a number of numerical advantages such as the stability and robustness to noise-injected data and the faster convergence of iterations in the training stages than the existing neural network technique. The macro-model generated by using the eigenvectors extracted from the proposed method as basis functions shows its flexibility and efficiency in the representation and simulation of the original non-linear partial differential equations. © 2002 Elsevier Science Ltd. All rights reserved.|
|Source Title:||Journal of Sound and Vibration|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Feb 15, 2018
WEB OF SCIENCETM
checked on Feb 5, 2018
checked on Feb 20, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.