Abstract
This paper addresses a novel model order reduction (MOR) technique with dominant substructure preservation. This process leads to cost minimization of the considered physical system which could be of any type from motors to circuitry packaging to software design. The new technique is formulated based on an artificial neural network (ANN) transformation along with the linear matrix inequality (LMI) optimization method. The proposed method is validated by comparing its performance with the following well-known reduction techniques Balanced Schur Decomposition (BSD) and state elimination via balanced realization.
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Alsmadi, O.M.K., Abo-Hammour, Z.S., Al-Smadi, A.M. (2010). Efficient Substructure Preserving MOR Using Real-Time Temporal Supervised Neural Network. In: Zavoral, F., Yaghob, J., Pichappan, P., El-Qawasmeh, E. (eds) Networked Digital Technologies. NDT 2010. Communications in Computer and Information Science, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14306-9_20
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DOI: https://doi.org/10.1007/978-3-642-14306-9_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14305-2
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