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Efficient Substructure Preserving MOR Using Real-Time Temporal Supervised Neural Network

  • Othman M. K. Alsmadi
  • Zaer. S. Abo-Hammour
  • Adnan M. Al-Smadi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 88)

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.

Keywords

Neural networks model order reduction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Othman M. K. Alsmadi
    • 1
  • Zaer. S. Abo-Hammour
    • 2
  • Adnan M. Al-Smadi
    • 3
  1. 1.Department of Electrical EngineeringUniversity of JordanAmmanJordan
  2. 2.Department of Mechatronics EngineeringUniversity of JordanAmmanJordan
  3. 3.Department of Computer ScienceAl Al-Bayt UniversityMafraqJordan

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