Model reduction of 2-D systems via orthogonal series

P. N. Paraskevopoulos, P. E. Panagopoulos, G. K. Vaitsis, S. J. Varoufakis, G. E. Antoniou

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

In this article, the problem of model reduction of 2-D systems is studied via orthogonal series. The algorithm proposed reduces the problem to an overdetermined linear algebraic system of equations, which may readily be solved to yield the simplified model. When this model approximates adequately the original system, it has many important advantages, e.g., it simplifies the analysis and simulation of the original system, it reduces the computational effort in design procedures, it reduces the hardware complexity of the system, etc. Several examples are included which illustrate the efficiency of the proposed method and gives some comparison with other model reduction techniques.

Original languageEnglish
Pages (from-to)69-83
Number of pages15
JournalMultidimensional Systems and Signal Processing
Volume2
Issue number1
DOIs
Publication statusPublished - 1 Mar 1991

    Fingerprint

Keywords

  • Chebyshev polynomials
  • Pade
  • Walsh and Chebyshev series
  • block pulse
  • fraction expansion
  • model reduction
  • orthogonal series
  • shifting transformation matrix

Cite this

Paraskevopoulos, P. N., Panagopoulos, P. E., Vaitsis, G. K., Varoufakis, S. J., & Antoniou, G. E. (1991). Model reduction of 2-D systems via orthogonal series. Multidimensional Systems and Signal Processing, 2(1), 69-83. https://doi.org/10.1007/BF01940473