DFT%20calculation%20of%20the%20generalized%20and%20drazin%20inverse%20of%20a%20polynomial%20matrix - PowerPoint PPT Presentation

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DFT%20calculation%20of%20the%20generalized%20and%20drazin%20inverse%20of%20a%20polynomial%20matrix

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http://anadrasis.math.auth.gr. Objectives ... known ones in the case where the degree and the size of the polynomial matrix get bigger. ... – PowerPoint PPT presentation

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Title: DFT%20calculation%20of%20the%20generalized%20and%20drazin%20inverse%20of%20a%20polynomial%20matrix


1
DFT calculation of the generalized and drazin
inverse of a polynomial matrix
N. Karampetakis, S. Vologiannidis
  • Department of Mathematics
  • Aristotle University of Thessaloniki
  • Thessaloniki 54006, Greece
  • http//anadrasis.math.auth.gr

2
Objectives
  • A new algorithm is presented for the
    determination of the generalized inverse and the
    drazin inverse of a polynomial matrix based on
    the discrete Fourier transform.
  • The above algorithms are implemented in the
    Mathematica programming language.

3
Discrete Fourier Transform
4
Generalized Inverse
5
Computation of the generalized inverse
6
Computation of the generalized inverse via
DFTStep 1. (Evaluation of the polynomial a(s,z))
7
Step 2. (Evaluate )
8
Step 3. (Evaluate
where )
9
Step 4. Evaluate the generalized inverse
10
Drazin Inverse
11
Drazin Inverse
12
Computation of the Drazin Inverse via DFTStep 1
(Evaluation of a(s,z))
13
Step 2
14
Step 3 (
)
15
Step 4
16
Step 5
17
Step 6. (Evaluation of the Drazin inverse)
18
Implementation
  • The above algorithms have been implemented in
    Mathematica.
  • The following graphs shows the efficiency of the
    DFT based algorithms compared to the algorithms
    described in Karampetakis 1997, Staminirovic and
    Karampetakis 2000. The red surface represents
    the DFT based algorithms.

19
Graphs
20
Conclusions
  • Two new algorithms have been presented for the
    computation of the generalized inverse and Drazin
    inverse of a polynomial matrix.
  • The proposed algorithms proved to be more
    efficient from the known ones in the case where
    the degree and the size of the polynomial matrix
    get bigger.
  • The proposed algorithms can be easily extended to
    the multivariable polynomial matrices.
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