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Modular shift of a polynomial matrix using Matlab
Hurák, Zdeněk ; Šebek, Michael
Efficient algorithm for modular shift of a polynomial matrix is proposed in this note.The algorithm avoids any iteration that is inherent in standard Euclidean algorithm for division of polynomial matrices.It assumes that the denominator polynomial matrix is row-reduced.If it is not,it can always be transformed into row-reduced form accepting some additional computational cost. Numerical experiments with an implementation of the proposed algorithm in Matlab are reported.
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Polynomial Toolbox
Hromčík, M. ; Šebek, M. ; Ježek, Jan
Quite recently the polynomial design methods found a new great field of application outside the control area: the algebraic approach have been used successfully in signal processing and mobile communications. In contrast to the control systems synthesis, polynomials and polynomial matrices with complex coefficients are often required when designing filters, equalizers, decouplers and other components of mobile phones for instance.
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New algorithm for spectral factorization and its application in signal processing
Ježek, Jan ; Hromčík, Martin ; Šebek, Michael
In this report a new algorithm is presented for the spectral factorization of a two-sided symmetric polynomial. The method is based on the discrete Fourier transform theory (DFT) and its relationship to the Z-transform. Involving DFT computational techniques, namely the famous fast Fourier transform routine (FFT), brings high computational efficiency and reliability. The power of the proposed procedure is employed in a particular practical signal processing application.
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Simultaneous feedback stabilization: A survey
Hurák, Zdeněk ; Šebek, Michael
This paper gives a short introduction into the topic of simultaneous feedback stabilization, which is recognized as one of the fundamental open problems in control theory. In this paper, some essential defnitions are given, the relation between strong and simultaneous stability is explained, the recent result on complexity of the topic is stated, and some recent approaches based on LMI paradigm are described. SISO systems are considered only.
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An LMI condition for robust stability of polynomial matrix polytopes
Henrion, D. ; Arzelier, D. ; Peaucelle, D. ; Šebek, Michael
A sufficient LMI condition is proposed for checking robust stability of apolytope of polynomial matrices. It hinges upon two recent results: a new approach topolynomial matrix stability analysis and a new robust stability condition for convex polytopic uncertainty. Numerical experiments illustrate that the condition narrows signifficantly the unavoidable gap between conservative tractable quadratic stability results and exact NP-hard robust stability results.
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Numerical algorithms for polynomial matrices
Hromčík, Martin ; Šebek, Michael
This report is devoted to new numerical methods for computations with polynomials and polynomial matrices that are encountered when solving the problems of control systems design via the algebraic methods. A distinguishing feature of our approach is the extensive employment of the discrete Fourier transform techniques, namely of the famous Fast Fourier Transform routine and its relation topolynomial interpolation and Z-transform.
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Polynomial toolbox and control education
Hromčík, Martin ; Šebek, Michael
In this report we give our experience with employing thePolynomial Toolbox for Matlab version 2 at the lectures and labs of Algebraic Design Methods course taught at the Czech Technical University in Prague. Practical examples illustrating the Toolbox performance and contribution are also included. Though we have been using the tool for teaching purposes for arelatively short time, our experience is positive and we find the Polynomial Toolbox a very useful software tool for teachers.
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Fast Fourier Transform and robustness analysis with respect to parametric uncertainties
Hromčík, Martin ; Šebek, M.
In this paper two new numerical algorithms based on the Fast Fourier Transform techniques (FFT) are used to solve the structured robustness analysis problem in the case of one parameter entering polynomially. Both scalar and matrix cases are considered. The employed algorithms are namely numerical routines for the computation of one- and two-dimensional polynomial matrix determinants, based on the one- and two-dimensional FFT's respectively.
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