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Showing papers by "Chun-Hsiung Fang published in 1992"


Journal ArticleDOI
TL;DR: In this article, a simple approach to finding all polynomial matrix solutions of the Diophantine equation is proposed based on the state-space concepts, which is very simple in comparison to earlier ones.
Abstract: Based on the state-space concepts, a simple approach to finding all polynomial matrix solutions of the Diophantine equation is proposed. The procedure presented is very simple in comparison to earlier ones. Unlike earlier ones, it is not necessary to solve any equation. Only two constant matrices which could be selected at random are required. All solutions are expressed in an explicit formula form. >

17 citations


Journal ArticleDOI
TL;DR: Using the concepts of state feedback in generalized state- space, explicit formulas for calculating doubly coprime matrix fraction descriptions (MFDs) of the transfer matrix of a regular state-space system and the polynomial generalized Bezout identity elements corresponding to thoseCoprime MFDs are presented.
Abstract: Using the concepts of state feedback in generalized state-space, explicit formulas for calculating doubly coprime matrix fraction descriptions (MFDs) of the transfer matrix of a regular state-space system and the polynomial generalized Bezout identity elements corresponding to those coprime MFDs are presented. They can be easily calculated with the help of existing computational algorithms and software packages. >

9 citations



Proceedings ArticleDOI
10 May 1992
TL;DR: Using the generalized state-space concepts, a simple and iterative algorithm for finding the polynomial matrix solutions to the well known polynomially Bezout identity is developed in this article.
Abstract: Using the generalized state-space concepts, a simple and iterative algorithm for finding the polynomial matrix solutions to the well known polynomial Bezout identity is developed. The polynomial Bezout identity plays a central role in systems design and analysis while using polynomial fractional approaches. The initial values needed in this algorithm are only two constant matrices which can be selected at random. From the computational point of view, the method presented seems to be easier than the approaches in the literature. Illustrative examples are included. >