# Approximate polynomial GCD

- Programs and Algorithms of Numerical Mathematics, Publisher: Institute of Mathematics AS CR(Prague), page 63-68

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topEliaš, Ján, and Zítko, Jan. "Approximate polynomial GCD." Programs and Algorithms of Numerical Mathematics. Prague: Institute of Mathematics AS CR, 2013. 63-68. <http://eudml.org/doc/271395>.

@inProceedings{Eliaš2013,

abstract = {The computation of polynomial greatest common divisor (GCD) ranks among basic algebraic problems with many applications, for example, in image processing and control theory. The problem of the GCD computing of two exact polynomials is well defined and can be solved symbolically, for example, by the oldest and commonly used Euclid’s algorithm. However, this is an ill-posed problem, particularly when some unknown noise is applied to the polynomial coefficients. Hence, new methods for the GCD computation have been extensively studied in recent years. The aim is to overcome the ill-posed sensitivity of the GCD computation in the presence of noise. We show that this can be successively done through a TLS formulation of the solved problem, [1,5,7].},

author = {Eliaš, Ján, Zítko, Jan},

booktitle = {Programs and Algorithms of Numerical Mathematics},

keywords = {polynomial greatest common divisor; approximate greatest common divisor; Sylvester subresultant matrix; singular value; total least squares problem},

location = {Prague},

pages = {63-68},

publisher = {Institute of Mathematics AS CR},

title = {Approximate polynomial GCD},

url = {http://eudml.org/doc/271395},

year = {2013},

}

TY - CLSWK

AU - Eliaš, Ján

AU - Zítko, Jan

TI - Approximate polynomial GCD

T2 - Programs and Algorithms of Numerical Mathematics

PY - 2013

CY - Prague

PB - Institute of Mathematics AS CR

SP - 63

EP - 68

AB - The computation of polynomial greatest common divisor (GCD) ranks among basic algebraic problems with many applications, for example, in image processing and control theory. The problem of the GCD computing of two exact polynomials is well defined and can be solved symbolically, for example, by the oldest and commonly used Euclid’s algorithm. However, this is an ill-posed problem, particularly when some unknown noise is applied to the polynomial coefficients. Hence, new methods for the GCD computation have been extensively studied in recent years. The aim is to overcome the ill-posed sensitivity of the GCD computation in the presence of noise. We show that this can be successively done through a TLS formulation of the solved problem, [1,5,7].

KW - polynomial greatest common divisor; approximate greatest common divisor; Sylvester subresultant matrix; singular value; total least squares problem

UR - http://eudml.org/doc/271395

ER -

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