Title :
A fast neural-network algorithm for simultaneous extraction of all roots of algebraic polynomial
Author :
Zhu, Wei ; Zeng, Zhezhao ; Zhou, Youqing
Author_Institution :
Coll. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha
Abstract :
In this paper, we present a fast neural-network algorithm of multi-point iterative method for simultaneous determination of all roots of polynomial. Its convergence was researched. The computation is carried out by simple steepest descent rule with adaptive variable step-size. The specific examples illustrated that the proposed method can find simultaneously the roots of polynomials at a very rapid convergence and very high accuracy with less computation.
Keywords :
iterative methods; mathematics computing; neural nets; polynomials; adaptive variable step-size; multipoint iterative method; neural-network algorithm; simultaneous algebraic polynomial root extraction; steepest descent rule; Communication system control; Control systems; Convergence; Data mining; Educational institutions; Equations; Iterative algorithms; Iterative methods; Polynomials; Signal processing algorithms;
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
DOI :
10.1109/ICOSP.2008.4697750