Micromodels For Numerical Analysis Topics Via Simi-Neural Net Between Matlab & MuPad

Abstract

The aim of this paper is to create micro models for specific topics in numerical analysis, when by certain types of combined non-linear equations including trigonometric and/or exponential functions look likes impassive against elaboration while to portrait or determine their roots, also it will offer somewhat modified approach for treatment of these as well as other cases via semi-neural net between MAT LAB & MUPAD, Moreover it includes certain comparison between the proposed approach and the classical ones, those separately depends on Newton-Raphson, False position, Secant, Muller or others methods, While  these methods already embedded & act individually, dually, or triply through by  built-in Mat lab &Mupad Functions designed to seeking for polynomials or other roots, also there is mutual verification between FTA theorem & the micro models results, except that the author tried to produce elegant & unique of its kind image cal models  through by Mat lab integrating within Mupad to enhance his thesis.

Keywords: infinite roots, dancing roots, complex roots, real roots, polynomial's roots, algebraic

roots, combined equationroots,Newton-Raphson,Falsi-Regula,Secant,Bisection,Muller

classical approximation, Mat lab & Mupad approximation, FTA Theorem.