shikakunara / shippuden

ESO208A

MATLAB ASSIGNMENT

REGRESSION MODEL

This program aims to use polynomial regression models from degree one to four to explain the given data set and compare them. The input are the X and Y coordinates of the data set or namely the observations. The output contains the coeffecients of all the four regression polynomials, their regression coeffecients and a figure containing a scatter plot of the given data set along with the graphs of all four polynomials, to compare the four methods graphically.

Bairstow Method Implementation

This Program aims at using Bairstow method to compute the roots of a given nth degree polynomial in single variable x. The input contains the polynomial's degree and the corresponding coeffecients. The output contains all the roots (real and complex) and a graph of the given polynomial.

Gauss-Seidel Method Implementation

The program implements gauss-seidel method with relaxation to solve linear euations in n variables. The coeffecients are taken as input as an nXn matrix along with the constants, and a system of n equation of the form a1x1 + a2x2 + a3x3 ..... anxn + c=0 and approximates the values to a certain accepted value of error taken as input.

Integration of a particular 2nd order differential Equation via Implementing Euler's Method - Heun's Method - 4th Order Runge-Kutta Method.

The program implements Euler's method , Heun's Method and Fourth Order Runge-Kutta method to solve a predefined 2nd order Differential Equation by decomposing the equation into a system of two 1st order Differential equations.