%Clear memory, console and close open plots
clear; clc; close all;
%% Q1(a)
fprintf('\n==============================Q1(a)===================================\n');
global x y%make input data global
f=@(x) (exp(-x).*(x.^2)).*log(x+0.1)+sin(sqrt(x))+1;%Define input function
x=0:0.5:9; y=f(x);%Compute I/P function
str='Input function plot';
figure('Name',str,'NumberTitle','off');
plot(x,y,'LineWidth',2,'Color',[1 0 0]);%Plot input function
title(str); xlabel('X'); ylabel('f(X)');
fprintf('\nPlot of input function successfully generated.\n');
%% Q1(b)
fprintf('\n==============================Q1(b)===================================\n');
%Weight function definition
global w1 w2
w1=@(x) ones(size(x));%Define Weight function w1
w2=@(x) (1./x).^2;%Define Weight function w2
C0=[1 1 1 1 1];
[C1,err1] = fminunc(@(X) quadpolerr(X,1),C0);%Compute least square minimization for w1
[C2,err2] = fminunc(@(X) quadpolerr(X,2),C0);%Compute least square minimization for w2
fprintf('\n The table of values of funnction for different x are as follows.\n');
[x' y']%print tabular values of input function
%Display computed fit equation
fprintf('\nThe fit equation for unit weight is as follows and the error in this case is %6.4f.\n',err1);
fprintf('y=%6.4f + %6.4fx + %6.4fx^2 + %6.4fx^3 + %6.4fx^4\n\n',C1(1),C1(2),C1(3),C1(4),C1(5));
fprintf('\nThe fit equation for inverse square weight is as follows and the error in this case is %6.4f.\n',err2);

Write a Matlab program that creates 10,000 random Xs and Ys where:...