transformation - %beta x2=[min(x):.1:max(x)];...

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
function transformation(x,y) %Problem 13.7 %To linearize, divide by x and take the natural logarithm. To solve the %overdetermined linear system for the unknown coefficients, use the Matlab %backslash (\) operator % %Convert the equation y=a1*xe^(a2*x) to form of Ax=b %Where A=coefficent matrix and b consist of a know matrix of values ln(y/x) b=log(y./x); xx=numel(x); c=ones(xx,1); A=[c x]; answ=A\b; a1=exp(answ(1,1)); %alpha a2=answ(2,1);
Background image of page 1
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: %beta x2=[min(x):.1:max(x)]; yy=a1.*x2.*exp(a2*x2); plot(x,y,'o',x2,yy); title('Plot of origional data with nonlinear model fit:'); legend('exp data','fit'); xlabel('x'); ylabel('y'); pause x3=linspace(min(x),max(x),2); y3=a2*x3+log(a1); plot(x,b,'o',x3,y3); title('Plot of linearized data with linear regression fit:'); xlabel('x'); ylabel('log(y/x)'); fprintf('a1=%7.6f, a2=%5.4f\n\n',a1,a2);...
View Full Document

This note was uploaded on 09/27/2011 for the course EGM 3344 taught by Professor Raphaelhaftka during the Spring '09 term at University of Florida.

Ask a homework question - tutors are online