transformation

transformation - ¾ta x2=[min(x.1:max(x yy=a1*x2*exp(a2*x2...

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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);
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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);...
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