matlab代写代考

xdata=[0.075 0.5 1.0 1.2 1.7 2.0 2.3] ydata=[600 800 1200 1400 2050 2650 3750] N=length(xdata); A=[N sum(xdata) sum(xdata.^2) ; sum(xdata) sum(xdata.^2) sum(xdata.^3); sum(xdata.^2) sum(xdata.^3) sum(xdata.^4)]; C=[sum(ydata); sum(xdata.*ydata); sum(xdata.^2.*ydata)]; % %Note that for brevity I have used the MATLAB linsolve() function %solve the resulting equation. You can use any of the %solvers from previous lectures. % […]

Delta=1 x=linspace(2,10,9) y=1./x; I=SimpsonByOoi(y,Delta) %Check with MATLAB Imatlab=Delta*trapz(y) function I=SimpsonByOoi(y,dx) n=length(y); I=(dx/3)*(y(1)+4*sum(y(2:2:end))+2*sum(y(3:2:end-1))+y(n)); end

[Content_Types].xml _rels/.rels matlab/document.xml matlab/output.xml metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml Least Squares Regression In this livescript, you will learn how To apply least squares regression Given a set of data points, we may approximate the relationship by assuming a functional relationship y_{i}=f(x_{i};\textbf{a}) , where \textbf{a} the parameters defining the problem. For a linear relationship y=a_{0}+a_{1}x a_{0} and

[Content_Types].xml _rels/.rels matlab/document.xml matlab/output.xml metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml Bracketing Methods: Bisection Method In this livescript, you will learn how to Write a MATLAB program that implements the Bisection method to solve an algebraic nonlinear equation We’ll be considering the problem f(x)=x^{3}-x=0 Equation 1. It is always a good idea to plot f(x) to see what

%MATLAB script to illustrate Richardson’s extrapolation for derivative %% MyFunc=@(x) x.^2.*cos(x) MyDeriv=@(x)x.*(2.*cos(x)-x.*sin(x)) %% Dexact=MyDeriv(2) %% xi=2; Delta1=0.2; xim2=xi-2*Delta1; xim1=xi-Delta1; xip1=xi+Delta1; xip2=xi+2*Delta1; D1=(1./(12*Delta1))*(MyFunc(xim2)-8*MyFunc(xim1)+8*MyFunc(xip1)-MyFunc(xip2)) %% Delta2=0.1; xim2=xi-2*Delta2; xim1=xi-Delta2; xip1=xi+Delta2; xip2=xi+2*Delta2; D2=(1./(12*Delta2))*(MyFunc(xim2)-8*MyFunc(xim1)+8*MyFunc(xip1)-MyFunc(xip2)) %% D=D2*(1+1/((Delta1/Delta2)^4-1))-D1*(1/((Delta1/Delta2)^4-1))

[Content_Types].xml _rels/.rels matlab/_rels/document.xml.rels matlab/document.xml matlab/output.xml media/image1.png metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml Systems of Differential Equations In this livescript, you will learn how To reduce higher order differential equations to systems of first order differential equations To solve the resulting set of equations numerically and using MATLAB. Consider the motion of a spring-mass system Applying Newton’s second