matlab代写代考

CS计算机代考程序代写 matlab cuda Agda [Content_Types].xml

[Content_Types].xml _rels/.rels matlab/document.xml matlab/output.xml metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml Perform 1d differentiation using differentiation matrix approach. fx=@(x) x.^7 d2fanalytical=@(x)42*x.^5 nx=20; %number of grid points. It is Nx+1 if you follow the notation in the question Lx=2.0; xi=linspace(-1,1,nx)’ Dx=zeros(nx,nx); Deltax=Lx/(nx-1); %Double Derivative matrix for internal nodes D2x=diag(-2*ones(1,nx))+diag(ones(1,nx-1),1)+diag(ones(1,nx-1),-1); %Have to treat boundaries differently D2x(1,1)=1.0;D2x(1,2)=-2;D2x(1,3)=1; D2x(nx,nx)=1.0;D2x(nx,nx-1)=-2;D2x(nx,nx-2)=1; D2x=D2x/Deltax^2; d2fx=D2x*fx(xi) plot(xi,d2fx, […]

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CS计算机代考程序代写 matlab Numerical Methods in Engineering (ENGR20005)

Numerical Methods in Engineering (ENGR20005) Lecture 22 Dr. Leon Chan lzhchan@unimelb.edu.au Department of Mechanical Engineering The University of Melbourne Slides prepared by Prof.Andrew Ooi L22.1: Implicit Euler’s method for a system of linear equations Implicit Euler’s method for a system of equations So far, we have learnt to solve single ODE using implicit Euler method.

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CS计算机代考程序代写 matlab clear all;

clear all; close all; Delta_t=0.05; t=0:Delta_t:50; xRK2=zeros(length(t),3); xEuler=zeros(length(t),3); xRK2(1,:)=[0.0 1.0 1.0]; xEuler(1,:)=[0.0 1.0 1.0]; for n=1:length(t)-1 k1=f(t(n),xRK2(n,:))’; k2=f(t(n)+Delta_t,xRK2(n,:)+Delta_t*k1)’; xRK2(n+1,:)=xRK2(n,:)+Delta_t*(k1/2.0+k2/2.0); xEuler(n+1,:)=xEuler(n,:)+Delta_t*f(t(n),xEuler(n,:))’; end [tmat,xmat]=ode23(@f,[0 50],[0 1 1]); hold off plot(t,xEuler(:,2),’b-‘,’linewidth’,2,’markersize’,10) hold on plot(t,xRK2(:,2),’r-‘,’linewidth’,2,’markersize’,10) plot(tmat,xmat(:,2),’k-‘,’linewidth’,2) xlabel(‘t’);ylabel(‘x_1(t)’); legend(‘Explicit Euler’,’RK-2′,’MATLAB ode23()’) function dxdt=f(t,x) dxdt=[x(2)*x(3); -x(1)*x(3) ;-0.5*x(1)*x(2)]; end

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CS计算机代考程序代写 matlab [Content_Types].xml

[Content_Types].xml _rels/.rels matlab/document.xml matlab/output.xml metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml Iterative Methods: Jacobi Method In this livescript, you will learn how To use the Jacobi method to solve systems of linear equations As with fixed point iteration, our aim is to cast the system [A]\{x\}=\{c\} Equation 1. into the form \{x\}=g(\{x\}) To do this we consider the

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CS计算机代考程序代写 matlab [Content_Types].xml

[Content_Types].xml _rels/.rels mathml/eqn1.mml matlab/_rels/document.xml.rels matlab/document.xml matlab/output.xml metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml f(x)=cos(x)  Plotting Taylor Series This livescript shows you how you can use MATLAB to plot a Taylor series of . xe^x A Taylor series of any function can be written concisely as f(x)=\sum_{k=0}^{\infty}\frac{f^{(k)}(x_0)}{k!}(x-x_0)^k It is sometimes useful to expand this summation to clearly see all

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CS计算机代考程序代写 scheme matlab Numerical Methods in Engineering (ENGR20005)

Numerical Methods in Engineering (ENGR20005) Lecture 21 Dr. Leon Chan lzhchan@unimelb.edu.au Department of Mechanical Engineering The University of Melbourne Slides prepared by Prof.Andrew Ooi L21.1: Solving ODEs with MATLAB inbuilt functions • There are many inbuilt MATLAB functions to solve ODEs: Initial Value Problems. Some of them are ode45() ode23() ode23s() ode34s() ode15s() ’s’ is

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CS计算机代考程序代写 matlab AI Numerical Methods in Engineering (ENGR20005)

Numerical Methods in Engineering (ENGR20005) Lecture 09 Dr. Leon Chan lzhchan@unimelb.edu.au Department of Mechanical Engineering The University of Melbourne Slides prepared by Prof.Andrew Ooi L9.1: Interpolation 2 “Book” (Chap. 5) Interpolation – Motivation Continuous Function f : x ↦ sin(x) Function at discrete points y f(y) 1 0.5 4 1.5 7 4.5 Figure 1: Continuous

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CS计算机代考程序代写 matlab Java flex DHCP algorithm Agda [Content_Types].xml

[Content_Types].xml _rels/.rels matlab/document.xml matlab/output.xml metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml Open Methods: Fixed Point Iteration In this livescript, you will learn how The fixed point iteration method finds a root To write a piece of code that implements the method We’ll be considering the problem f(x)=ax^{2}+(1-a)x=0 Equation 1. (a) Determine the roots of Eq. (1) analytically. The

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CS计算机代考程序代写 matlab clear all

clear all %asks MATLAB to print out more decimal places. format long e % % It is important to have a good guess!! % xmatlab1 = fsolve(@TwoPointGaussLegendreQuadrature,[1;1;-1;1]); options = optimoptions(@fsolve,’Display’,’iter’,’SpecifyObjectiveGradient’,true); [xmatlab2,F,exitflag,output,JAC] = fsolve(@TwoPointGaussLegendreQuadratureWithJacobian,[1;1;-1;1],options); function [f,J] = TwoPointGaussLegendreQuadratureWithJacobian(x) f(1) = x(1)+x(2)-2; f(2) = x(1)*x(3)+x(2)*x(4); f(3)=x(1)*x(3).^2+x(2)*x(4).^2-(2./3.); f(4)=x(1)*x(3).^3+x(2)*x(4).^3; J(1,1)=1;J(1,2)=1;J(1,3)=0;J(1,4)=0; J(2,1)=x(3);J(2,2)=x(4);J(2,3)=x(1);J(2,4)=x(2); J(3,1)=x(3).^2;J(3,2)=x(4).^2;J(3,3)=2*x(1)*x(3);J(3,4)=2*x(2)*x(4); J(4,1)=x(3).^3;J(4,2)=x(4).^3;J(4,3)=3*x(1)*x(3).^2;J(4,4)=3*x(2)*x(4).^2; end function f = TwoPointGaussLegendreQuadrature(x) f(1)

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CS计算机代考程序代写 scheme matlab [Content_Types].xml

[Content_Types].xml _rels/.rels matlab/document.xml matlab/output.xml metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml Types of Boundary Conditions for Finite Difference Methods In this livescript, you will learn how To implement varying types of boundary conditions. Boundary value problems are differential equations of the form \frac{d^{2}y}{dx^{2}}+p(x)\frac{dy}{dx}+q(x)y=r(x) coupled with some constraints at the boundary, called boundary conditions, which can be specified as

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