MATLAB/ Simulink demos




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100_working code for conjugate gradient iterative algo for finding solution of Ax=b

%%100_working code for conjugate gradient iterative algo for finding %%solution of Ax=b, where A is symmetric Positive definite %%written by vikram bhayyA on 18-6-26 ~13:19-13:59 %%general clc clear all A=input( 'enter a Symmetric Positive Definite matrix:' ); %A=[4,1,1;1,3,-1;1,-1,3]; %has to be symmetric Positve definite [m,n]=size(A); n b=input( 'enter the output vector of size n,1:' ); %b=[6,3 3]'; %x0=zeros(n,1); x0=[1 -1 0]'; %x0=[0 0 0]' ; % initial guess %initialize r0=b-A*x0; %residual if norm(r0)<0.1 display( 'solution of Ax=b is:' ) x0 ...
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100% working code for Steepest Descent iterative algo for finding solution of Ax=b

%%100_working code for Steepest Descent iterative algo for finding %%solution of Ax=b, where A is symmetric Positive definite %%written by vikram bhayyA on 18-6-26 ~14:37-14:42 %%general. clc clear all A=input( 'enter a Symmetric Positive Definite matrix:' ); %A=[4,1,1;1,3,-1;1,-1,3]; %has to be symmetric Positve definite [m,n]=size(A); n b=input( 'enter the output vector of size n,1:' ); %b=[6,3 3]'; %x0=zeros(n,1); x0=[1 -1 0]'; %x0=[0 0 0]' ; % initial guess %initialize r0=b-A*x0; %residual if norm(r0)<0.01 display( 'solution of Ax=b is' ) x0 else %p0=r0; %search direction k=1; while (k) alpha0=(r0'*r0)/(r0'*A*r0); %step size x1=x0+alpha0*r0; %update x1 r1=b-(A*x1)...
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