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How to solve a matrix using Cholesky Decompositon on Matlab


Implement a program in Matlab for LU decomposition with pivotingSignificant improvement when I use lsqnonlin function with wrong sized XHow to solve linear equation using Matlab?How to solve over-determined linear system of equations?LU Decomposition vs. QR Decomposition for similar problemsusing MATLAB to solve a linear programHow to solve Newton's method in matlab?Solve intregal equation using MATLABIdentify a state space model from measured inputs and outputsUsing MATLAB to solve Poisson matrix equation













0












$begingroup$


I'm trying to solve a system of linear equations on MATLAB, I have written a code that solves the problem using Gaussian Elimination. But I was wondering how I could modify this to use other methods of matrix decomposition, such as Cholesky Decomposition?



%set up matrices
A=[-900 400 0 0 0; 500 -900 400 0 0; 0 500 -900 400 0; 0 0 500 -900 400; 0 0 0 400 -900];
b=[0;0;0;0;0];

%decompose A matrix
[L, U] = lu(A);

%set up series of yin's for plot
yin=0:0.01:0.25;
yout=zeros(length(yin),1);
xout=zeros(length(yin),1);

%create b based on yin, and solve
for i=1:1:length(yin)
b(1)=-500*yin(i);
d = Lb;
y = Ud;
%save yout and xout values before next iteration
yout(i)=y(5);
xout(i)=y(1)*4;
end









share|cite|improve this question









$endgroup$
















    0












    $begingroup$


    I'm trying to solve a system of linear equations on MATLAB, I have written a code that solves the problem using Gaussian Elimination. But I was wondering how I could modify this to use other methods of matrix decomposition, such as Cholesky Decomposition?



    %set up matrices
    A=[-900 400 0 0 0; 500 -900 400 0 0; 0 500 -900 400 0; 0 0 500 -900 400; 0 0 0 400 -900];
    b=[0;0;0;0;0];

    %decompose A matrix
    [L, U] = lu(A);

    %set up series of yin's for plot
    yin=0:0.01:0.25;
    yout=zeros(length(yin),1);
    xout=zeros(length(yin),1);

    %create b based on yin, and solve
    for i=1:1:length(yin)
    b(1)=-500*yin(i);
    d = Lb;
    y = Ud;
    %save yout and xout values before next iteration
    yout(i)=y(5);
    xout(i)=y(1)*4;
    end









    share|cite|improve this question









    $endgroup$














      0












      0








      0





      $begingroup$


      I'm trying to solve a system of linear equations on MATLAB, I have written a code that solves the problem using Gaussian Elimination. But I was wondering how I could modify this to use other methods of matrix decomposition, such as Cholesky Decomposition?



      %set up matrices
      A=[-900 400 0 0 0; 500 -900 400 0 0; 0 500 -900 400 0; 0 0 500 -900 400; 0 0 0 400 -900];
      b=[0;0;0;0;0];

      %decompose A matrix
      [L, U] = lu(A);

      %set up series of yin's for plot
      yin=0:0.01:0.25;
      yout=zeros(length(yin),1);
      xout=zeros(length(yin),1);

      %create b based on yin, and solve
      for i=1:1:length(yin)
      b(1)=-500*yin(i);
      d = Lb;
      y = Ud;
      %save yout and xout values before next iteration
      yout(i)=y(5);
      xout(i)=y(1)*4;
      end









      share|cite|improve this question









      $endgroup$




      I'm trying to solve a system of linear equations on MATLAB, I have written a code that solves the problem using Gaussian Elimination. But I was wondering how I could modify this to use other methods of matrix decomposition, such as Cholesky Decomposition?



      %set up matrices
      A=[-900 400 0 0 0; 500 -900 400 0 0; 0 500 -900 400 0; 0 0 500 -900 400; 0 0 0 400 -900];
      b=[0;0;0;0;0];

      %decompose A matrix
      [L, U] = lu(A);

      %set up series of yin's for plot
      yin=0:0.01:0.25;
      yout=zeros(length(yin),1);
      xout=zeros(length(yin),1);

      %create b based on yin, and solve
      for i=1:1:length(yin)
      b(1)=-500*yin(i);
      d = Lb;
      y = Ud;
      %save yout and xout values before next iteration
      yout(i)=y(5);
      xout(i)=y(1)*4;
      end






      matlab






      share|cite|improve this question













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      share|cite|improve this question










      asked Mar 16 at 22:48









      eenzeenz

      11




      11




















          1 Answer
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          0












          $begingroup$

          Given a self-adjoint positive-definite square matrix $A$, $operatornamechol(A)$ returns an upper triangular matrix $U$ such that $A = U^* U$



          To turn this into code, replace



          [L, U] = lu(A);


          by



          U = chol(A);
          L = U';





          share|cite|improve this answer









          $endgroup$












            Your Answer





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            oldest

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            0












            $begingroup$

            Given a self-adjoint positive-definite square matrix $A$, $operatornamechol(A)$ returns an upper triangular matrix $U$ such that $A = U^* U$



            To turn this into code, replace



            [L, U] = lu(A);


            by



            U = chol(A);
            L = U';





            share|cite|improve this answer









            $endgroup$

















              0












              $begingroup$

              Given a self-adjoint positive-definite square matrix $A$, $operatornamechol(A)$ returns an upper triangular matrix $U$ such that $A = U^* U$



              To turn this into code, replace



              [L, U] = lu(A);


              by



              U = chol(A);
              L = U';





              share|cite|improve this answer









              $endgroup$















                0












                0








                0





                $begingroup$

                Given a self-adjoint positive-definite square matrix $A$, $operatornamechol(A)$ returns an upper triangular matrix $U$ such that $A = U^* U$



                To turn this into code, replace



                [L, U] = lu(A);


                by



                U = chol(A);
                L = U';





                share|cite|improve this answer









                $endgroup$



                Given a self-adjoint positive-definite square matrix $A$, $operatornamechol(A)$ returns an upper triangular matrix $U$ such that $A = U^* U$



                To turn this into code, replace



                [L, U] = lu(A);


                by



                U = chol(A);
                L = U';






                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered yesterday









                Alex VongAlex Vong

                1,309819




                1,309819



























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