Demonstrate the following propierties (State-space representation)












0












$begingroup$


Having this properties:



$E[x(j)w^T(k)]=0$; $j,kgeq 0, jleq k$.



$E[z(j)w^T(k)]=0$; $j,kgeq 0, jleq k$.



Demonstrate it with the following assumptions:





  • $x(k+1)=Phi (k+1,k)x(k)+Gamma (k+1,k)w(k)~$, $kgeq 0$; $x(0)=x_0~$
    (is State equation)


  • $z(k)=H(k)x(k)+v(k), kgeq0$ (observation equation)

  • Initial state $x_0$, vector n-dimensional gaussian with cov. matrix
    $E[x_0x^T_o]=P_0$


  • The process ${w(k);kgeq 0}$ is a white noise succession, centred,
    with cov. matrix $E[w(k)w^T(k)]=Q(k), kgeq0$




    • The process ${v(k);kgeq 0}$ is a white noise succession, centred,
      with cov. matrix $E[v(k)v^T(k)]=R(k), kgeq0$



  • The initial state and additive noises are mutually independent.



I think it has to be done with Doob theorem but in my case is not working. Thanks in advance,










share|cite|improve this question











$endgroup$

















    0












    $begingroup$


    Having this properties:



    $E[x(j)w^T(k)]=0$; $j,kgeq 0, jleq k$.



    $E[z(j)w^T(k)]=0$; $j,kgeq 0, jleq k$.



    Demonstrate it with the following assumptions:





    • $x(k+1)=Phi (k+1,k)x(k)+Gamma (k+1,k)w(k)~$, $kgeq 0$; $x(0)=x_0~$
      (is State equation)


    • $z(k)=H(k)x(k)+v(k), kgeq0$ (observation equation)

    • Initial state $x_0$, vector n-dimensional gaussian with cov. matrix
      $E[x_0x^T_o]=P_0$


    • The process ${w(k);kgeq 0}$ is a white noise succession, centred,
      with cov. matrix $E[w(k)w^T(k)]=Q(k), kgeq0$




      • The process ${v(k);kgeq 0}$ is a white noise succession, centred,
        with cov. matrix $E[v(k)v^T(k)]=R(k), kgeq0$



    • The initial state and additive noises are mutually independent.



    I think it has to be done with Doob theorem but in my case is not working. Thanks in advance,










    share|cite|improve this question











    $endgroup$















      0












      0








      0





      $begingroup$


      Having this properties:



      $E[x(j)w^T(k)]=0$; $j,kgeq 0, jleq k$.



      $E[z(j)w^T(k)]=0$; $j,kgeq 0, jleq k$.



      Demonstrate it with the following assumptions:





      • $x(k+1)=Phi (k+1,k)x(k)+Gamma (k+1,k)w(k)~$, $kgeq 0$; $x(0)=x_0~$
        (is State equation)


      • $z(k)=H(k)x(k)+v(k), kgeq0$ (observation equation)

      • Initial state $x_0$, vector n-dimensional gaussian with cov. matrix
        $E[x_0x^T_o]=P_0$


      • The process ${w(k);kgeq 0}$ is a white noise succession, centred,
        with cov. matrix $E[w(k)w^T(k)]=Q(k), kgeq0$




        • The process ${v(k);kgeq 0}$ is a white noise succession, centred,
          with cov. matrix $E[v(k)v^T(k)]=R(k), kgeq0$



      • The initial state and additive noises are mutually independent.



      I think it has to be done with Doob theorem but in my case is not working. Thanks in advance,










      share|cite|improve this question











      $endgroup$




      Having this properties:



      $E[x(j)w^T(k)]=0$; $j,kgeq 0, jleq k$.



      $E[z(j)w^T(k)]=0$; $j,kgeq 0, jleq k$.



      Demonstrate it with the following assumptions:





      • $x(k+1)=Phi (k+1,k)x(k)+Gamma (k+1,k)w(k)~$, $kgeq 0$; $x(0)=x_0~$
        (is State equation)


      • $z(k)=H(k)x(k)+v(k), kgeq0$ (observation equation)

      • Initial state $x_0$, vector n-dimensional gaussian with cov. matrix
        $E[x_0x^T_o]=P_0$


      • The process ${w(k);kgeq 0}$ is a white noise succession, centred,
        with cov. matrix $E[w(k)w^T(k)]=Q(k), kgeq0$




        • The process ${v(k);kgeq 0}$ is a white noise succession, centred,
          with cov. matrix $E[v(k)v^T(k)]=R(k), kgeq0$



      • The initial state and additive noises are mutually independent.



      I think it has to be done with Doob theorem but in my case is not working. Thanks in advance,







      ordinary-differential-equations stochastic-processes






      share|cite|improve this question















      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited Dec 20 '18 at 17:55







      fonaritm

















      asked Dec 20 '18 at 13:47









      fonaritmfonaritm

      33




      33






















          1 Answer
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          0












          $begingroup$

          $x_j$ is a linear combination of $x_0$ and $w_0,...,w_{j-1}$.



          Per last assumptions, these are all independent of of the vectors $w_k$, $kge j$.



          Therefore, the claim.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            I add some more information, just to know if it is right. I need some help about this, I'm quite new in stochastic systems.
            $endgroup$
            – fonaritm
            Dec 20 '18 at 15:45












          • $begingroup$
            What is $v_k$? The same applies, also $z_j$ is composed of data from times $<j$ that are independent of $w_k$, $k>j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 16:07










          • $begingroup$
            Thanks @LutzL I have corrected this in the question area
            $endgroup$
            – fonaritm
            Dec 20 '18 at 17:55










          • $begingroup$
            Then $z_j$ is obviously correlated to $v_j$, but still not to $w_k$, $kge j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 18:02










          • $begingroup$
            You're right, thank you
            $endgroup$
            – fonaritm
            Dec 20 '18 at 22:13












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          1 Answer
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          active

          oldest

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          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          0












          $begingroup$

          $x_j$ is a linear combination of $x_0$ and $w_0,...,w_{j-1}$.



          Per last assumptions, these are all independent of of the vectors $w_k$, $kge j$.



          Therefore, the claim.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            I add some more information, just to know if it is right. I need some help about this, I'm quite new in stochastic systems.
            $endgroup$
            – fonaritm
            Dec 20 '18 at 15:45












          • $begingroup$
            What is $v_k$? The same applies, also $z_j$ is composed of data from times $<j$ that are independent of $w_k$, $k>j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 16:07










          • $begingroup$
            Thanks @LutzL I have corrected this in the question area
            $endgroup$
            – fonaritm
            Dec 20 '18 at 17:55










          • $begingroup$
            Then $z_j$ is obviously correlated to $v_j$, but still not to $w_k$, $kge j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 18:02










          • $begingroup$
            You're right, thank you
            $endgroup$
            – fonaritm
            Dec 20 '18 at 22:13
















          0












          $begingroup$

          $x_j$ is a linear combination of $x_0$ and $w_0,...,w_{j-1}$.



          Per last assumptions, these are all independent of of the vectors $w_k$, $kge j$.



          Therefore, the claim.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            I add some more information, just to know if it is right. I need some help about this, I'm quite new in stochastic systems.
            $endgroup$
            – fonaritm
            Dec 20 '18 at 15:45












          • $begingroup$
            What is $v_k$? The same applies, also $z_j$ is composed of data from times $<j$ that are independent of $w_k$, $k>j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 16:07










          • $begingroup$
            Thanks @LutzL I have corrected this in the question area
            $endgroup$
            – fonaritm
            Dec 20 '18 at 17:55










          • $begingroup$
            Then $z_j$ is obviously correlated to $v_j$, but still not to $w_k$, $kge j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 18:02










          • $begingroup$
            You're right, thank you
            $endgroup$
            – fonaritm
            Dec 20 '18 at 22:13














          0












          0








          0





          $begingroup$

          $x_j$ is a linear combination of $x_0$ and $w_0,...,w_{j-1}$.



          Per last assumptions, these are all independent of of the vectors $w_k$, $kge j$.



          Therefore, the claim.






          share|cite|improve this answer









          $endgroup$



          $x_j$ is a linear combination of $x_0$ and $w_0,...,w_{j-1}$.



          Per last assumptions, these are all independent of of the vectors $w_k$, $kge j$.



          Therefore, the claim.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Dec 20 '18 at 15:23









          LutzLLutzL

          60.3k42057




          60.3k42057












          • $begingroup$
            I add some more information, just to know if it is right. I need some help about this, I'm quite new in stochastic systems.
            $endgroup$
            – fonaritm
            Dec 20 '18 at 15:45












          • $begingroup$
            What is $v_k$? The same applies, also $z_j$ is composed of data from times $<j$ that are independent of $w_k$, $k>j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 16:07










          • $begingroup$
            Thanks @LutzL I have corrected this in the question area
            $endgroup$
            – fonaritm
            Dec 20 '18 at 17:55










          • $begingroup$
            Then $z_j$ is obviously correlated to $v_j$, but still not to $w_k$, $kge j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 18:02










          • $begingroup$
            You're right, thank you
            $endgroup$
            – fonaritm
            Dec 20 '18 at 22:13


















          • $begingroup$
            I add some more information, just to know if it is right. I need some help about this, I'm quite new in stochastic systems.
            $endgroup$
            – fonaritm
            Dec 20 '18 at 15:45












          • $begingroup$
            What is $v_k$? The same applies, also $z_j$ is composed of data from times $<j$ that are independent of $w_k$, $k>j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 16:07










          • $begingroup$
            Thanks @LutzL I have corrected this in the question area
            $endgroup$
            – fonaritm
            Dec 20 '18 at 17:55










          • $begingroup$
            Then $z_j$ is obviously correlated to $v_j$, but still not to $w_k$, $kge j$.
            $endgroup$
            – LutzL
            Dec 20 '18 at 18:02










          • $begingroup$
            You're right, thank you
            $endgroup$
            – fonaritm
            Dec 20 '18 at 22:13
















          $begingroup$
          I add some more information, just to know if it is right. I need some help about this, I'm quite new in stochastic systems.
          $endgroup$
          – fonaritm
          Dec 20 '18 at 15:45






          $begingroup$
          I add some more information, just to know if it is right. I need some help about this, I'm quite new in stochastic systems.
          $endgroup$
          – fonaritm
          Dec 20 '18 at 15:45














          $begingroup$
          What is $v_k$? The same applies, also $z_j$ is composed of data from times $<j$ that are independent of $w_k$, $k>j$.
          $endgroup$
          – LutzL
          Dec 20 '18 at 16:07




          $begingroup$
          What is $v_k$? The same applies, also $z_j$ is composed of data from times $<j$ that are independent of $w_k$, $k>j$.
          $endgroup$
          – LutzL
          Dec 20 '18 at 16:07












          $begingroup$
          Thanks @LutzL I have corrected this in the question area
          $endgroup$
          – fonaritm
          Dec 20 '18 at 17:55




          $begingroup$
          Thanks @LutzL I have corrected this in the question area
          $endgroup$
          – fonaritm
          Dec 20 '18 at 17:55












          $begingroup$
          Then $z_j$ is obviously correlated to $v_j$, but still not to $w_k$, $kge j$.
          $endgroup$
          – LutzL
          Dec 20 '18 at 18:02




          $begingroup$
          Then $z_j$ is obviously correlated to $v_j$, but still not to $w_k$, $kge j$.
          $endgroup$
          – LutzL
          Dec 20 '18 at 18:02












          $begingroup$
          You're right, thank you
          $endgroup$
          – fonaritm
          Dec 20 '18 at 22:13




          $begingroup$
          You're right, thank you
          $endgroup$
          – fonaritm
          Dec 20 '18 at 22:13


















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