Matrix to the power t.

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Compute the matrix $A^t$ for the following cases:



$A_1=beginbmatrix0&0\0&1endbmatrix, quad A_2=beginbmatrix-1&0\0&-2 endbmatrix, quad A_3=beginbmatrix0&1\0&0endbmatrix, quad A_4=beginbmatrix0&1&0\0&0&1\0&0&0endbmatrix, quad A_5=beginbmatrix1&1\1&1endbmatrix$



And the answers should be:



$ quad A^t_1=beginbmatrix0^t&0\0&1^t endbmatrix, quad A^t_2=beginbmatrix(-1)^t&0\0&(-2)^t endbmatrix, quad A^t_3=beginbmatrixdelta(t)&delta(t-1)\0&delta(t) endbmatrix,quad A^t_4=beginbmatrixdelta(t)&delta(t-1)&delta(t-2)\0&delta(t)&delta(t-1)\0&0&delta(t)endbmatrix,quad A^t_5=frac12beginbmatrix0^t+2^t&-0^t+2^t\-0^t+2^t&0^t+2^t endbmatrix$



where
$ delta(j)=0^j=left{
beginarrayll
1 textfor j = 0\
0 textfor j neq 0\
endarray
right.
$



How is this done? What kind of sorcery is this?



I've checked on the net but all I could find were tricky mathematical definitions, while I'm looking for a simple "how to".



Help me Stackexchange, you are my only hope.










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  • 2




    It's a capital $^T$ for transposition. OP: have you tried just writing down a few terms in the sequence? e.g. $A_1^2, A_1^3$ and seeing what you get?
    – MRobinson
    Sep 3 at 11:52







  • 1




    No it's not the transpose. The answers are shown below. It has to do with the response to discrete time autonomous linear systems. the "$t$" could just as well be another random variable like $"k"$ or whatever.
    – user463102
    Sep 3 at 11:55











  • @Arthur I agree, terrible idea! But look at $A_4$ and $A_4^t$, that's not how the transpose works!
    – MRobinson
    Sep 3 at 11:57










  • Have you tried diagonalisation. The first few are obvious
    – Bruce
    Sep 3 at 12:02






  • 3




    Compute the first powers by hand and look for a pattern.
    – Yves Daoust
    Sep 3 at 12:05














up vote
0
down vote

favorite












Compute the matrix $A^t$ for the following cases:



$A_1=beginbmatrix0&0\0&1endbmatrix, quad A_2=beginbmatrix-1&0\0&-2 endbmatrix, quad A_3=beginbmatrix0&1\0&0endbmatrix, quad A_4=beginbmatrix0&1&0\0&0&1\0&0&0endbmatrix, quad A_5=beginbmatrix1&1\1&1endbmatrix$



And the answers should be:



$ quad A^t_1=beginbmatrix0^t&0\0&1^t endbmatrix, quad A^t_2=beginbmatrix(-1)^t&0\0&(-2)^t endbmatrix, quad A^t_3=beginbmatrixdelta(t)&delta(t-1)\0&delta(t) endbmatrix,quad A^t_4=beginbmatrixdelta(t)&delta(t-1)&delta(t-2)\0&delta(t)&delta(t-1)\0&0&delta(t)endbmatrix,quad A^t_5=frac12beginbmatrix0^t+2^t&-0^t+2^t\-0^t+2^t&0^t+2^t endbmatrix$



where
$ delta(j)=0^j=left{
beginarrayll
1 textfor j = 0\
0 textfor j neq 0\
endarray
right.
$



How is this done? What kind of sorcery is this?



I've checked on the net but all I could find were tricky mathematical definitions, while I'm looking for a simple "how to".



Help me Stackexchange, you are my only hope.










share|cite|improve this question

















  • 2




    It's a capital $^T$ for transposition. OP: have you tried just writing down a few terms in the sequence? e.g. $A_1^2, A_1^3$ and seeing what you get?
    – MRobinson
    Sep 3 at 11:52







  • 1




    No it's not the transpose. The answers are shown below. It has to do with the response to discrete time autonomous linear systems. the "$t$" could just as well be another random variable like $"k"$ or whatever.
    – user463102
    Sep 3 at 11:55











  • @Arthur I agree, terrible idea! But look at $A_4$ and $A_4^t$, that's not how the transpose works!
    – MRobinson
    Sep 3 at 11:57










  • Have you tried diagonalisation. The first few are obvious
    – Bruce
    Sep 3 at 12:02






  • 3




    Compute the first powers by hand and look for a pattern.
    – Yves Daoust
    Sep 3 at 12:05












up vote
0
down vote

favorite









up vote
0
down vote

favorite











Compute the matrix $A^t$ for the following cases:



$A_1=beginbmatrix0&0\0&1endbmatrix, quad A_2=beginbmatrix-1&0\0&-2 endbmatrix, quad A_3=beginbmatrix0&1\0&0endbmatrix, quad A_4=beginbmatrix0&1&0\0&0&1\0&0&0endbmatrix, quad A_5=beginbmatrix1&1\1&1endbmatrix$



And the answers should be:



$ quad A^t_1=beginbmatrix0^t&0\0&1^t endbmatrix, quad A^t_2=beginbmatrix(-1)^t&0\0&(-2)^t endbmatrix, quad A^t_3=beginbmatrixdelta(t)&delta(t-1)\0&delta(t) endbmatrix,quad A^t_4=beginbmatrixdelta(t)&delta(t-1)&delta(t-2)\0&delta(t)&delta(t-1)\0&0&delta(t)endbmatrix,quad A^t_5=frac12beginbmatrix0^t+2^t&-0^t+2^t\-0^t+2^t&0^t+2^t endbmatrix$



where
$ delta(j)=0^j=left{
beginarrayll
1 textfor j = 0\
0 textfor j neq 0\
endarray
right.
$



How is this done? What kind of sorcery is this?



I've checked on the net but all I could find were tricky mathematical definitions, while I'm looking for a simple "how to".



Help me Stackexchange, you are my only hope.










share|cite|improve this question













Compute the matrix $A^t$ for the following cases:



$A_1=beginbmatrix0&0\0&1endbmatrix, quad A_2=beginbmatrix-1&0\0&-2 endbmatrix, quad A_3=beginbmatrix0&1\0&0endbmatrix, quad A_4=beginbmatrix0&1&0\0&0&1\0&0&0endbmatrix, quad A_5=beginbmatrix1&1\1&1endbmatrix$



And the answers should be:



$ quad A^t_1=beginbmatrix0^t&0\0&1^t endbmatrix, quad A^t_2=beginbmatrix(-1)^t&0\0&(-2)^t endbmatrix, quad A^t_3=beginbmatrixdelta(t)&delta(t-1)\0&delta(t) endbmatrix,quad A^t_4=beginbmatrixdelta(t)&delta(t-1)&delta(t-2)\0&delta(t)&delta(t-1)\0&0&delta(t)endbmatrix,quad A^t_5=frac12beginbmatrix0^t+2^t&-0^t+2^t\-0^t+2^t&0^t+2^t endbmatrix$



where
$ delta(j)=0^j=left{
beginarrayll
1 textfor j = 0\
0 textfor j neq 0\
endarray
right.
$



How is this done? What kind of sorcery is this?



I've checked on the net but all I could find were tricky mathematical definitions, while I'm looking for a simple "how to".



Help me Stackexchange, you are my only hope.







linear-algebra control-theory linear-control






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asked Sep 3 at 11:47









user463102

1519




1519







  • 2




    It's a capital $^T$ for transposition. OP: have you tried just writing down a few terms in the sequence? e.g. $A_1^2, A_1^3$ and seeing what you get?
    – MRobinson
    Sep 3 at 11:52







  • 1




    No it's not the transpose. The answers are shown below. It has to do with the response to discrete time autonomous linear systems. the "$t$" could just as well be another random variable like $"k"$ or whatever.
    – user463102
    Sep 3 at 11:55











  • @Arthur I agree, terrible idea! But look at $A_4$ and $A_4^t$, that's not how the transpose works!
    – MRobinson
    Sep 3 at 11:57










  • Have you tried diagonalisation. The first few are obvious
    – Bruce
    Sep 3 at 12:02






  • 3




    Compute the first powers by hand and look for a pattern.
    – Yves Daoust
    Sep 3 at 12:05












  • 2




    It's a capital $^T$ for transposition. OP: have you tried just writing down a few terms in the sequence? e.g. $A_1^2, A_1^3$ and seeing what you get?
    – MRobinson
    Sep 3 at 11:52







  • 1




    No it's not the transpose. The answers are shown below. It has to do with the response to discrete time autonomous linear systems. the "$t$" could just as well be another random variable like $"k"$ or whatever.
    – user463102
    Sep 3 at 11:55











  • @Arthur I agree, terrible idea! But look at $A_4$ and $A_4^t$, that's not how the transpose works!
    – MRobinson
    Sep 3 at 11:57










  • Have you tried diagonalisation. The first few are obvious
    – Bruce
    Sep 3 at 12:02






  • 3




    Compute the first powers by hand and look for a pattern.
    – Yves Daoust
    Sep 3 at 12:05







2




2




It's a capital $^T$ for transposition. OP: have you tried just writing down a few terms in the sequence? e.g. $A_1^2, A_1^3$ and seeing what you get?
– MRobinson
Sep 3 at 11:52





It's a capital $^T$ for transposition. OP: have you tried just writing down a few terms in the sequence? e.g. $A_1^2, A_1^3$ and seeing what you get?
– MRobinson
Sep 3 at 11:52





1




1




No it's not the transpose. The answers are shown below. It has to do with the response to discrete time autonomous linear systems. the "$t$" could just as well be another random variable like $"k"$ or whatever.
– user463102
Sep 3 at 11:55





No it's not the transpose. The answers are shown below. It has to do with the response to discrete time autonomous linear systems. the "$t$" could just as well be another random variable like $"k"$ or whatever.
– user463102
Sep 3 at 11:55













@Arthur I agree, terrible idea! But look at $A_4$ and $A_4^t$, that's not how the transpose works!
– MRobinson
Sep 3 at 11:57




@Arthur I agree, terrible idea! But look at $A_4$ and $A_4^t$, that's not how the transpose works!
– MRobinson
Sep 3 at 11:57












Have you tried diagonalisation. The first few are obvious
– Bruce
Sep 3 at 12:02




Have you tried diagonalisation. The first few are obvious
– Bruce
Sep 3 at 12:02




3




3




Compute the first powers by hand and look for a pattern.
– Yves Daoust
Sep 3 at 12:05




Compute the first powers by hand and look for a pattern.
– Yves Daoust
Sep 3 at 12:05










2 Answers
2






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up vote
1
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accepted










For a diagonal $ntimes n$ matrix, it is not very hard to check that
$$bigl(D(a_1,dots,a_n)bigr)^t=D(a_1^t,dots,a_n^t).$$



For $A_3$ and $A_4$, just compute the first values to find that
$$A_3^2=0,quad A_4^2=beginpmatrix0&0&1\0&0&0\0&0&0endpmatrix,quad A_4^3=0.$$



For $A_5$, you can prove by induction that $$A_5^t=beginpmatrix2^t-1&2^t-1\ 2^t-1&2^t-1endpmatrix.$$






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    up vote
    1
    down vote













    Raise each matrix to powers and use math induction to prove the given results.



    The notation should not bother you if you use your own notation instead of those $delta$ stuff.



    Some like $A_1$ and $A_2$ are obvious and others take some time but are not too bad.






    share|cite|improve this answer




















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      2 Answers
      2






      active

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      2 Answers
      2






      active

      oldest

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      active

      oldest

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      active

      oldest

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      up vote
      1
      down vote



      accepted










      For a diagonal $ntimes n$ matrix, it is not very hard to check that
      $$bigl(D(a_1,dots,a_n)bigr)^t=D(a_1^t,dots,a_n^t).$$



      For $A_3$ and $A_4$, just compute the first values to find that
      $$A_3^2=0,quad A_4^2=beginpmatrix0&0&1\0&0&0\0&0&0endpmatrix,quad A_4^3=0.$$



      For $A_5$, you can prove by induction that $$A_5^t=beginpmatrix2^t-1&2^t-1\ 2^t-1&2^t-1endpmatrix.$$






      share|cite|improve this answer
























        up vote
        1
        down vote



        accepted










        For a diagonal $ntimes n$ matrix, it is not very hard to check that
        $$bigl(D(a_1,dots,a_n)bigr)^t=D(a_1^t,dots,a_n^t).$$



        For $A_3$ and $A_4$, just compute the first values to find that
        $$A_3^2=0,quad A_4^2=beginpmatrix0&0&1\0&0&0\0&0&0endpmatrix,quad A_4^3=0.$$



        For $A_5$, you can prove by induction that $$A_5^t=beginpmatrix2^t-1&2^t-1\ 2^t-1&2^t-1endpmatrix.$$






        share|cite|improve this answer






















          up vote
          1
          down vote



          accepted







          up vote
          1
          down vote



          accepted






          For a diagonal $ntimes n$ matrix, it is not very hard to check that
          $$bigl(D(a_1,dots,a_n)bigr)^t=D(a_1^t,dots,a_n^t).$$



          For $A_3$ and $A_4$, just compute the first values to find that
          $$A_3^2=0,quad A_4^2=beginpmatrix0&0&1\0&0&0\0&0&0endpmatrix,quad A_4^3=0.$$



          For $A_5$, you can prove by induction that $$A_5^t=beginpmatrix2^t-1&2^t-1\ 2^t-1&2^t-1endpmatrix.$$






          share|cite|improve this answer












          For a diagonal $ntimes n$ matrix, it is not very hard to check that
          $$bigl(D(a_1,dots,a_n)bigr)^t=D(a_1^t,dots,a_n^t).$$



          For $A_3$ and $A_4$, just compute the first values to find that
          $$A_3^2=0,quad A_4^2=beginpmatrix0&0&1\0&0&0\0&0&0endpmatrix,quad A_4^3=0.$$



          For $A_5$, you can prove by induction that $$A_5^t=beginpmatrix2^t-1&2^t-1\ 2^t-1&2^t-1endpmatrix.$$







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Sep 3 at 12:02









          Bernard

          112k635104




          112k635104




















              up vote
              1
              down vote













              Raise each matrix to powers and use math induction to prove the given results.



              The notation should not bother you if you use your own notation instead of those $delta$ stuff.



              Some like $A_1$ and $A_2$ are obvious and others take some time but are not too bad.






              share|cite|improve this answer
























                up vote
                1
                down vote













                Raise each matrix to powers and use math induction to prove the given results.



                The notation should not bother you if you use your own notation instead of those $delta$ stuff.



                Some like $A_1$ and $A_2$ are obvious and others take some time but are not too bad.






                share|cite|improve this answer






















                  up vote
                  1
                  down vote










                  up vote
                  1
                  down vote









                  Raise each matrix to powers and use math induction to prove the given results.



                  The notation should not bother you if you use your own notation instead of those $delta$ stuff.



                  Some like $A_1$ and $A_2$ are obvious and others take some time but are not too bad.






                  share|cite|improve this answer












                  Raise each matrix to powers and use math induction to prove the given results.



                  The notation should not bother you if you use your own notation instead of those $delta$ stuff.



                  Some like $A_1$ and $A_2$ are obvious and others take some time but are not too bad.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered Sep 3 at 12:17









                  Mohammad Riazi-Kermani

                  31.4k41853




                  31.4k41853



























                       

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