Other inner products for $mathbbR^n$Defining an Inner ProductInner product alternative definitionFinding uniq inner product satisying the following requierments:Prove that there is a unique inner product on $V$Characterisation of inner products preserved by an automorphismThe Redundancy of applying the Gram-Schmidt Procedure on an orthogonal subset of $V$.If complementary subspaces are almost orthogonal, is the same true for their orthogonal complements?Find inner product that meets primary decomposition criteriasan orthogonal map associated with inner productHow to prove Cauchy-Schwarz inequality using multivariable calculus?

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Other inner products for $mathbbR^n$


Defining an Inner ProductInner product alternative definitionFinding uniq inner product satisying the following requierments:Prove that there is a unique inner product on $V$Characterisation of inner products preserved by an automorphismThe Redundancy of applying the Gram-Schmidt Procedure on an orthogonal subset of $V$.If complementary subspaces are almost orthogonal, is the same true for their orthogonal complements?Find inner product that meets primary decomposition criteriasan orthogonal map associated with inner productHow to prove Cauchy-Schwarz inequality using multivariable calculus?













1












$begingroup$


For $mathbbR^n$, the standard inner product is the dot product. It is defined as $ langle v,,wrangle = sum_i v_i cdot w_i $. I am aware that any scaled version, namely
$ langle v,,wrangle = sum_ilambda_icdot v_i cdot w_i $ will still satisfy the 4 inner product requirements.



Is there any inner product for $mathbbR^n$ that is not just a scaled version of the standard dot product?



I tried for $mathbbR^2$ with $ langle v,,wrangle = v_1 cdot w_2 + v_2 cdot w_1 $ but that is not positive definite.










share|cite|improve this question











$endgroup$











  • $begingroup$
    So, everyone is saying you can also use a matrix, and that works. Is there a proof though that any inner product can be represented by such a matrix type inner product?
    $endgroup$
    – Ion Sme
    2 days ago










  • $begingroup$
    $newcommandRmathbbRnewcommandumathbfe$Yes. Here is a sketch. Suppose that $(cdot, cdot)$ is some inner product on $R^n$. Let $u_1, ldots,u_n$ be the standard basis for $R^n$ (so $u_k$ is a vector whose $k$-th entry is $1$, and all other entries are $0$). Define $A$ to be the $ntimes n$ matrix with $i,j$ entry $colorbluea_ij= (u_i, u_j)$. Then show that this $A$ satisfies $(mathbfx, mathbfy) = mathbfx^T A mathbfy$ for all $mathbfx,mathbfyin R^n$. EDIT: I see Travis has mentioned this in an answer below.
    $endgroup$
    – Minus One-Twelfth
    2 days ago
















1












$begingroup$


For $mathbbR^n$, the standard inner product is the dot product. It is defined as $ langle v,,wrangle = sum_i v_i cdot w_i $. I am aware that any scaled version, namely
$ langle v,,wrangle = sum_ilambda_icdot v_i cdot w_i $ will still satisfy the 4 inner product requirements.



Is there any inner product for $mathbbR^n$ that is not just a scaled version of the standard dot product?



I tried for $mathbbR^2$ with $ langle v,,wrangle = v_1 cdot w_2 + v_2 cdot w_1 $ but that is not positive definite.










share|cite|improve this question











$endgroup$











  • $begingroup$
    So, everyone is saying you can also use a matrix, and that works. Is there a proof though that any inner product can be represented by such a matrix type inner product?
    $endgroup$
    – Ion Sme
    2 days ago










  • $begingroup$
    $newcommandRmathbbRnewcommandumathbfe$Yes. Here is a sketch. Suppose that $(cdot, cdot)$ is some inner product on $R^n$. Let $u_1, ldots,u_n$ be the standard basis for $R^n$ (so $u_k$ is a vector whose $k$-th entry is $1$, and all other entries are $0$). Define $A$ to be the $ntimes n$ matrix with $i,j$ entry $colorbluea_ij= (u_i, u_j)$. Then show that this $A$ satisfies $(mathbfx, mathbfy) = mathbfx^T A mathbfy$ for all $mathbfx,mathbfyin R^n$. EDIT: I see Travis has mentioned this in an answer below.
    $endgroup$
    – Minus One-Twelfth
    2 days ago














1












1








1


1



$begingroup$


For $mathbbR^n$, the standard inner product is the dot product. It is defined as $ langle v,,wrangle = sum_i v_i cdot w_i $. I am aware that any scaled version, namely
$ langle v,,wrangle = sum_ilambda_icdot v_i cdot w_i $ will still satisfy the 4 inner product requirements.



Is there any inner product for $mathbbR^n$ that is not just a scaled version of the standard dot product?



I tried for $mathbbR^2$ with $ langle v,,wrangle = v_1 cdot w_2 + v_2 cdot w_1 $ but that is not positive definite.










share|cite|improve this question











$endgroup$




For $mathbbR^n$, the standard inner product is the dot product. It is defined as $ langle v,,wrangle = sum_i v_i cdot w_i $. I am aware that any scaled version, namely
$ langle v,,wrangle = sum_ilambda_icdot v_i cdot w_i $ will still satisfy the 4 inner product requirements.



Is there any inner product for $mathbbR^n$ that is not just a scaled version of the standard dot product?



I tried for $mathbbR^2$ with $ langle v,,wrangle = v_1 cdot w_2 + v_2 cdot w_1 $ but that is not positive definite.







linear-algebra inner-product-space






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited 2 days ago









J.G.

29.6k22946




29.6k22946










asked 2 days ago









Ion SmeIon Sme

11510




11510











  • $begingroup$
    So, everyone is saying you can also use a matrix, and that works. Is there a proof though that any inner product can be represented by such a matrix type inner product?
    $endgroup$
    – Ion Sme
    2 days ago










  • $begingroup$
    $newcommandRmathbbRnewcommandumathbfe$Yes. Here is a sketch. Suppose that $(cdot, cdot)$ is some inner product on $R^n$. Let $u_1, ldots,u_n$ be the standard basis for $R^n$ (so $u_k$ is a vector whose $k$-th entry is $1$, and all other entries are $0$). Define $A$ to be the $ntimes n$ matrix with $i,j$ entry $colorbluea_ij= (u_i, u_j)$. Then show that this $A$ satisfies $(mathbfx, mathbfy) = mathbfx^T A mathbfy$ for all $mathbfx,mathbfyin R^n$. EDIT: I see Travis has mentioned this in an answer below.
    $endgroup$
    – Minus One-Twelfth
    2 days ago

















  • $begingroup$
    So, everyone is saying you can also use a matrix, and that works. Is there a proof though that any inner product can be represented by such a matrix type inner product?
    $endgroup$
    – Ion Sme
    2 days ago










  • $begingroup$
    $newcommandRmathbbRnewcommandumathbfe$Yes. Here is a sketch. Suppose that $(cdot, cdot)$ is some inner product on $R^n$. Let $u_1, ldots,u_n$ be the standard basis for $R^n$ (so $u_k$ is a vector whose $k$-th entry is $1$, and all other entries are $0$). Define $A$ to be the $ntimes n$ matrix with $i,j$ entry $colorbluea_ij= (u_i, u_j)$. Then show that this $A$ satisfies $(mathbfx, mathbfy) = mathbfx^T A mathbfy$ for all $mathbfx,mathbfyin R^n$. EDIT: I see Travis has mentioned this in an answer below.
    $endgroup$
    – Minus One-Twelfth
    2 days ago
















$begingroup$
So, everyone is saying you can also use a matrix, and that works. Is there a proof though that any inner product can be represented by such a matrix type inner product?
$endgroup$
– Ion Sme
2 days ago




$begingroup$
So, everyone is saying you can also use a matrix, and that works. Is there a proof though that any inner product can be represented by such a matrix type inner product?
$endgroup$
– Ion Sme
2 days ago












$begingroup$
$newcommandRmathbbRnewcommandumathbfe$Yes. Here is a sketch. Suppose that $(cdot, cdot)$ is some inner product on $R^n$. Let $u_1, ldots,u_n$ be the standard basis for $R^n$ (so $u_k$ is a vector whose $k$-th entry is $1$, and all other entries are $0$). Define $A$ to be the $ntimes n$ matrix with $i,j$ entry $colorbluea_ij= (u_i, u_j)$. Then show that this $A$ satisfies $(mathbfx, mathbfy) = mathbfx^T A mathbfy$ for all $mathbfx,mathbfyin R^n$. EDIT: I see Travis has mentioned this in an answer below.
$endgroup$
– Minus One-Twelfth
2 days ago





$begingroup$
$newcommandRmathbbRnewcommandumathbfe$Yes. Here is a sketch. Suppose that $(cdot, cdot)$ is some inner product on $R^n$. Let $u_1, ldots,u_n$ be the standard basis for $R^n$ (so $u_k$ is a vector whose $k$-th entry is $1$, and all other entries are $0$). Define $A$ to be the $ntimes n$ matrix with $i,j$ entry $colorbluea_ij= (u_i, u_j)$. Then show that this $A$ satisfies $(mathbfx, mathbfy) = mathbfx^T A mathbfy$ for all $mathbfx,mathbfyin R^n$. EDIT: I see Travis has mentioned this in an answer below.
$endgroup$
– Minus One-Twelfth
2 days ago











7 Answers
7






active

oldest

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2












$begingroup$

Yes. Given any positive definite $n times n$ matrix $A$, $$bf x cdot bf y := bf y^top A bf x$$
defines an inner product on $Bbb R^n$, and for $n > 1$ there are nondiagonal positive definite matrices, for example,
$$pmatrix1&epsilon\epsilon&1\&&1\&&&ddots\&&&&1$$
for any $0 < |epsilon| < 1$.



Conversely all inner products arise this way, as we can recover $A$ by setting $$A_ij = bf e_i cdot bf e_j$$ for the standard basis $(bf e_i)$.



On the other hand, given any inner product on $Bbb R^n$, applying the Gram-Schmidt Process produces an orthonormal basis $(bf f_i)$, so the matrix representation of the inner product with respect to that basis is the identity matrix, $I_n$. In this sense, all inner products on $Bbb R^n$ are equivalent.






share|cite|improve this answer











$endgroup$








  • 1




    $begingroup$
    I think that if OP knew what a positive definite symmetric matrix is, there would be no need to pose the question as it is.
    $endgroup$
    – Marc van Leeuwen
    yesterday










  • $begingroup$
    @MarcvanLeeuwen Thanks for the comment. And yes, I agree, but one needs that language in order to state the result precisely. Still, that probably means OP would benefit from a concrete example, which I've added to the answer.
    $endgroup$
    – Travis
    yesterday



















1












$begingroup$

For any invertible linear transformation $A$ you can define the inner product $langle v,wrangle_A=langle Av,Awrangle$ where $langlecdot,cdotrangle$ denotes the standard inner product. I expect there are no other inner products, which is motivated by the fact that all inner products are known to induce equivalent norms.






share|cite|improve this answer









$endgroup$




















    1












    $begingroup$

    Technically, you need positive $lambda_i$. Or if we use $sum_ijlambda_ijv_iw_j$, the matrix $lambda$ is without loss of generality equal to $(lambda+lambda^T)/2$, and it has to be positive-definite. (Yes, this matrix property has the same name; it basically means it has only positive eigenvalues.) With an appropriate basis change we can then diagonalize this matrix, which recovers the case you knew about. As for the example you tried, it failed because if you work out the matrix $lambda=left(beginarraycc
    0 & 1\
    1 & 0
    endarrayright)$
    (once we make it self-adjoint as explained above), which has $-1$ as an eigenvalue.






    share|cite|improve this answer











    $endgroup$












    • $begingroup$
      Where does the condition $lambda = (lambda+lambda^T)/2$ come from?
      $endgroup$
      – Ion Sme
      2 days ago











    • $begingroup$
      @IonSme As I said, it's imposed without loss of generality. If you replace $lambda$ as thus, the resulting inner product won't be changed. (This is obvious in the case $v=w$, but in fact this is exhaustive because norms determine an inner product viz. $langle v,, wrangle = (Vert v+wVert^2-Vert v-wVert^2)/4$.)
      $endgroup$
      – J.G.
      2 days ago



















    0












    $begingroup$

    Inner products $p(x,y)$ on $mathbb R^n$ have the form
    $$
    p(x,y) = sum_j=1^n sum_k=1^n a_jk x_j y_k
    $$

    where the matrix $A = [a_jk]$ is positive definite. Choosing a basis of eigenvectors for the matrix $A$, and expanding according to this new basis instead of the original basis, the inner product is then diagonal:
    $$
    p(x,y) = sum_j=1^n b_j x_j y_j
    $$

    where $b_j>0$.






    share|cite|improve this answer









    $endgroup$




















      0












      $begingroup$

      I agree with SmileyCraft. In finite dimensional vector spaces, bilinear transformations, as linear transformations, can be written in terms of the values that they adopt in a given base:$$left langle x,y right rangle=sum_i,j=1^nx_iy_jleft langle e_i,e_j right rangle.$$
      I believe you can arrive in this representation without difficult, proving then you suspicion.






      share|cite|improve this answer








      New contributor




      Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






      $endgroup$




















        0












        $begingroup$

        It is well known (and easy to prove) that any two finite dimensional inner product spaces are isometrically isomorphic. Hence $ langle x, y rangle'$ is an inner product on $mathbb R^n$ iff there is a vector space isomorphism $T: mathbb R^n to mathbb R^n$ such that $langle x, y rangle' =langle Tx, Ty rangle$ for all $x,y$.






        share|cite|improve this answer









        $endgroup$




















          0












          $begingroup$

          In general, for any $ntimes n$ matrix $A=(a_i,j)_i,j=1,ldots,n$ the expression $sum_i,j=1^na_i,jx_iy_j$ defines a bilinear form, which will be symmetric if and only $A$ is. Giving a positive definite symmetric bilinear form is a more subtle condition that leads to inequalities for the coefficients of $A$ (and the matrices that satisfy the condition are naturally called positive definite). For $2times2$ symmetric matrices the positive definite condition is $a_1,1>0$, $a_2,2>0$ together with $a_1,1a_2,2-a_1,2^2>0$ (so $det(A)>0$). For a concrete example, the symmetric matrix
          $$
          A=pmatrix1&frac12\frac12&1
          quadtextgives an inner product with
          langle v,,wrangle = v_1w_1 +frac12(v_1w_2+v_2w_1) + v_2w_2,.
          $$



          In higher dimension the condition is more complicated, but in any case one does get many different inner products on $Bbb R^n$ in this way. They do turn out to be all equivalent in the sense that they give rise to the same structure theory, but they are not equal.






          share|cite|improve this answer











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            7 Answers
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            active

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            7 Answers
            7






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            2












            $begingroup$

            Yes. Given any positive definite $n times n$ matrix $A$, $$bf x cdot bf y := bf y^top A bf x$$
            defines an inner product on $Bbb R^n$, and for $n > 1$ there are nondiagonal positive definite matrices, for example,
            $$pmatrix1&epsilon\epsilon&1\&&1\&&&ddots\&&&&1$$
            for any $0 < |epsilon| < 1$.



            Conversely all inner products arise this way, as we can recover $A$ by setting $$A_ij = bf e_i cdot bf e_j$$ for the standard basis $(bf e_i)$.



            On the other hand, given any inner product on $Bbb R^n$, applying the Gram-Schmidt Process produces an orthonormal basis $(bf f_i)$, so the matrix representation of the inner product with respect to that basis is the identity matrix, $I_n$. In this sense, all inner products on $Bbb R^n$ are equivalent.






            share|cite|improve this answer











            $endgroup$








            • 1




              $begingroup$
              I think that if OP knew what a positive definite symmetric matrix is, there would be no need to pose the question as it is.
              $endgroup$
              – Marc van Leeuwen
              yesterday










            • $begingroup$
              @MarcvanLeeuwen Thanks for the comment. And yes, I agree, but one needs that language in order to state the result precisely. Still, that probably means OP would benefit from a concrete example, which I've added to the answer.
              $endgroup$
              – Travis
              yesterday
















            2












            $begingroup$

            Yes. Given any positive definite $n times n$ matrix $A$, $$bf x cdot bf y := bf y^top A bf x$$
            defines an inner product on $Bbb R^n$, and for $n > 1$ there are nondiagonal positive definite matrices, for example,
            $$pmatrix1&epsilon\epsilon&1\&&1\&&&ddots\&&&&1$$
            for any $0 < |epsilon| < 1$.



            Conversely all inner products arise this way, as we can recover $A$ by setting $$A_ij = bf e_i cdot bf e_j$$ for the standard basis $(bf e_i)$.



            On the other hand, given any inner product on $Bbb R^n$, applying the Gram-Schmidt Process produces an orthonormal basis $(bf f_i)$, so the matrix representation of the inner product with respect to that basis is the identity matrix, $I_n$. In this sense, all inner products on $Bbb R^n$ are equivalent.






            share|cite|improve this answer











            $endgroup$








            • 1




              $begingroup$
              I think that if OP knew what a positive definite symmetric matrix is, there would be no need to pose the question as it is.
              $endgroup$
              – Marc van Leeuwen
              yesterday










            • $begingroup$
              @MarcvanLeeuwen Thanks for the comment. And yes, I agree, but one needs that language in order to state the result precisely. Still, that probably means OP would benefit from a concrete example, which I've added to the answer.
              $endgroup$
              – Travis
              yesterday














            2












            2








            2





            $begingroup$

            Yes. Given any positive definite $n times n$ matrix $A$, $$bf x cdot bf y := bf y^top A bf x$$
            defines an inner product on $Bbb R^n$, and for $n > 1$ there are nondiagonal positive definite matrices, for example,
            $$pmatrix1&epsilon\epsilon&1\&&1\&&&ddots\&&&&1$$
            for any $0 < |epsilon| < 1$.



            Conversely all inner products arise this way, as we can recover $A$ by setting $$A_ij = bf e_i cdot bf e_j$$ for the standard basis $(bf e_i)$.



            On the other hand, given any inner product on $Bbb R^n$, applying the Gram-Schmidt Process produces an orthonormal basis $(bf f_i)$, so the matrix representation of the inner product with respect to that basis is the identity matrix, $I_n$. In this sense, all inner products on $Bbb R^n$ are equivalent.






            share|cite|improve this answer











            $endgroup$



            Yes. Given any positive definite $n times n$ matrix $A$, $$bf x cdot bf y := bf y^top A bf x$$
            defines an inner product on $Bbb R^n$, and for $n > 1$ there are nondiagonal positive definite matrices, for example,
            $$pmatrix1&epsilon\epsilon&1\&&1\&&&ddots\&&&&1$$
            for any $0 < |epsilon| < 1$.



            Conversely all inner products arise this way, as we can recover $A$ by setting $$A_ij = bf e_i cdot bf e_j$$ for the standard basis $(bf e_i)$.



            On the other hand, given any inner product on $Bbb R^n$, applying the Gram-Schmidt Process produces an orthonormal basis $(bf f_i)$, so the matrix representation of the inner product with respect to that basis is the identity matrix, $I_n$. In this sense, all inner products on $Bbb R^n$ are equivalent.







            share|cite|improve this answer














            share|cite|improve this answer



            share|cite|improve this answer








            edited yesterday

























            answered 2 days ago









            TravisTravis

            63k767150




            63k767150







            • 1




              $begingroup$
              I think that if OP knew what a positive definite symmetric matrix is, there would be no need to pose the question as it is.
              $endgroup$
              – Marc van Leeuwen
              yesterday










            • $begingroup$
              @MarcvanLeeuwen Thanks for the comment. And yes, I agree, but one needs that language in order to state the result precisely. Still, that probably means OP would benefit from a concrete example, which I've added to the answer.
              $endgroup$
              – Travis
              yesterday













            • 1




              $begingroup$
              I think that if OP knew what a positive definite symmetric matrix is, there would be no need to pose the question as it is.
              $endgroup$
              – Marc van Leeuwen
              yesterday










            • $begingroup$
              @MarcvanLeeuwen Thanks for the comment. And yes, I agree, but one needs that language in order to state the result precisely. Still, that probably means OP would benefit from a concrete example, which I've added to the answer.
              $endgroup$
              – Travis
              yesterday








            1




            1




            $begingroup$
            I think that if OP knew what a positive definite symmetric matrix is, there would be no need to pose the question as it is.
            $endgroup$
            – Marc van Leeuwen
            yesterday




            $begingroup$
            I think that if OP knew what a positive definite symmetric matrix is, there would be no need to pose the question as it is.
            $endgroup$
            – Marc van Leeuwen
            yesterday












            $begingroup$
            @MarcvanLeeuwen Thanks for the comment. And yes, I agree, but one needs that language in order to state the result precisely. Still, that probably means OP would benefit from a concrete example, which I've added to the answer.
            $endgroup$
            – Travis
            yesterday





            $begingroup$
            @MarcvanLeeuwen Thanks for the comment. And yes, I agree, but one needs that language in order to state the result precisely. Still, that probably means OP would benefit from a concrete example, which I've added to the answer.
            $endgroup$
            – Travis
            yesterday












            1












            $begingroup$

            For any invertible linear transformation $A$ you can define the inner product $langle v,wrangle_A=langle Av,Awrangle$ where $langlecdot,cdotrangle$ denotes the standard inner product. I expect there are no other inner products, which is motivated by the fact that all inner products are known to induce equivalent norms.






            share|cite|improve this answer









            $endgroup$

















              1












              $begingroup$

              For any invertible linear transformation $A$ you can define the inner product $langle v,wrangle_A=langle Av,Awrangle$ where $langlecdot,cdotrangle$ denotes the standard inner product. I expect there are no other inner products, which is motivated by the fact that all inner products are known to induce equivalent norms.






              share|cite|improve this answer









              $endgroup$















                1












                1








                1





                $begingroup$

                For any invertible linear transformation $A$ you can define the inner product $langle v,wrangle_A=langle Av,Awrangle$ where $langlecdot,cdotrangle$ denotes the standard inner product. I expect there are no other inner products, which is motivated by the fact that all inner products are known to induce equivalent norms.






                share|cite|improve this answer









                $endgroup$



                For any invertible linear transformation $A$ you can define the inner product $langle v,wrangle_A=langle Av,Awrangle$ where $langlecdot,cdotrangle$ denotes the standard inner product. I expect there are no other inner products, which is motivated by the fact that all inner products are known to induce equivalent norms.







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered 2 days ago









                SmileyCraftSmileyCraft

                3,626519




                3,626519





















                    1












                    $begingroup$

                    Technically, you need positive $lambda_i$. Or if we use $sum_ijlambda_ijv_iw_j$, the matrix $lambda$ is without loss of generality equal to $(lambda+lambda^T)/2$, and it has to be positive-definite. (Yes, this matrix property has the same name; it basically means it has only positive eigenvalues.) With an appropriate basis change we can then diagonalize this matrix, which recovers the case you knew about. As for the example you tried, it failed because if you work out the matrix $lambda=left(beginarraycc
                    0 & 1\
                    1 & 0
                    endarrayright)$
                    (once we make it self-adjoint as explained above), which has $-1$ as an eigenvalue.






                    share|cite|improve this answer











                    $endgroup$












                    • $begingroup$
                      Where does the condition $lambda = (lambda+lambda^T)/2$ come from?
                      $endgroup$
                      – Ion Sme
                      2 days ago











                    • $begingroup$
                      @IonSme As I said, it's imposed without loss of generality. If you replace $lambda$ as thus, the resulting inner product won't be changed. (This is obvious in the case $v=w$, but in fact this is exhaustive because norms determine an inner product viz. $langle v,, wrangle = (Vert v+wVert^2-Vert v-wVert^2)/4$.)
                      $endgroup$
                      – J.G.
                      2 days ago
















                    1












                    $begingroup$

                    Technically, you need positive $lambda_i$. Or if we use $sum_ijlambda_ijv_iw_j$, the matrix $lambda$ is without loss of generality equal to $(lambda+lambda^T)/2$, and it has to be positive-definite. (Yes, this matrix property has the same name; it basically means it has only positive eigenvalues.) With an appropriate basis change we can then diagonalize this matrix, which recovers the case you knew about. As for the example you tried, it failed because if you work out the matrix $lambda=left(beginarraycc
                    0 & 1\
                    1 & 0
                    endarrayright)$
                    (once we make it self-adjoint as explained above), which has $-1$ as an eigenvalue.






                    share|cite|improve this answer











                    $endgroup$












                    • $begingroup$
                      Where does the condition $lambda = (lambda+lambda^T)/2$ come from?
                      $endgroup$
                      – Ion Sme
                      2 days ago











                    • $begingroup$
                      @IonSme As I said, it's imposed without loss of generality. If you replace $lambda$ as thus, the resulting inner product won't be changed. (This is obvious in the case $v=w$, but in fact this is exhaustive because norms determine an inner product viz. $langle v,, wrangle = (Vert v+wVert^2-Vert v-wVert^2)/4$.)
                      $endgroup$
                      – J.G.
                      2 days ago














                    1












                    1








                    1





                    $begingroup$

                    Technically, you need positive $lambda_i$. Or if we use $sum_ijlambda_ijv_iw_j$, the matrix $lambda$ is without loss of generality equal to $(lambda+lambda^T)/2$, and it has to be positive-definite. (Yes, this matrix property has the same name; it basically means it has only positive eigenvalues.) With an appropriate basis change we can then diagonalize this matrix, which recovers the case you knew about. As for the example you tried, it failed because if you work out the matrix $lambda=left(beginarraycc
                    0 & 1\
                    1 & 0
                    endarrayright)$
                    (once we make it self-adjoint as explained above), which has $-1$ as an eigenvalue.






                    share|cite|improve this answer











                    $endgroup$



                    Technically, you need positive $lambda_i$. Or if we use $sum_ijlambda_ijv_iw_j$, the matrix $lambda$ is without loss of generality equal to $(lambda+lambda^T)/2$, and it has to be positive-definite. (Yes, this matrix property has the same name; it basically means it has only positive eigenvalues.) With an appropriate basis change we can then diagonalize this matrix, which recovers the case you knew about. As for the example you tried, it failed because if you work out the matrix $lambda=left(beginarraycc
                    0 & 1\
                    1 & 0
                    endarrayright)$
                    (once we make it self-adjoint as explained above), which has $-1$ as an eigenvalue.







                    share|cite|improve this answer














                    share|cite|improve this answer



                    share|cite|improve this answer








                    edited yesterday

























                    answered 2 days ago









                    J.G.J.G.

                    29.6k22946




                    29.6k22946











                    • $begingroup$
                      Where does the condition $lambda = (lambda+lambda^T)/2$ come from?
                      $endgroup$
                      – Ion Sme
                      2 days ago











                    • $begingroup$
                      @IonSme As I said, it's imposed without loss of generality. If you replace $lambda$ as thus, the resulting inner product won't be changed. (This is obvious in the case $v=w$, but in fact this is exhaustive because norms determine an inner product viz. $langle v,, wrangle = (Vert v+wVert^2-Vert v-wVert^2)/4$.)
                      $endgroup$
                      – J.G.
                      2 days ago

















                    • $begingroup$
                      Where does the condition $lambda = (lambda+lambda^T)/2$ come from?
                      $endgroup$
                      – Ion Sme
                      2 days ago











                    • $begingroup$
                      @IonSme As I said, it's imposed without loss of generality. If you replace $lambda$ as thus, the resulting inner product won't be changed. (This is obvious in the case $v=w$, but in fact this is exhaustive because norms determine an inner product viz. $langle v,, wrangle = (Vert v+wVert^2-Vert v-wVert^2)/4$.)
                      $endgroup$
                      – J.G.
                      2 days ago
















                    $begingroup$
                    Where does the condition $lambda = (lambda+lambda^T)/2$ come from?
                    $endgroup$
                    – Ion Sme
                    2 days ago





                    $begingroup$
                    Where does the condition $lambda = (lambda+lambda^T)/2$ come from?
                    $endgroup$
                    – Ion Sme
                    2 days ago













                    $begingroup$
                    @IonSme As I said, it's imposed without loss of generality. If you replace $lambda$ as thus, the resulting inner product won't be changed. (This is obvious in the case $v=w$, but in fact this is exhaustive because norms determine an inner product viz. $langle v,, wrangle = (Vert v+wVert^2-Vert v-wVert^2)/4$.)
                    $endgroup$
                    – J.G.
                    2 days ago





                    $begingroup$
                    @IonSme As I said, it's imposed without loss of generality. If you replace $lambda$ as thus, the resulting inner product won't be changed. (This is obvious in the case $v=w$, but in fact this is exhaustive because norms determine an inner product viz. $langle v,, wrangle = (Vert v+wVert^2-Vert v-wVert^2)/4$.)
                    $endgroup$
                    – J.G.
                    2 days ago












                    0












                    $begingroup$

                    Inner products $p(x,y)$ on $mathbb R^n$ have the form
                    $$
                    p(x,y) = sum_j=1^n sum_k=1^n a_jk x_j y_k
                    $$

                    where the matrix $A = [a_jk]$ is positive definite. Choosing a basis of eigenvectors for the matrix $A$, and expanding according to this new basis instead of the original basis, the inner product is then diagonal:
                    $$
                    p(x,y) = sum_j=1^n b_j x_j y_j
                    $$

                    where $b_j>0$.






                    share|cite|improve this answer









                    $endgroup$

















                      0












                      $begingroup$

                      Inner products $p(x,y)$ on $mathbb R^n$ have the form
                      $$
                      p(x,y) = sum_j=1^n sum_k=1^n a_jk x_j y_k
                      $$

                      where the matrix $A = [a_jk]$ is positive definite. Choosing a basis of eigenvectors for the matrix $A$, and expanding according to this new basis instead of the original basis, the inner product is then diagonal:
                      $$
                      p(x,y) = sum_j=1^n b_j x_j y_j
                      $$

                      where $b_j>0$.






                      share|cite|improve this answer









                      $endgroup$















                        0












                        0








                        0





                        $begingroup$

                        Inner products $p(x,y)$ on $mathbb R^n$ have the form
                        $$
                        p(x,y) = sum_j=1^n sum_k=1^n a_jk x_j y_k
                        $$

                        where the matrix $A = [a_jk]$ is positive definite. Choosing a basis of eigenvectors for the matrix $A$, and expanding according to this new basis instead of the original basis, the inner product is then diagonal:
                        $$
                        p(x,y) = sum_j=1^n b_j x_j y_j
                        $$

                        where $b_j>0$.






                        share|cite|improve this answer









                        $endgroup$



                        Inner products $p(x,y)$ on $mathbb R^n$ have the form
                        $$
                        p(x,y) = sum_j=1^n sum_k=1^n a_jk x_j y_k
                        $$

                        where the matrix $A = [a_jk]$ is positive definite. Choosing a basis of eigenvectors for the matrix $A$, and expanding according to this new basis instead of the original basis, the inner product is then diagonal:
                        $$
                        p(x,y) = sum_j=1^n b_j x_j y_j
                        $$

                        where $b_j>0$.







                        share|cite|improve this answer












                        share|cite|improve this answer



                        share|cite|improve this answer










                        answered 2 days ago









                        GEdgarGEdgar

                        62.9k267171




                        62.9k267171





















                            0












                            $begingroup$

                            I agree with SmileyCraft. In finite dimensional vector spaces, bilinear transformations, as linear transformations, can be written in terms of the values that they adopt in a given base:$$left langle x,y right rangle=sum_i,j=1^nx_iy_jleft langle e_i,e_j right rangle.$$
                            I believe you can arrive in this representation without difficult, proving then you suspicion.






                            share|cite|improve this answer








                            New contributor




                            Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                            Check out our Code of Conduct.






                            $endgroup$

















                              0












                              $begingroup$

                              I agree with SmileyCraft. In finite dimensional vector spaces, bilinear transformations, as linear transformations, can be written in terms of the values that they adopt in a given base:$$left langle x,y right rangle=sum_i,j=1^nx_iy_jleft langle e_i,e_j right rangle.$$
                              I believe you can arrive in this representation without difficult, proving then you suspicion.






                              share|cite|improve this answer








                              New contributor




                              Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                              Check out our Code of Conduct.






                              $endgroup$















                                0












                                0








                                0





                                $begingroup$

                                I agree with SmileyCraft. In finite dimensional vector spaces, bilinear transformations, as linear transformations, can be written in terms of the values that they adopt in a given base:$$left langle x,y right rangle=sum_i,j=1^nx_iy_jleft langle e_i,e_j right rangle.$$
                                I believe you can arrive in this representation without difficult, proving then you suspicion.






                                share|cite|improve this answer








                                New contributor




                                Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                                Check out our Code of Conduct.






                                $endgroup$



                                I agree with SmileyCraft. In finite dimensional vector spaces, bilinear transformations, as linear transformations, can be written in terms of the values that they adopt in a given base:$$left langle x,y right rangle=sum_i,j=1^nx_iy_jleft langle e_i,e_j right rangle.$$
                                I believe you can arrive in this representation without difficult, proving then you suspicion.







                                share|cite|improve this answer








                                New contributor




                                Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                                Check out our Code of Conduct.









                                share|cite|improve this answer



                                share|cite|improve this answer






                                New contributor




                                Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                                Check out our Code of Conduct.









                                answered 2 days ago









                                Jonathan HonórioJonathan Honório

                                113




                                113




                                New contributor




                                Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                                Check out our Code of Conduct.





                                New contributor





                                Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                                Check out our Code of Conduct.






                                Jonathan Honório is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                                Check out our Code of Conduct.





















                                    0












                                    $begingroup$

                                    It is well known (and easy to prove) that any two finite dimensional inner product spaces are isometrically isomorphic. Hence $ langle x, y rangle'$ is an inner product on $mathbb R^n$ iff there is a vector space isomorphism $T: mathbb R^n to mathbb R^n$ such that $langle x, y rangle' =langle Tx, Ty rangle$ for all $x,y$.






                                    share|cite|improve this answer









                                    $endgroup$

















                                      0












                                      $begingroup$

                                      It is well known (and easy to prove) that any two finite dimensional inner product spaces are isometrically isomorphic. Hence $ langle x, y rangle'$ is an inner product on $mathbb R^n$ iff there is a vector space isomorphism $T: mathbb R^n to mathbb R^n$ such that $langle x, y rangle' =langle Tx, Ty rangle$ for all $x,y$.






                                      share|cite|improve this answer









                                      $endgroup$















                                        0












                                        0








                                        0





                                        $begingroup$

                                        It is well known (and easy to prove) that any two finite dimensional inner product spaces are isometrically isomorphic. Hence $ langle x, y rangle'$ is an inner product on $mathbb R^n$ iff there is a vector space isomorphism $T: mathbb R^n to mathbb R^n$ such that $langle x, y rangle' =langle Tx, Ty rangle$ for all $x,y$.






                                        share|cite|improve this answer









                                        $endgroup$



                                        It is well known (and easy to prove) that any two finite dimensional inner product spaces are isometrically isomorphic. Hence $ langle x, y rangle'$ is an inner product on $mathbb R^n$ iff there is a vector space isomorphism $T: mathbb R^n to mathbb R^n$ such that $langle x, y rangle' =langle Tx, Ty rangle$ for all $x,y$.







                                        share|cite|improve this answer












                                        share|cite|improve this answer



                                        share|cite|improve this answer










                                        answered 2 days ago









                                        Kavi Rama MurthyKavi Rama Murthy

                                        66.3k42867




                                        66.3k42867





















                                            0












                                            $begingroup$

                                            In general, for any $ntimes n$ matrix $A=(a_i,j)_i,j=1,ldots,n$ the expression $sum_i,j=1^na_i,jx_iy_j$ defines a bilinear form, which will be symmetric if and only $A$ is. Giving a positive definite symmetric bilinear form is a more subtle condition that leads to inequalities for the coefficients of $A$ (and the matrices that satisfy the condition are naturally called positive definite). For $2times2$ symmetric matrices the positive definite condition is $a_1,1>0$, $a_2,2>0$ together with $a_1,1a_2,2-a_1,2^2>0$ (so $det(A)>0$). For a concrete example, the symmetric matrix
                                            $$
                                            A=pmatrix1&frac12\frac12&1
                                            quadtextgives an inner product with
                                            langle v,,wrangle = v_1w_1 +frac12(v_1w_2+v_2w_1) + v_2w_2,.
                                            $$



                                            In higher dimension the condition is more complicated, but in any case one does get many different inner products on $Bbb R^n$ in this way. They do turn out to be all equivalent in the sense that they give rise to the same structure theory, but they are not equal.






                                            share|cite|improve this answer











                                            $endgroup$

















                                              0












                                              $begingroup$

                                              In general, for any $ntimes n$ matrix $A=(a_i,j)_i,j=1,ldots,n$ the expression $sum_i,j=1^na_i,jx_iy_j$ defines a bilinear form, which will be symmetric if and only $A$ is. Giving a positive definite symmetric bilinear form is a more subtle condition that leads to inequalities for the coefficients of $A$ (and the matrices that satisfy the condition are naturally called positive definite). For $2times2$ symmetric matrices the positive definite condition is $a_1,1>0$, $a_2,2>0$ together with $a_1,1a_2,2-a_1,2^2>0$ (so $det(A)>0$). For a concrete example, the symmetric matrix
                                              $$
                                              A=pmatrix1&frac12\frac12&1
                                              quadtextgives an inner product with
                                              langle v,,wrangle = v_1w_1 +frac12(v_1w_2+v_2w_1) + v_2w_2,.
                                              $$



                                              In higher dimension the condition is more complicated, but in any case one does get many different inner products on $Bbb R^n$ in this way. They do turn out to be all equivalent in the sense that they give rise to the same structure theory, but they are not equal.






                                              share|cite|improve this answer











                                              $endgroup$















                                                0












                                                0








                                                0





                                                $begingroup$

                                                In general, for any $ntimes n$ matrix $A=(a_i,j)_i,j=1,ldots,n$ the expression $sum_i,j=1^na_i,jx_iy_j$ defines a bilinear form, which will be symmetric if and only $A$ is. Giving a positive definite symmetric bilinear form is a more subtle condition that leads to inequalities for the coefficients of $A$ (and the matrices that satisfy the condition are naturally called positive definite). For $2times2$ symmetric matrices the positive definite condition is $a_1,1>0$, $a_2,2>0$ together with $a_1,1a_2,2-a_1,2^2>0$ (so $det(A)>0$). For a concrete example, the symmetric matrix
                                                $$
                                                A=pmatrix1&frac12\frac12&1
                                                quadtextgives an inner product with
                                                langle v,,wrangle = v_1w_1 +frac12(v_1w_2+v_2w_1) + v_2w_2,.
                                                $$



                                                In higher dimension the condition is more complicated, but in any case one does get many different inner products on $Bbb R^n$ in this way. They do turn out to be all equivalent in the sense that they give rise to the same structure theory, but they are not equal.






                                                share|cite|improve this answer











                                                $endgroup$



                                                In general, for any $ntimes n$ matrix $A=(a_i,j)_i,j=1,ldots,n$ the expression $sum_i,j=1^na_i,jx_iy_j$ defines a bilinear form, which will be symmetric if and only $A$ is. Giving a positive definite symmetric bilinear form is a more subtle condition that leads to inequalities for the coefficients of $A$ (and the matrices that satisfy the condition are naturally called positive definite). For $2times2$ symmetric matrices the positive definite condition is $a_1,1>0$, $a_2,2>0$ together with $a_1,1a_2,2-a_1,2^2>0$ (so $det(A)>0$). For a concrete example, the symmetric matrix
                                                $$
                                                A=pmatrix1&frac12\frac12&1
                                                quadtextgives an inner product with
                                                langle v,,wrangle = v_1w_1 +frac12(v_1w_2+v_2w_1) + v_2w_2,.
                                                $$



                                                In higher dimension the condition is more complicated, but in any case one does get many different inner products on $Bbb R^n$ in this way. They do turn out to be all equivalent in the sense that they give rise to the same structure theory, but they are not equal.







                                                share|cite|improve this answer














                                                share|cite|improve this answer



                                                share|cite|improve this answer








                                                edited 9 hours ago

























                                                answered yesterday









                                                Marc van LeeuwenMarc van Leeuwen

                                                88.2k5111228




                                                88.2k5111228



























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