Function notation and inner product

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The discussion focuses on understanding a homework problem involving function notation and inner products. The task is to show that the function d(x, y) = x^T A y, where A is a matrix expressed as A = B^T B, qualifies as a vector dot product. Participants clarify that if A is defined this way, the function d can be interpreted as satisfying the definition of an inner product. Additionally, they emphasize the importance of matrix algebra and the properties of matrix multiplication in deriving the solution. Overall, the conversation aims to demystify the function notation and guide towards a clearer understanding of the inner product concept.
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Homework Statement


I have this problem, but I'm not familiar with the function notation that the professor is using. Can anyone tell me what is actually being asked? I understand everything up to the part that is in bold, but after that, I am lost.

Let A be a nxn matrix of real numbers, such that A can be written as a product of
another matrix B and its transpose (e.g. A=BT*B). Assuming that B is
nonsingular, show that the function d:RnxRn->R, d(x,y)=xTAy is a vector dot
product.

Some of the formating was lost so Rn is shown as R^n and xT is x transpose.
 
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x and y are in Rn, so they are n by 1 matrices so xTAy is (1 by n)(n by n)(n by 1) = 1 by 1 or scalar. If you put in A = BTB I think you will see that it is a dot product of two vectors if you look at it right.
 
I would interpret the problem as "Show that d satisfies the definition of an inner product". This is really easy if you know the definition and you're comfortable with matrix algebra (stuff like (XY)^T=Y^T X^T).

If you're only supposed to show that x^TAy is a dot product of two vectors, the complete solution would be x^TAy=x^T(Ay), because Ay is a column vector. (You know that the definition of matrix multiplication implies that u^Tv=u_1v_1+\dots+u_nv_n when u and v are column matrices, right?)
 
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