Matrix multiplication vs dot product

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SUMMARY

The discussion clarifies the distinction between matrix multiplication and the dot product. Matrix multiplication of two matrices A and B, represented as AB, results in a new matrix where each element is computed as the sum of products of corresponding elements. The dot product, however, is typically defined for vectors and results in a scalar value. The correct formulation for matrix multiplication is confirmed as AB = \begin{pmatrix} ae + bg & af + bh \\ ce + dg & cf + dh \end{pmatrix}, while the dot product of matrices is not conventionally defined.

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jabers
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What is the difference between matrix multiplication and the dot product of two matrices? Is there a difference?

If,

A =<br /> \begin{pmatrix}<br /> a &amp; b \\<br /> c &amp; d<br /> \end{pmatrix}

and

B =<br /> \begin{pmatrix}<br /> e &amp; f \\<br /> g &amp; h<br /> \end{pmatrix}

then does
<br /> {\mathbf{A} \cdot \mathbf{B}} =<br /> \begin{pmatrix}<br /> ae &amp; bf \\<br /> cg &amp; dh<br /> \end{pmatrix}

and

AB = <br /> \begin{pmatrix}<br /> ae + bg &amp; af + bh \\<br /> ce + dg &amp; cf + dh<br /> \end{pmatrix}

? Is this correct? Any help would be appreciated.
 
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Don't confuse dot product of matrix with vectors. The second product is correct.
 
so,

{\mathbf{A} \cdot \mathbf{B}} = AB = <br /> \begin{pmatrix}<br /> ae + bg &amp; af + bh \\<br /> ce + dg &amp; cf + dh<br /> \end{pmatrix}

With matrices the dot product means that you need to multiply the matrices? Correct?
 
Usually the "dot product" of two matrices is not defined. I think a "dot product" should output a real (or complex) number. So one definition of A\bulletB is ae + bf + cg + df. This is thinking of A, B as elements of R^4. If we want our dot product to be a bi-linear map into R this is how we need to define it (up to multiplication by a constant).
 
You should view AB as a collection of dot products ie.
ab11 (top left of AB) can be described as the dot product of

\begin{pmatrix}
a & b
\end{pmatrix}dot\begin{pmatrix}
e \\
g
\end{pmatrix}

and so on for the rest of the positions.
 

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