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Matrices are good objects to store connections between dimensions/entities. However, matrix computation is often time consuming and sometimes wasteful if matrix is too sparse. Also thinking about the fact the inverse of the matrix is $O^n$. I am trying to understand that why is matrix used to store information in the perceptron. Wouldn't a functional form be more compact instead of a big sparse matrix to replace a perceptron layer in the neural networks?

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