[tarquilu]

Hello,

I'm trying to compute the pseudo-inverse of matrix X with dimensions [d+1 x N], where N is the number of data points. Lecture 3, slide 16 shows that the dimensions "shrink" when multiplying (X^T)X from [d+1 x N][N x d+1] to [d+1 x d+1].

Although LFD on page 86 states that "In practice, (X^T)T is invertible in most of the cases since N is often much bigger than d+1, so there will likely be d+1 linearly independent vectors xn," I don't know if this statement is meant to explain the reason for the simplification to [d+1 x d+1] dimensions. Moreover, when creating X and computing (X^T)T, I obtain a matrix with [N x N] dimensions, not [d+1 x d+1] dimensions.

Could some please clarify this for me? Thank you.