For noiseless data, we can define two $(N-L)\times L$ matrices, $Y_1$ and $Y_2$, defined by \begin{align} [Y_2] &= \begin{bmatrix} x(1) & x(2) &\cdots& x(L)\\ x(2) & x(3) &\cdots& x(L+1)\\ \vdots & \vdots & \vdots & \vdots\\ x(N-L-1)& x(N-L)&\cdots&x(N-1) \end{bmatrix}_{(N-L)\times L}\\ [Y_1] &=\begin{bmatrix} x(0) & x(1) &\cdots& x(L-1)\\ x(1) & x(2) &\cdots& x(L)\\ \vdots & \vdots & \vdots & \vdots\\ x(N-L-1)& x(N-L)&\cdots&x(N-2) \end{bmatrix}_{(N-L)XL.} \end{align}
I look at this and read it as "two N minus L times L matrices".
I don't have a mathematics background but I need to interpret this paper for an ongoing research project.
Where do you recommend I begin my search (any books, related terms or mathematical concepts I should learn about would be very appreciated)!
My hope is to implement the formulations on page 3 in Matlab.
This is the math-filled, Signal Processing paper by the way: https://sci-hub.tw/10.1109/74.370583 (trying to extract frequencies and amplitudes of a signal after removing noise that came from the instrument/receiver).