Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.
Explores orthogonality, vector norms, and subspaces in Euclidean space, including determining orthogonal complements and properties of subspaces and matrices.
Explores communicating classes in Markov chains, distinguishing between transient and recurrent classes, and delves into the properties of these classes.
