Lectures related to Untitled | EPFL Graph Search

Explores the properties and applications of Cayley graphs in group theory and network analysis.

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.

Explores different types of noise in devices and circuits, including interference noise, inherent noise, and random signals.

Covers the concept of sparse regression and the use of Gaussian additive noise in the context of MAP estimator and regularization.

Explains the proof of the ergodic theorem and the concept of positive-recurrence in Markov chains.

Explores the coupling of Markov chains and the proof of the ergodic theorem, emphasizing distribution convergence and chain properties.

Discusses approximation by smooth functions and the convergence of function sequences in normed vector spaces.

Explores the physics of electrophoresis for protein characterization, covering Native Gel, SDS-PAGE, and 2D Gel.