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Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.
Covers Markov processes, transition densities, and distribution conditional on information, discussing classification of states and stationary distributions.
Introduces mathematical tools for communication systems and data science, focusing on stochastic processes and preparing students for advanced courses.
