Basic Information
The Course Introduces Central Models in Electrical Engineering Of Stochastic Nature, Extends The Toolbox For Probabilistic Analysis And Exposes Algorithmic Probabilistic Tools. Topics# Basics of Markovian Queueing Theory, Effective Statistical Bandwidth, Load Balancing, Phase Locked Loop in White Noise, Shot Noise. Analytical Tools# Reversible Chains, Perron-frobenius Theorem, Rates to Ergodicity, The Coupling Method, Cramer's Theorem On Large Deviations, Lyapunov Functions in Stability Analysis. Algorithmic Tools# Maekov Chain Monte Carlo, Approximate Counting, Exact Simulation, Simulated Annealing. Learning Outcomes# The Student Will Learn About Central Stochastic Models and Gain Control Over Relevant Analytic and Algorithmic Tools.
Faculty: Electrical and Computer Engineering
|Graduate Studies
Pre-required courses
Course with no extra credit
94334 - Simulation-modeling and Analysis 95334 - Simulation - Modeling and Analysis