Probability and Statistics for Signals and Networks
I am responsible for this 40-hour lecture course under the Master program in Intelligent and Communicating Systems.
Course Content:
- Discrete and continuous probability distributions.
- Law simulations and experiment modeling.
- Statistical parameters (mean, variance, skewness, kurtosis), estimators.
- Conditional probabilities.
- Probabilistic algorithms: Las Vegas, Monte Carlo, Markov Chains.
- Hidden Markov Models, Viterbi algorithm.
- Queueing theory and network simulation.
Location:
Room A478, CYU.