By actively participating in this Week, you will achieve different Intended Learning Outcomes:

  1. classify stochastic processes as continuous or discrete, and as monodimensional or multidimensional, and describe their characterization in terms of probabilities and statistical moments (mean, standard deviation, cross-correlation);
  2. analyze the properties of stationary and ergodic processes and apply the concept of ergodicity to extract statistical information;
  3. explain how the power spectrum characterizes stochastic processes, relate it to autocorrelation, and evaluate its significance in practical scenarios;
  4. determine the relationship between the input and output of stochastic processes in a Linear Time-Invariant (LTI) system;
  5. assess the relevance of stochastic processes, particularly Gaussian processes, and illustrate their application in real-world contexts.