Probability Models & Stochastic Processes

Credits: 3

Prerequisites: ECE 300/ECE 310, MA 224

Topics in probability, random variables and stochastic processes applied to the fields of electrical and computer engineering. Probability, events, random variables, expectation, moments, characteristic functions, conditional probability and expectation. Functions of random variables, random vectors, Gausian random vectors, Poisson points. Bounding and limit theorems. Relations among important distributions and probability models.Stochastic processes: stationarity, ergodicity, Brownian motion, Markov processes. Deterministic systems with stochastic inputs, correlation and power spectral density, ARMA models. Hilbert space and applications: orthogonality principle, discrete Wiener and Kalman filters, linear prediction, lattice filters.

Course Overview & Topics

• key concepts, software, etc

Professors

• John Doe
  • specific advice
  • workload, assessments, teaching style
  • professor specific advice

Resources

• TBD