#### Spring 2016 textbook list

The Spring 2016 ECE textbook list is available online for students.

#### Current Prerequisites & Course Offering

For current prerequisites for a particular course, and to view course offerings for a particular semester, see the Virginia Tech Course Timetables.

### ECE 5605 Stochastic Signals and Systems (3C)

5605: Egnineering applications of probability theory, random variables and random processes. Topics include: Gaussian and non-Gaussian random variables, correlation and stationarity of random processes. Time and frequency response of linear systems to random inputs using both classical transform and modern state space techiques.

What is the reason for this course?

The analysis of system response to stochastic signals and noise is fundamental for the understanding of advanced system analysis and synthesis.

Typically offered: Fall. Program Area: Communications.

*Prerequisites: STAT 4714*.

Why are these prerequisites or corequisites required?

A basic course in probability and statistics such as STAT 4714 provides the necessary background in probability theory and random variables that the beginning graduate student should have for ECPE 5605, which is an advanced treatment of probability and stochastic processes. ECPE 5606 is the second course in the sequence, which requires ECPE 5605 as prerequisite.

### Department Syllabus Information:

**Major Measurable Learning Objectives:**

- analyze the response of linear systems to both deterministic and random input processes.
- design system structures to meet desired performance objectives for both continuous and discrete time applications.

Course Topics | |
---|---|

Topic | Percentage |

Probability space, sigma fields; probability axioms, conditional probability, random variables | 10% |

Probability distributions and density functions; independent and conditional random variables | 10% |

Two or more random variables; functions of random variables expectations, moments; characteristic functions | 10% |

Correlation; covariance; parameter estimation; multivariate normal variables random sequences and stochastic convergence; Central Limit Theorem | 10% |

Stochastic processes; Gaussian, exponential, random phase sinusoids in continuous and discrete time | 20% |

Strict and wide-sense stationary processes; correlation functions and expected values | 20% |

Linear transformations on random variables; linear system response to stochastic processes; ergodicity; power spectral density. | 20% |