ECE 30200 - Probabilistic Methods in Electrical and Computer EngineeringLecture Hours: 3 Credits: 3 Professional Attributes
Normally Offered: Each Fall, Spring, Summer
(MA 26200 or MA 26600 or MA 36600) and ECE 30100 [may be taken concurrently].
An introductory treatment of probability theory including distribution and density functions, moments and random variables. Applications of normal and exponential distributions. Estimation of means, variances. Correlation and spectral density functions. Random processes and response of linear systems to random inputs.
This course is intended to introduce the concepts of probability and random processes and to discuss their application to engineering problems. Particular emphasis is given to application of these methods to systems analysis. It is also intended that this course should be a suitable prerequisite for EE 60000.
- Probability, Statistics, and Random Processes for Electrical Engineering, 3rd Edition, Alberto Leon-Garcia, Prentice-Hall, 2008, ISBN No. 9780131471221.
- MatLab: Student Version, Current Edition, The MathWorks, Inc..
Learning Objectives:A student who successfully fulfills the course requirements will have demonstrated:
- an ability to solve simple probability problems in electrical and computer engineering applications. [a,b,e]
- an ability to model complex families of signals by means of random processes. [a,b,e,k]
|1||Introduction, Definitions; Set Operations; Probability Introduced|
|2||Probability Axioms; Math Model; Joint & Conditional Probability|
|3||Independence, Bernoulli Trials; Random Variables and Distribution Functions; Density Functions|
|4||Gaussian Random Variables; Other Density Functions; Conditional Probability|
|5||Expectation; Moments; Transformations of a Random Variables|
|6||Review; Test; Vector Random Variables|
|7||Joint Distribution & Density; Conditional Distributions, Independence; Sums of Random Variables|
|8||Random Processes; Correlation Functions|
|9||Process Measurements; Gaussian, Poisson Processes|
|10||Review; Test; Spectral Density|
|11||Relationship to Correlation Function; Some Noise Definitions; Linear System Fundamentals|
|12||Random Signals & Linear Systems; System Evaluation Using Random Noise; Spectral Character of System Response|
|13||Noise Bandwidth; Modeling Noise Sources; Matched Filters|
|14||Wiener Filters; Review; Test|
|15||Noise is AM; Noise is FM; Noise Feedback Systems|