Line 41: Line 41:
 
----
 
----
 
==Materials Cover==
 
==Materials Cover==
*1. Probability Models (Ch.1)
+
* Probability Models (Ch.1)
*2. Axioms of Probability, counting, conditional probability, independence(Ch.2)
+
* Axioms of Probability, counting, conditional probability, independence(Ch.2)
*3. Random variables, Expected value and moments, probability mass function (Ch.3)
+
* Random variables, Expected value and moments, probability mass function (Ch.3)
*4. Cumulative distribution function, functions of a random variable (Ch.4)
+
* Cumulative distribution function, functions of a random variable (Ch.4)
*5. Two random variables(r.v.), joint cdf of 2 r.v., independence of 2 r.v., conditional expectation (Ch.5)
+
* Two random variables(r.v.), joint cdf of 2 r.v., independence of 2 r.v., conditional expectation (Ch.5)
*6. Vector r.v., jointly Gaussian r.v, estimation of r.v. (Ch.6)
+
* Vector r.v., jointly Gaussian r.v, estimation of r.v. (Ch.6)
*7. Definition of Random Processes(r.p.), Poison r.p., Random Walk (Ch.9)
+
* Definition of Random Processes(r.p.), Poison r.p., Random Walk (Ch.9)
*8. Power spectral density, response of linear systems to random signals (Ch.10)
+
* Power spectral density, response of linear systems to random signals (Ch.10)
 
----
 
----
 
== Relevant Resources  ==
 
== Relevant Resources  ==

Revision as of 08:06, 5 January 2013


Rhea Section for ECE302, Professor Boutin, Spring 2013

MWF 12:30- 1:20pm in MSEE B012

Message Area:

Course Information

  • Instructor: Prof. Mimi
  • Teaching Assistant: Wei-Kang Hsu
    • Email: hsu59 at purdue dot you know what
    • Office hours: T 1:30-3:30 / R 1:00-3:00 pm EE209
  • Schedule
  • Course Syllabus
  • Important Dates:
    • Test 1
    • Test 2
    • Final, TBD

Textbook

Probability, Statistics, and Random Processes for Electrical Engineering, 3rd Edition, by Alberto Leon-Garcia, Pearson Education, Inc., 2008, ISBN 0-13-601641-3


Homework


Lecture Blog

Lecture 1, 2, 3


Materials Cover

  • Probability Models (Ch.1)
  • Axioms of Probability, counting, conditional probability, independence(Ch.2)
  • Random variables, Expected value and moments, probability mass function (Ch.3)
  • Cumulative distribution function, functions of a random variable (Ch.4)
  • Two random variables(r.v.), joint cdf of 2 r.v., independence of 2 r.v., conditional expectation (Ch.5)
  • Vector r.v., jointly Gaussian r.v, estimation of r.v. (Ch.6)
  • Definition of Random Processes(r.p.), Poison r.p., Random Walk (Ch.9)
  • Power spectral density, response of linear systems to random signals (Ch.10)

Relevant Resources


Back to List of Course Wikis

Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva