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==Materials Cover==
 
==Materials Cover==
*1. Probability Models (Ch.1)
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* Probability Models (Ch.1)
*2. Axioms of Probability, counting, conditional probability, independence(Ch.2)
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* 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)
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* 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)
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* 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)
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* 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)
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* Power spectral density, response of linear systems to random signals (Ch.10)
 
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== Relevant Resources  ==
 
== Relevant Resources  ==

Revision as of 07:06, 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

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Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

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