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| − | In Lecture 30, | + | In Lecture 30, we defined various 1D and 2D signals (mean, variance, autocorrelation, autocovariance) that can be used to describe the statistical properties of a Random Process. We also introduced the cross-correlation and the cross-covariance of two Random Processes. |
| − | + | ||
==Action items for students (to be completed before next lecture)== | ==Action items for students (to be completed before next lecture)== | ||
| + | *Solve the following problems in the textbook (you will hand in your solution as part of homework 6) | ||
| + | ::9.2, 9.3, 9.4, 9.5 | ||
Previous: [[Lecture29_blog_ECE302S13_Boutin|Lecture 29]] | Previous: [[Lecture29_blog_ECE302S13_Boutin|Lecture 29]] | ||
Latest revision as of 11:15, 25 March 2013
Lecture 30 Blog, ECE302 Spring 2013, Prof. Boutin
Monday March 25, 2013 (Week 12) - See Course Outline.
(Other blogs 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30)
In Lecture 30, we defined various 1D and 2D signals (mean, variance, autocorrelation, autocovariance) that can be used to describe the statistical properties of a Random Process. We also introduced the cross-correlation and the cross-covariance of two Random Processes.
Action items for students (to be completed before next lecture)
- Solve the following problems in the textbook (you will hand in your solution as part of homework 6)
- 9.2, 9.3, 9.4, 9.5
Previous: Lecture 29
Next: Lecture 31
