EEE-350 Random Signal Analysis
ASU Catalog Description:
Probablistic and statistical analysis as applied
to electrical signals and systems. Prerequisite: EEE 303 or MAE 317.
Course Links
- EEE-350 Syllabus (Word 97 document)
- Textbook (R.H. Williams, Electrical Engineering Probability, 1991) Corrections
- change equal signs ("=") in Equations (1.22) and (1.23) to
approximately signs ("
") on p. 15
- change subscript "j" to an "i" Eq. (2.13a) on p. 48
- change two subscript "1"s to "j"s Eq. (2.32) on p. 56
- missing "P" on last equation (Example 2.13) on p. 61
- limits on last term of Eq. (2.40) on p. 62 should be "i=1" to "n-1"
- change two "2"s to "n"s in equation above Eq. (3.50) on p. 91
- remove extra equal sign in Eq. (3.69) on p. 103
- the pdf equation in Exercise 3.10 (p. 127) should be fX(x)=
e
-
x
- change µX to µY in fourth equation on p. 149
- remove superscript "2" in the fifth equation on page 154, should be E[UV]
- two missing parentheses in Eq. (4.32) on p. 155
- numerator in the fifth equation on p. 195 should be (N - n)!
- missing coefficient "b" on right-hand-side of the last equation on bottom of p. 199
- two corrections to top of p. 313: (1) limit of k=0 in first equation, and (2)
just below Eq. (8.72), should be kM=N-1...
- Homework Assignments
- Homework #1 (given in class); Due Wednesday, September 2
- Homework #2 (given in class); Due Friday, September 11
- Homework #3 (given in class); Due Monday, Sept. 21
- Homework #4 (given in class); Due Wednesday, October 7
- Homework #5 (given in class); Due Wednesday, October 21
- Homework #6 (given in class); Due Monday, November 2
- Homework #7 (given in class); Due Wednesday, November 18
- Homework #8 (given in class); Due Wednesday, November 25
- Homework #9 (given in class); Due Monday, December 7
- EXCEL Help from the
ECE 100 Course Materials. Some example Excel worksheets can be
found
here or here.
- Handouts
- PSpice
- The most recent PSpice version 8 can be downloaded from
OrCAD (formerly MicroSim).
- I have put a copies of older versions here for those with
older hardware and software. These are IBM-PC compatible DOS-based
versions that only require a coprocessor and 1 or 2 MB of
extended memory. They will run under Microsoft Windows.
Links to Further Understanding
Monte Carlo
Introduction to Monte Carlo Methods by the Computational Science Education
Project
This includes a nice case study on particle transport. There are several
sites to choose from:
Oak Ridge National Laboratory
(ORNL)
Vanderbilt
University
Colorado State
University
Similar Courses at Other Universities:
Last updated: December 9, 1998
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