ECE 661 Statistical Signal Processing

University of DaytonDepartment of Electrical and Computer Engineeringp p g g

Spring Term, 2010

Dr. John Malas

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1.0 Introduction

1 1 S ll b1.1 Syllabus1.2 Book and References 1.3 Course Approach1.4 Modeling and Analysis Using MATLAB1.5 Course Projects 1.6 Homework1.6 Homework1.7 Survey of Math and Statistics background

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1.1 Syllabus

Course Catalogue Description• Course Catalogue Description

• Instructor Contact Information

• Location and Time

• Calendar Dates

• Office Hours

• Prerequisites - Random processes, DSPq p

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1.2 Book and References

Class Web Page: johnmalas com• Class Web Page: johnmalas.com

•Text: Discrete Random Signals and Statistical Signal Processing, By Charles W. Therrien, Prentice Hall Signal Processing SeriesCharles W. Therrien, Prentice Hall Signal Processing Series

• References - Class Notes for ECE 661, Statistical Signal Processing, Professor Krishna P lPasala- Statistical Digital Signal Processing & Modeling, M. H. Hayes, Wiley, 1996.- Modern Spectral Estimation, Steven M.. Kay, Prentice Hall, 1988- Fundamentals of Radar Signal Processing , M. A. Richards, McGraw-Hill, f g g , , ,2005Probability, Random Processes and Stochastic Processes, PapoulisMatrix Computations, G. Golub, C. Van Loan 1996P b bilit & R d P f El t i l E i i Alb t L

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Probability & Random Processes for Electrical Engineering, Alberto Leon-Garcia, 1994

1.3 Course Approach

• Course Content1. Random Vectors2. Random Processes - Review3. Second Moment Analysis & the Covariance Matrix4 Linear Transformations4. Linear Transformations 5. Estimation6. Optimal Filtering7. Linear Prediction 8. Linear Models9. Spectrum Estimation

• Course Gradingg

7 MATLAB Projects (10% each) 70% (70 points)Homework (weekly) 15% (15 points)I Fi l E 15% (15 i )

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I Final Exam 15% (15 points)A: 90-100 Points, B: 80-89 points, C: 70-79 points

1.3 Course Approach (cont.)

• Teaching Philosophy

- Theory + applied, journey not an end, Sequential series

- Main ideas and techniques are importantMain ideas and techniques are important

•Summary Sheets for each chapter

ECE 661 i fi t/ d i i d bl- ECE 661 is first/second in series and enables many other areas where application is more concrete

Assumption: Interested students at advanced graduate- Assumption: Interested students at advanced graduate levels are motivated by noble intentions

• Honor System6

Honor System

1.4 Modeling and Analysis Using MATLAB

MATLAB based modeling and analysis of course• MATLAB based modeling and analysis of course techniques can become a repository of tools for future work

• Think of this as a means to add some capability to your set• Think of this as a means to add some capability to your set of professional analysis tools

• Models will be mainly radar centered in context but canModels will be mainly radar centered in context but can be applied to other applications

• Radar based modeling is physics based with stochastic g p yelements

• The modeling presentations will feed into projects in

7follow-on course in Adaptive Filtering.

1.5 Course Projects

• Projects Focus on Main Ideas of Course • Theory of stochastic processes, estimation, and optimal filtering

• Signal Analysis – spectral estimation, signal modeling

• Signal Filtering – array processing

• Projects1. Estimating Correlation & Covariance Matrix (due: 4 Feb)Second Moment Analysis (18 Feb)The Matched Filter (4 March)E ti ti i MLE d MAP (18 M h)Estimation using MLE and MAP (18 March)Optimal Filtering (1 April)Linear Modeling (15 April)Spectrum Estimation (29 April)

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Spectrum Estimation (29 April)

• Two week intervals

1.6 Homework

• Assigned on Thursday when appropriate – due in two weeks

• Worth 15% of Grade

• Mostly using Matlab – with some analytical problems

• Idea should be to spend a few minutes pushing on the p p gsolution – 15 minutes implementing the solution

• Focused on main ideas and will fill in where projects do not address directly

• Solutions for the problems will be posted on web page f i d i

9after assignments are turned in

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1.7 Survey of Math and Statistics background

• Objective of Survey

• No names attached

• Varying range of exposure to topics• Varying range of exposure to topics

• No & Limited versus Substantial

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