Previous Year's Lecture Notes: 

New Random Variables and Random Processes Class Notes

Lecture #1: Introduction to Detection and Estimation 

Lecture #2&3: Review of Random Variables and Random Processes

Lecture #4&5: Bayes Criterion

Lecture # 6: Neyman-Pearson Criterion

Lecture # 7: Receiver Operating Characteristics

Lecture # 8: Multiple Hypothesis Testing

Lecture # 9-12: Matched Filters

Lecture # 13-15: Introduction to estimation, random parameter estimation

Lecture # 16: Multiple random parameter estimation

Lecture: MAP Estimation for Random Parameter An Example

Lecture: Real Parameter Estimation

Lecture: CRLB for Vector Parameter_1

Lecture: CRLB for Vector Parameter_2

Lecture: General MVU estimator

All Whiteboard Notes

The Solution to End_Term Examination

Previous Year's Assignments:

1.  MATLAB Programming Assignment #1

2. MATLAB Programming Assignment #2

Previous Year's Evaluation:

1.  Quiz: Question_Paper  Solution

2. Mid_Term: Question_Paper  Solution

3. End_Term: Question_Paper  Solution

Evaluation and Other Requirements:

Prerequisites

-Random Variables and Stochastic Processes

-Linear Algebra, Matrices etc.

-Comfort at Mathematics. 

Two Assignments (problem set and programming set): 10% each, i.e., total 20%.

Four Evaluations (Quiz-1 (10%), Quiz-2 (10%), Mid-Term (20%), and End-Term (40%))

Recommended Books:

• • • Harry L. Van Trees, Detection, Estimation, and Modulation Theory. Part I, Wiley, 1968, ISBN-13: 978-0471899556.

    • Mourad Barkat,  Signal Detection and Estimation, 2e, Artech House, 2005, ISBN-10: 1-58053-070-2.

• • • Steven M. Kay, Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory, Prentice-Hall, 1993, ISBN-13: 978-0133457117 2.

    • Steven M. Kay, Fundamentals of Statistical Signal Processing, Volume II: Detection Theory, Prentice-Hall, 1998, ISBN-13: 978-0135041352.