ECE 630 Class Notes

Lecture Notes

In the table below, for each class you find the topic of the lecture; the topics are linked to a set of slides covered in the class. Slides are not available for all lectures.
The final column may include links to other resources from the lecture, e.g., MATLAB files.

Date Topic Other Resources
Jan. 26 Introduction Textbook: chapter 1
Feb. 2 Mathematical Prerequisites:
Working with Gaussian random variables and vectors;
Introduction to random processes
Textbook: Appendix A and section 3.1
Feb. 9 Mathematical Prerequisites:
Random processes: stationarity; white Gaussian noise; filtering of Random processes.
Textbook: Appendix A and section 3.1
Feb. 16 Mathematical Prerequisites:
Random processes: power spectral density;
Introduction to linear vector spaces: norms and inner products, Hilbert spaces, subspaces, projection theorem.
Textbook: Appendix A and section 3.3
Feb. 23 Mathematical Prerequisites:
Introduction to linear vector spaces: representation in terms of bases, orthonormal bases, Gram-Schmidt procedure; representation of random processes: Karhunen-Loeve expansion.
Textbook: Appendix A and section 3.3
March 2 Optimum Receiver Principles:
Introduction: computing the probability of error for a simple communication system.
Textbook: sections 3.4 and 3.5
March 9 Optimum Receiver Principles:
Statistical Hypothesis Testing.
Textbook: sections 3.4 and 3.5
March 23 Optimum Receiver Principles:
Optimal receiver front-end; matched filter receiver.
Textbook: sections 3.4 and 3.5
April 6 Optimum Receiver Principles:
suboptimal receiver frontends.
Introduction to M-ary signal sets.
Textbook: sections 3.4 and 3.5
April 13 Optimum Receiver Principles: Computing the probability of error for M-ary signal sets; union bound, nearest neighbor approximation, energy efficiency. Textbook: sections 3.5 and 3.6

Complete Set of Slides