Adaptive and Array Signal Processing - 2017.2

 

Objectives:        

                The objective of the course is to introduce the fundamentals of adaptive and array signal processing using linear algebra, optimisation and intuition. The main focus is on filtering and estimation techniques and beamforming and direction finding methods and their application in several areas of electrical engineering (communications, control, time-series analysis, sensing, defence systems, etc).

 

Syllabus:             

1.   Mathematical fundamentals

2.   Adaptive signal processing and applications

3.  Optimal filters

4.  The Steepest Descent Method

5.  LMS Type Algorithms

6.  LS Type Algorithms

7.  Algorithms for Large Systems

8.  Sensor Array Processing

9.  Beamforming Techniques

10.  Direction finding

 

Assessment:     

                The assessment is based on lists of tutorial questions (T), an exam paper (E) and a project (P) . The final grade is given by FG = (P + E+ T)/3.

 

Tutorial questions:

List 1

List 2

List 3

List 4

List 5

List 6

List 7

List 8

 

Matlab codes:

System identification with LMS - code

Distributed LMS using diffusion - code

                                               Echo cancellation - code

                                               MVDR beamforming - code

                                               Direction finding - code

 

Grades:

                                               Grades

References:

1.   HAYKIN, S.,  Adaptive Filter Theory. 4a Ed. Prentice Hall, 2002. 

2.   VAN TREES, H. L., Optimum Array Processing. Wiley, 2002.

3.   DINIZ, P. S. R., Adaptive Filtering: Algorithms and Practical Implementation, 2nd Edition, Kluwer, 2002.

4.   SAYED, A. H., Adaptive Filters. Wiley, 2008.

5.   JOHNSON, D.H., DUDGEON, D. E., Array Signal Processing. Prentice Hall, 1993.