1. "Adaptive Filter Theory," Simon Haykin, 3rd Edition, Prentice Hall, 1996.
2. "Statistical Signal Processing and Modeling," M. H. Hayes, Wiley, 1996.
 

Course Objective:

    This course focuses on problems, algorithms, and solutions for processing signals in a manner that is responsive to a changing environment. Adaptive signal processing systems are developed which take advantage of the statistical properties of the received signals. The course analyzes the performance of adaptive filters and considers the application of the theory to a variety of practical problems such as interference and echo cancellation, signal and system identification, and channel equalization. The class is designed as an advanced statistical signal processing course in which students will build a strong foundation in approaching problems in such diverse areas as acoustic, sonar, radar, geophysical, biomedical, and communications signal processing. Understanding of the theoretical foundations of adaptive signal processing theory will be achieved through a combination of theoretical and computer-based homework assignments.

Grading:

  They will be given 5 homeworks, one class project, and a final exam:
· 5 sets of homework problems (20%)
· Class Project (30 %)
· Final Exam (50%)