EECS 225A Spring 2008

schedule resources

catalog description


225A.  Digital Signal Processing. (3)   Three hours of lecture per week. Prerequisites: 123 and 126 or solid background in stochastic processes. Advanced techniques in signal processing. Stochastic signal processing, parametric statistical signal models, and adaptive filtering. Application to spectral estimation, speech and audio coding, adaptive equalization, noise cancellation, echo cancellation, and linear prediction.



Class: 293 Cory Hall, Tuesdays and Thursdays 11-12:30

Instructor: Michael Gastpar

Office Hours: Tuesdays, 12:40-1:30; Wednesday, 11-12



Monson H. Hayes, Statistical Digital Signal Processing and Modeling, Wiley, 1996 (ISBN 0471594318) [homepage]


In addition, various resources (Web and handouts) will be used to supplement the text.

course topics


With signal processing becoming ubiquitous in today's computer literate world, a large number of application areas are growing in importance, both in industry and in the research community, such as seismic signal processing, speech data processing, medical image processing, radar signal processing, and sensor array processing. These problems have many different aspects, and a corresponding number of different solutions have been explored.


Signal Models (5 lectures)


Signal Representation and Approximation (6 lectures)


Signals, Systems, Noise (19 lectures)

  • Estimation Theory (Wiener, Kalman, Adaptive, Neural networks...)
  • Detection Theory (Neyman-Pearson, etc)
  • System Identification


student responsibilities


First and foremost, please check the class web pages frequently.

Students are also reminded of the Departmental Policy on Academic Dishonesty and are also urged to also read and abide by the professional ethics represented in the IEEE Code of Ethics. Especially relevant in the latter are the two guidelines:




The components of the course will be weighted as follows in the final grade. The final grades will be set by matching a curve to the final course averages.







General Class Participation

In-class Midterm


80 minute open-book exam

Takehome Midterm







In small groups (1-3 students), you will select a subarea of the class and explore the related literature. You will select around 5 papers and discuss and extend their contributions in a short report.


This web page is mostly drawn from the web page of Prof. D. G. Messerschmitt (Spring 2005).