Advanced Filter Design for Communications and Signal Processing Systems

This project is directed by Prof. Brian Evans.

Goal: Automate the optimization analog and digital filters
Impact: Designers can design and implement filters for communications and signal processing systems.
Requirements
- EE313 Linear Systems and Signals
- EE351M Digital Signal Processing or EE345S Real-Time Digital Signal Processing
- Experience with using and programming Matlab.
What you will learn: algebra describing filter design, applications that use filters, and one of the following programming languages: Tcl/Tk, Java, or Mathematica.
Resources
- Morris Smith, "An Improved PLL Design Method without w_n and l", Motorola Application Note 1253
Undergraduate Projects:
- Project #1 (OPEN): work with a graduate student to extend a set of analog IIR filter design packages in Mathematica to digital new exotic IIR filters. You will develop the equations in Mathematica. Then, Mathematica will generate the corresponding Matlab code, and finally, Matlab will perform the numerical optimization. See Filter Optimization Software.
- Project #2 (Rezaul Hasan, Spring 1999; Justin Burk, Fall 1998): develop closed-form design equations to optimize the choice of macrocomponents (resistors and either capacitors or inductors) in the phase-locked loop filter. The topology of the filter is already fixed. This is closed-form bottom-up design, i.e., no numerical optimization is involved.
Graduate Projects:
- Project #3 (Niranjan Damera-Venkata): Extend the formulation of analog filter design problem implemented in Mathematica/Matlab to digital filter design. The formulation allows the simultaneous optimization of multiple filter criteria, whereas the classical design algorithms only optimize for one.

Last updated 05/18/00.