|
|
|
[Contents] | [Index] |
Collaborator: J. Tseng, V. Schulz
Cooperation with: K.L. Teo (Hong Kong Polytechnic University, China), A. Cantoni (University of Western Australia, Perth), Z. Zang (Australian Telecommunications Research Institute, Perth), R.H.W. Hoppe, S.I. Petrova (Universität Augsburg)
Description:
This project is concerned with the application of optimization techniques to signal processing where the design of a filter can often be cast as a constrained optimization problem. The envelope-constrained (EC) filtering problem is a specific constrained optimization problem. In this problem, we are concerned with the design of a linear time-invariant filter with impulse response u(t) to process a given input signal s(t) which is corrupted by an additive random noise. The objective is to design a filter such that its squared L2 norm is minimized, whereas its noiseless output response with respect to a specified input signal stays within a prescribed pulse-shape envelope defined by the lower and upper boundaries. Traditionally, problems of this type were often handled by minimizing the weighted least-mean-square (LMS) difference between the output of the filter and a desired pulse shape. By using output envelope constraints, the EC filtering approach, however, is more relevant than the LMS approach in a variety of signal processing fields such as robust antenna and filter design, radar and sonar detection, and seismology. The continuous-time envelope-constrained filtering problem is then posed as a QP problem with linear inequality constraints:
References:
|
|
|
[Contents] | [Index] |