Sensitivity Considerations in the Design of Linear Least Mean-Squared Error Filters,
Abstract
The usual approach to linear least mean-squared error filter design is concerned with minimizing a quadratic function of the error. Neglected in such an analysis is the effect that variations of the filter parameters may have upon the error criterion. In this paper the quadratic error term is combined with a suitable sensitivity measure to produce a new performance function, which is then minimized by selecting the appropriate linear filter. The resulting mean-squared error will be larger than the minimum error but less sensitive to parameter variations. To illustrate the advantages of this method, two specific examples are considered; both are concerned with estimating a random signal in while noise and exhibit a significant decrease in sensitivity with only a modest increase in mean-squared error. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1971
- Accession Number
- AD0732132
Entities
People
- K. J. Liopiros
- R. Lugannani
Organizations
- Princeton University