Title :
Minimum mean absolute error nonlinear filtering
Author :
Lin, J.H. ; Coyle, E.J.
Author_Institution :
Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
Abstract :
A class of sliding window operators called generalized stack filters is developed. This class of filters, which includes all rank order filters, stack filters, and digital morphological filters, is the set of all filters possessing the threshold decomposition architecture and a consistency property, called the stacking property. A linear program is provided which determines a generalized stack filter which minimizes the Mean Absolute Error (MAE) between the output of the filter and a desired input signal, given noisy observations of that signal. These results show that choosing the generalized stack filter which minimizes the MAE is equivalent to massively parallel threshold-crossing decision making when these decisions are consistent with each other
Keywords :
digital filters; error analysis; filtering and prediction theory; minimisation; Boolean functions; decision making; digital morphological filters; error minimisation; generalized stack filters; input signal; linear program; massively parallel threshold-crossing; mean absolute error nonlinear filtering; noisy observations; rank order filters; sliding window operators; stacking property; threshold decomposition architecture; Boolean functions; Decision making; Digital filters; Error analysis; Filtering; Nonlinear filters; Stacking; Stochastic processes;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on
Conference_Location :
New York, NY
DOI :
10.1109/ICASSP.1988.196871