Title :
Adaptive rank filtering based on error minimization
Author_Institution :
David Sarnoff Res. Center, Princeton, NJ, USA
Abstract :
A method for adaptive (online) pruning and constructing a (layered) computational network is introduced. The dimensions of the network are updated for every new available sample, which makes this technique highly suitable for tracking nonstationary sources. This method extends work on predictive least squares by Rissanen (1986) and Wax (1988) to an adaptive updating scheme. The algorithm is demonstrated by an application to adaptive prediction of exchange rates
Keywords :
adaptive filters; adaptive signal processing; error correction; filtering theory; least squares approximations; minimisation; multilayer perceptrons; prediction theory; adaptive prediction; adaptive pruning; adaptive rank filtering; error minimization; exchange rates; layered computational network; nonstationary source tracking; online pruning; predictive least squares; Adaptive filters; Computer networks; Exchange rates; Filtering; Least squares approximation; Least squares methods; Nonlinear filters; Predictive models; Speech; Statistics;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.595470
