Design of weighted order statistic filters by training-based optimization
Pertti T. Koivisto, Heikki J. Huttunen · 2002
This paper demonstrates how weighted order statistic filters can be designed using training-based optimization. The design method utilizes supervised learning with simulated annealing as the learning rule. In addition, the efficiency and flexibility of the presented method are studied through experiments.