Real Domain Adaptive WOS Filtering using Neural Network Approximations
I. Tabus, Moncef Gabbouj, Lin Yin · 2005
The problem of optimal Weighted Order Statistics (WOS) filters design is first related to the optimal design in a larger class, called Variable Rank Order Statistics (VROS) filters, the results obtained pro viding guidelines for the approach to be used in WOS filtering. Since adaptive methods applied directly to WOS filter models have to cope with a very ill conditioned problem, the adaptation will act on a model which belongs to Neural Networks (NN) class. This particular neural model can be trained using an algorithm very similar to the classical Backpropagation algorithm. In the final stage of training, the neural model can be made arbitrarily close to a WOS filter.