Sciweavers

Share
PR
2006

Prototype reduction schemes applicable for non-stationary data sets

8 years 10 months ago
Prototype reduction schemes applicable for non-stationary data sets
All of the prototype reduction schemes (PRS) which have been reported in the literature, process time-invariant data to yield a subset of prototypes that are useful in nearest-neighbor-like classification. Although these methods have been proven to be powerful, they suffer from a major disadvantage when they are utilized for applications involving non-stationary data, namely, time varying samples, typical of video and multimedia applications. In this paper, we suggest two PRS mechanisms which, in turn, are suitable for two distinct models of non-stationarity. In the first model, the data points obtained at discrete time steps, are individually assumed to be perturbed in the feature space, because of noise in the measurements or features. As opposed to this, in the second model, we assume that, at discrete time steps, new data points are available, and that these themselves are generated due to a non-stationarity in the parameters of the feature space. In both of these cases, rather th...
Sang-Woon Kim, B. John Oommen
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where PR
Authors Sang-Woon Kim, B. John Oommen
Comments (0)
books