(Хмельницький національний університет, 2015) Romanuke, V.V.; Романюк, В.В.
For tracking metal wear states at bad statistical data inaccuracies and shifts, there is a method of resume-training of
discontinuous wear state trackers for boosting them within high-accurate ensembles. These trackers are Gaussian-noiseddata-
trained two-layer perceptrons. An ordinary tracker is selected and, if its performance is satisfactory, it is resumed-trained
cyclically. Number of additional passes of training sets is limited. The resume-training procedure wholly can be cycled.