Detecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....

The problem of elimination of impulsive disturbances (such as clicks, pops, ticks, crackles, and record scratches) from archive audio recordings is considered and solved using autoregressive modeling. Three classical noise pulse detection schemes are examined and compared: the approach based on open-loop multi-step-ahead signal prediction, the approach based on decision-feedback signal prediction, and the double threshold approach,...

Opracowano metodę analizy osadów dennych na zawartość związków cynoorganicznych (MBT, DBT, TBT, MPhT, DPhT, TPhT) przy użyciu przyspieszonej ekstrakcji rozpuszczalnikiem i chromatografii gazowej z detektorem płomieniowo-fotometrycznym. Detektor ten pozwala selektywnie wykrywać niewielkie ilości pochodnych cynoorganicznych. Niestety, bardzo często spotykana w osadach siarka oraz jej pochodne zakłócają sygnał detektora. Z tego względu...

In this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...