| Title: | Adaptive Novelty Detection with Generalized Extreme Value Distribution |
| Authors: | Vrba, Jan |
| Citation: | 2018 International Conference on Applied Electronics: Pilsen, 11th – 12th September 2018, Czech Republic, 169-172. |
| Issue Date: | 2018 |
| Publisher: | Západočeská univerzita v Plzni |
| Document type: | konferenční příspěvek conferenceObject |
| URI: | http://hdl.handle.net/11025/35495 |
| ISBN: | 978–80–261–0721–7 |
| ISSN: | 1803–7232 |
| Keywords: | zpracování signálu;adaptivní systémy;adaptivní algoritmy;detekce změn;zobecněné rozdělení extrémních hodnot |
| Keywords in different language: | signal processing;adaptive systems;adaptive algorithms;novelty detection;generalized extreme value distribution |
| Abstract in different language: | This paper introduces the new adaptive novelty detection method. The proposed method is using generalized extreme value distribution to evaluate the absolute value of adaptive system weight increments in time. The detection of novelty is threshold-based and the threshold ζ corresponds to the value of joint probability density function. Performance of the proposed algorithm is shown on artificial data. For comparison also results of Learning Entropy algorithm are shown, as this algorithm also evaluates the increments of adaptive weights. |
| Rights: | © Západočeská univerzita v Plzni |
| Appears in Collections: | Applied Electronics 2018 Applied Electronics 2018 |
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