Risk upper bound for a NM-type multiresolution classification scheme of random signals by Daubechies wavelets
| Autor: | Zygmunt Hasiewicz, Urszula Libal |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science 020206 networking & telecommunications Pattern recognition Classification scheme 02 engineering and technology Upper and lower bounds ComputingMethodologies_PATTERNRECOGNITION Wavelet Binary classification Artificial Intelligence Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Electrical and Electronic Engineering business Classifier (UML) |
| Zdroj: | Engineering Applications of Artificial Intelligence. 62:109-123 |
| ISSN: | 0952-1976 |
| DOI: | 10.1016/j.engappai.2017.04.005 |
| Popis: | We propose an adaptive multistage classification scheme, based on the principle of multiresolution, using a naturally hierarchical wavelet representation of signals. The use of this principle in the context of a multi-class recognition task leads to the multistage binary classification tree, where recognition at different stages is performed with varying degrees of precision. In the paper, multistage minimum-distance NM-type binary classifier with reject option is introduced and examined. We analyze the upper bound of risk of the developed multistage classifier, especially paying attention to the impact of free (design) parameters on the efficiency of the classifier. The theoretical considerations are illustrated by simulation experiment and practical examples based on some benchmarks. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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