Signal processing approach for breath prediction pattern recognition

• Autorzy: Twardochleb, M. , Król, T.
• Języki publikacji: EN

Abstrakty

EN

In this paper, a new approach of signal processing for breath prediction pattern recognition is proposed and further analyses are presented. In order to extract key values from raw data, a shift from time domain to phase space has been utilized. It helped to achieve clearer peak-to-peak measurements which are crucial for breath prediction pattern recognition. Based on a special software tool for breath prediction pattern recognition several different algorithms have been compared. As a result, a reduction in error rate can be achieved when applying a new signal processing approach in comparison to the previous designs.

Słowa kluczowe

EN

pattern recognition; signal processing; neural network

• Czasopismo: Journal of Theoretical and Applied Computer Science
• Rocznik: 2013
• Tom: Vol. 7, nr 3
• Strony: 51--60
• Opis fizyczny: Bibliogr. 11 poz., rys., tab.

Twórcy

autor

Twardochleb, M.

• Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland,

autor

Król, T.

• Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland

Bibliografia

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