Acoustic Signal Classification Algorithm for WSN Node in Transport System

Autor:	Michal Chovanec, Róbert Žalman, Jan Kapitulik, Martin Revak
Rok vydání:	2018
Předmět:	Frequency analysis Artificial neural network Computer science business.industry Pattern recognition Signal law.invention Signal classification Computer Science::Sound law Node (circuits) Artificial intelligence business Focus (optics) Transport system
Zdroj:	Innovations for Community Services ISBN: 9783319934075 I4CS
DOI:	10.1007/978-3-319-93408-2_17
Popis:	In the paper, we focus on the classification of the acoustic signal and its characteristic properties, which we use for further processing of the acoustic signal. Its further processing is ensured that we are able to find the carrier frequencies of the selected signal with frequency analysis. We use compression methods to reduce the data needed to classify acoustic signals. We use neural networks to classify these signals. In addition, a method has been proposed to classify acoustic signals that are commonly found in transport. The result is the design of a method that is able to classify signals characteristic for different environments or different acoustic sources. In the paper, there is a description of the experiment that has been carried out for the mentioned purposes. For experiment is created evaluation and classification success rate on selected acoustic signals.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e88454c39b0d1eb113975f64ccc722b6 https://doi.org/10.1007/978-3-319-93408-2_17 Zobrazit plný text záznamu