Abstract
The paper presents a method of signal analysis which is based on the parameter space consideration. The parameter space is created during the short-time analysis of the signal. The general schema of the approach consists of using a time window sliding in time along a signal. After choosing some particular parameters one observes their changes in a sliding window and analyzes the data in a multidimensional parameter space. For recognition and detection of different system states we propose to perform the clustering in the parameter space. The presented approach was used for analysis of EEG signals and some vibroacoustic signals taken form the combustion engine.
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Boguś, P., Lewandowska, K.D. (2004). Short-Time Signal Analysis Using Pattern Recognition Methods. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_82
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DOI: https://doi.org/10.1007/978-3-540-24844-6_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22123-4
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