Detection of Structural Features in Biological Signals |
| |
Authors: | Aleksandar Jovanovi? Aleksandar Perovi? Wlodzimierz Klonowski Wlodzis?aw Duch Zoran ?or?evi? Sla?ana Spasi? |
| |
Affiliation: | (1) Group for Intelligent Systems, School of Mathematics, University of Belgrade, Studentski trg 16, 11000 Belgrade, Serbia;(2) Lab. Biosignal Analysis Fundamentals, Institute of Biocybernetics & Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland;(3) Department of Informatics, Nicolaus Copernicus University, Torun, Poland;(4) Department of Life Sciences, Institute for Multidisciplinary Research, Belgrade, Serbia |
| |
Abstract: | In this article structures in biological signals are treated. The simpler—directly visible in the signals, which still demand
serious methods and algorithms in the feature detection, similarity investigation and classification. The major actions in
this domain are of geometric, thus simpler sort, though there are still hard problems related to simple situations. The other
large class of less simple signals unsuitable for direct geometric or statistic approach, are signals with interesting frequency
components and behavior, those suitable for spectroscopic analysis. Semantics of spectroscopy, spectroscopic structures and
research demanded operations and transformations on spectra and time spectra are presented. The both classes of structures
and related analysis methods and tools share a large common set of algorithms, all of which aiming to the full automatization.
Some of the signal features present in the brain signal patterns are demonstrated, with the contexts relevant in BCI, brain
computer interfaces. Mathematical representations, invariants and complete characterization of structures in broad variety
of biological signals are in the central focus. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|