Rough Set Flow Graphs and Ant Based Clustering in Classification of Disturbed Periodic Biosignals

In the paper, we are interested in classification of disturbed periodic biosignals. An ant based clustering algorithm is used to group episodes into which examined biosignals are divided. Disturbances in periodicity of such signals cause some difficulties in formation of coherent clusters of similar episodes. A quality of a clustering process result can be used as an indicator of disturbances. A local function in the applied clustering algorithm is calculated on the basis of temporal rough set flow graphs representing an information flow distribution for episodes.

[1]  Krzysztof Pancerz,et al.  Rough Set Flow Graphs and Max - * Fuzzy Relation Equations in State Prediction Problems , 2008, RSCTC.

[2]  Krzysztof Pancerz,et al.  Computer-based clinical decision support for laryngopathies using recurrent neural networks , 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

[3]  Amine Nait-Ali.  Advanced Biosignal Processing , 2009 .

[4]  Krzysztof Pancerz,et al.  Recurrent Neural Networks in Computer-Based Clinical Decision Support for Laryngopathies: An Experimental Study , 2011, Comput. Intell. Neurosci..

[5]  Krzysztof Pancerz,et al.  Ant Based Clustering of Time Series Discrete Data - A Rough Set Approach , 2011, SEMCCO.

[6]  John L. Semmlow,et al.  Biosignal and Medical Image Processing , 2004 .

[7]  Krzysztof Pancerz,et al.  Computer Diagnosis of Laryngopathies Based on Temporal Pattern Recognition in Speech Signal , 2010, Bio Algorithms Med Syst..

[8]  Krzysztof Pancerz,et al.  Ant Based Clustering of Two-Class Sets with Well Categorized Objects , 2012, IPMU.

[9]  Krzysztof Pancerz,et al.  Classification of Speech Signals through Ant Based Clustering of Time Series , 2012, ICCCI.

[10]  Theophano Mitsa,et al.  Temporal Data Mining , 2010 .

[11]  Zdzislaw Pawlak,et al.  Flow Graphs and Data Mining , 2005, Trans. Rough Sets.

[12]  Shusaku Tsumoto,et al.  Rough Sets and Current Trends in Computing , 2001, Lecture Notes in Computer Science.

[13]  Marco Dorigo,et al.  Ant-Based Clustering and Topographic Mapping , 2006, Artificial Life.

[14]  Jean-Louis Deneubourg,et al.  The dynamics of collective sorting robot-like ants and ant-like robots , 1991 .

[15]  Krzysztof Pancerz,et al.  Classification of Voice Signals through Mining Unique Episodes in Temporal Information Systems: A Rough Set Approach , 2012, CS&P.

[16]  Baldo Faieta,et al.  Diversity and adaptation in populations of clustering ants , 1994 .