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Plenary Talks

Fuzzy Recurrence Analysis of Complex Systems Dynamics

Tuan D. Pham

Department of Biomedical Engineering Linkoping University, Sweden


Recurrence is pervasive in dynamical systems of the real world, and a fundamental property of dynamical processes. Methods for studying recurrences allow for both qualitative and quantitative measures of complex systems and their dynamics. Recurrence plots, which are visualizations of the recurrences of dynamical systems, and recurrence quantification analysis have been increasingly attracting interests from a wide range of scientific disciplines and applications. Based on the concept of recurrences in phase space, recurrence networks of a time series can be constructed, and their associated network properties are useful for gaining insight into the underlying dynamics of complex systems. However, there are critical issues for constructing recurrence plots and recurrence networks. These are the threshold for computing similarity that is very sensitive to the visual effect and their scalability in dealing with long time series. The concepts of fuzzy recurrence plots and fuzzy recurrence networks have recently been developed, revealing strong conceptual benefits of the new approach that can avoid the difficulty in selecting the critical similarity threshold, offers better computational requirements, and be considered as a convenient framework for transforming time series into recurrence complex networks that are unweighted or weighted, and scalable. Furthermore, fuzzy recurrence plots and fuzzy recurrence networks of multidimensional data can also be constructed. This talk will present theoretical developments of fuzzy recurrence analysis and its applications to the analysis and classification of sensor-based physiological signals, and quantification of complex patterns in medical images.

Biography of Prof. T.D. Pham

Tuan D. Pham is Professor of Biomedical Engineering at Linkoping University, University Hospital Campus, Linkoping, Sweden. Prior to the current position, he was appointed as Professor and Leader of the Aizu Research Cluster for Medical Engineering and Informatics, and the Medical Image Processing Lab, both at the University of Aizu, Japan. Before his appointments in Japan, He was the Bioinformatics Research Group Leader at the University of New South Wales, Canberra, Australia. His current research focuses on AI and machine learning methods for image processing, time-series analysis, complex networks, and pattern recognition applied to medicine, biology, and mental health. He serves as an Associate Editor for a number of scholarly journals, series, and conference proceedings, such as Pattern Recognition (Elsevier), Heliyon (Elsevier), IET Signal Processing, Computer Science Advisory Board (Cambridge Scholars), Current Bioinformatics (Bentham), IEEE-EMBC (Theme 10: Biomedical & Health Informatics), ACM, and SPIE conference proceedings. Dr. Pham has published extensively on pattern recognition, image processing, and time-series analysis in medicine, biology, and mental health.

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