Fuzzy Recurrence Plots and Networks with Applications in Biomedicine - Softcover

Über die Autorin bzw. den Autor

Tuan D. Pham is Professor and Director of the Center for Artificial Intelligence at Prince Mohammad Bin Fahd University, Al Khobar, Kingdom of Saudi Arabia. He has been a Professor of Biomedical Engineering at Linköping University, Sweden, and held other previous positions as Professor and the Leader of the Aizu Research Cluster for Medical Engineering and Informatics, Head of the Medical Image Processing Laboratory at the University of Aizu, Japan; and the Bioinformatics Research Group Leader, the School of Engineering and Information Technology, the University of New South Wales, Australia. His teaching and research span across several disciplines of computer science and engineering. His current research areas include artificial intelligence, image processing, time series, nonlinear dynamics, novel methods in pattern recognition and machine learning applied to medicine, physiology, biology, and health. He has been actively serving as Section Editor and Associate Editor of several international journals, conference chair, keynote speaker, and invited speaker.  Dr. Pham has been internationally recognized by his peers as a highly prolific scientist, publishing extensively as the lead author on various topics in books by well-known publishers, well-respected journals, and refereed conferences.

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This book presents an original combination of three well-known methodological approaches for nonlinear data analysis: recurrence, networks, and fuzzy logic.

After basic concepts of these three approaches are introduced, this book presents recently developed methods known as fuzzy recurrence plots and fuzzy recurrence networks.  Computer programs written in MATLAB, which implement the basic algorithms, are included to facilitate the understanding of the developed ideas. Several applications of these techniques to biomedical problems, ranging from cancer and neurodegenerative disease to depression, are illustrated to show the potential of fuzzy recurrence methods.

This book opens a new door to theorists in complex systems science as well as specialists in medicine, biology, engineering, physics, computer science, geosciences, and social economics to address issues in experimental nonlinear signal and data processing.