Introduction to Graph Signal Processing.- Oversampled Graph Laplacian Matrix for Graph Filter Banks.- Toward an Uncertainty Principle for Weighted Graphs.- Graph Theoretic Uncertainty and Feasibility.- Signal-Adapted Tight Frames on Graphs.- Local Spectral Analysis of the Cerebral Cortex: New Gyrification Indices.- Intrinsic Geometric Information Transfer Learning on Multiple Graph-Structured Datasets.
About the Author
Ljubisa Stankovic received the B.S.and the Ph.D degree in Electrical Engineering from the University of Montenegro, and the M.S. degree from the University of Belgrade. He is a professor at the University of Montenegro. He has been visiting academic at several universities, including the Ruhr University Bochum, Technische Universiteit Eindhoven, and the Imperial College, London. He is a member and vice-president of the National Academy of Science and Arts of Montenegro and a member of the European Academy of Sciences and Arts. He is a senior area editor of the IEEE Transactions on Image Processing, a member of the Editorial Board of Signal Processing, and an associate editor of the IET Signal Processing. He was an associate editor of the IEEE Signal Processing Letters and the IEEE Transactions on Signal Processing. His current interests are in Signal Processing. He published several books and about 400 papers, more than 150 of them in the leading journals. He was awarded the best Signal Processing journal award in 2017 by the European Association for Signal Processing. Stankovic is a Fellow of the IEEE since 2012 for contributors to time-frequency signal analysis. Ervin Sejdic received the B.E.Sc. and Ph.D. degrees in electrical engineering from the University of Western Ontario, London, ON, Canada, in 2002 and 2008, respectively. He was a Postdoctoral Fellow with Holland Bloorview Kids Rehabilitation Hospital/University of Toronto and a Research Fellow in medicine with Beth Israel Deaconess Medical Center/Harvard Medical School. He is currently an Associate Professor with the Department of Electrical and Computer Engineering (Swanson School of Engineering), the Department of Bioengineering (Swanson School of Engineering), the Department of Biomedical Informatics (School of Medicine), and the Intelligent Systems Program (School of Computing and Information) at the University of Pittsburgh, Pittsburgh, PA, USA. His research interests include biomedical and theoretical signal processing, swallowing difficulties, gait and balance, assistive technologies, rehabilitation engineering, anticipatory medical devices, and advanced information systems in medicine.