Kernel Methods in Bioengineering, Signal and Image Processing covers real-world applications, such as computational biology, text categorization, time series prediction, interpolation, system identification, speech recognition, image de-noising, image coding, classification, and segmentation. Kernel Methods in Bioengineering, Signal and Image Processing encompasses the vast field of kernel methods from a multidisciplinary approach by presenting chapters dedicated to adaptation and use of kernel methods in the selected areas of bioengineering, signal processing and communications, and image processing.
Dr. Jose Luis Rojo Álvarez is an associate professor at the Department of Signal Theory and Communications in University Carlos III of Madrid (Spain), where he teaches Systems and Circuits and related topics. He received a B.Sc. (1996) and the Ph.D. (2000) degrees on Telecommunication Engineering at University of Vigo and University Politécnica de Madrid, respectively. His research interests focus on statistical learning methods for signal and image processing, arrhythmia mechanisms, robust signal processing methods for cardiac repolarization, and Doppler image post-processing. He has (co)authored 25 international papers and has contributed to more than 60 conference proceedings.
Dr. Manel Martínez-Ramón is an associate professor at the Dpt. Signal Theory and Communications, at Universidad Carlos III de Madrid. He is currently doing research with the Group of Information Management and Processing and teaching several undergraduate and graduate courses in the area of knowledge of signal processing and communications. He has worked in several institutions including the University of New Mexico, USA and the Universidad Politécnica de Cartagena, Spain. He has participated in many research projects and published 40 papers in international journals and conferences about neural networks, machine learning and its applications to signal processing. [Editor]