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List of contents
1. Introduction; 2. Adaptive filtering for sparse models; 3. Kernel-based adaptive filtering; 4. Distributed adaptive filters; 5. Adaptive beamforming; 6. Adaptive filtering on graphs.
About the author
Paulo S. R. Diniz is a Professor at the Universidade Federal do Rio de Janeiro and a Fellow of the IEEE and of EURASIP. He is a Senior Editor of the IEEE Open Journal of Signal Processing and is co-author of a CUP textbook on Digital Signal Processing. He is also a member of the National Academy of Engineering and the Brazilian Academy of Science.Marcello L. R. de Campos is a Professor at the Universidade Federal do Rio de Janeiro. He is a Senior Member of the IEEE and of the Brazilian Telecommunications Society, and member of the Brazilian Mathematical Society and of the Society for Industrial and Applied Mathematics.Wallace A. Martins is an Associate Professor at the Universidade Federal do Rio de Janeiro and a researcher with the University of Luxembourg. He is an Associate Editor for the IEEE Signal Processing Letters, and is currently a Senior Member of the IEEE and a member of the Brazilian Telecommunications Society.Markus V. S. Lima is an Associate Professor at the Universidade Federal do Rio de Janeiro and Chair of the IEEE Signal Processing Chapter in Rio de Janeiro. He is also a member of the Brazilian Telecommunications Society.José A. Apolinário, Jr. is an Associate Professor at the Military Institute of Engineering. He is a Senior Member of the IEEE and the Brazilian Society of Telecommunications.
Summary
Learn to solve the unprecedented challenges facing Adaptive Signal Processing in this concise, intuitive text. Describing up-to-date techniques and algorithms in a condensed and unified way, this one-of-a-kind book allows you to implement solutions to practical problems and is an ideal resource for graduate students, researchers and professionals.
