Efficient Nonlinear Adaptive Filters

This book presents the design, analysis, and application of nonlinear adaptive filters with the goal of improving efficient performance (ie the convergence speed, steady-state error, and computational complexity). The authors present a nonlinear adaptive filter, which is an important part of nonlinear system and digital signal processing and can be applied to diverse fields such as communications, control power system, radar sonar, etc. The authors also present an efficient nonlinear filter model and robust adaptive filtering algorithm based on the local cost function of optimal criterion to overcome non-Gaussian noise interference. The authors show how these achievements provide new theories and methods for robust adaptive filtering of nonlinear and non-Gaussian systems. The book is written for the scientist and engineer who are not necessarily an expert in the specific nonlinear filtering field but who want to learn about the current research and application. The book is also writtento accompany a graduate/PhD course in the area of nonlinear system and adaptive signal processing.

Presents recent research results and applications of nonlinear adaptive filters in a variety of areas Includes the basic models, algorithms, performance analysis and applications of various nonlinear filters Suitable for scientists and engineers who want to learn about nonlinear filtering

Auteur
Haiquan Zhao (IEEE Senior Member) received the B.S. degree in applied mathematics in 1998, the M.S. degree and the Ph.D degree in Signal and Information Processing all at Southwest Jiaotong University, Chengdu, China, in 2005 and 2011, respectively. Since August 2012, he was a Professor with the School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China. From 2015 to 2016, as a visiting scholar, he worked at University of Florida, USA. His current research interests include information theoretical learning, neural networks, adaptive network, adaptive filtering algorithm, nonlinear active noise control, nonlinear system identification, power system frequency estimation. At present, he is the author or coauthor of more than 140 international journal papers (SCI indexed), and the owner of 70 invention patents. Prof. Zhao has served as an active reviewer for several IEEE Transactions, IET series, Signal Processing, and other international journals. From August 2017, hewas appointed an Editorial board member of AEU- International Journal of Electronics and Communications. And also appointed an associate editor of IEEE Access from March 2019. At presented, he also was a handling editor of Signal Processing ( Top Journal).Badong Chen (IEEE Senior Member) received the B.S. and M.S. degrees in Control Theory and Engineering from Chongqing University, Chongqing, China, in 1997 and 2003, respectively, and the Ph.D. degree in Computer Science and Technology from Tsinghua University, Beijing, China, in 2008. He was a Postdoctoral Associate at the University of Florida Computational NeuroEngineering Laboratory (CNEL) from 2010 to 2012. He visited the Nanyang Technological University (NTU), Singapore, as a visiting research scientist in 2015. He also served as a senior research fellow with The Hong Kong Polytechnic University in 2017. Currently he is a professor at the Institute of Artificial Intelligence and Robotics (IAIR), Xi'an Jiaotong University,Xi'an, China. His research interests are in signal processing, machine learning, artificial intelligence, neural engineering and robotics. He has published two books and over 200 papers in various journals and conference proceedings and his papers have got over 5700 citations according to Google Scholar. Dr. Chen is an IEEE Senior Member, a Technical Committee Member of IEEE SPS Machine Learning for Signal Processing (MLSP) and IEEE CIS Cognitive and Developmental Systems (CDS), and an associate editor of IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Neural Networks and Learning Systems and Journal of The Franklin Institute, and has been on the editorial board of Entropy.

Contenu
Adaptive filter.- Volterra adaptive filter.- FLANN adaptive filter.- Spline adaptive filter.- Kernel adaptive filters. <p