Adaptive Filtering Under Minimum Mean p-Power Error Criterion

Author:   Wentao Ma (Xi'an University, China) ,  Badong Chen (Xi'an University, China)
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032001654


Pages:   376
Publication Date:   31 May 2024
Format:   Hardback
Availability:   Not yet available   Availability explained
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Adaptive Filtering Under Minimum Mean p-Power Error Criterion


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Author:   Wentao Ma (Xi'an University, China) ,  Badong Chen (Xi'an University, China)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   0.880kg
ISBN:  

9781032001654


ISBN 10:   1032001658
Pages:   376
Publication Date:   31 May 2024
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

1. Introduction 2. Adaptive Filtering Algorithms under MMSE Criterion 3. MMPE Family Criteria 4. Adaptive Filtering Algorithms under MMPE 5. Recursive Adaptive Filtering Algorithms under MMPE 6. Nonlinear Filtering Algorithms under MMPE 7. Adaptive Filtering Algorithms under Mixture MMPE 8. Adaptive Filtering Algorithms under KMPE Family Criteria

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Author Information

Wentao Ma received a BSc in Mathematics and Applied Mathematics from Shannxi University of Technology in 2003, an MSc in Computing Mathematics from Huazhong University of Science and Technology in 2008, and a Ph.D. in Information and Communication Engineering from Xi'an Jiaotong University, in 2015. Currently, he is an associate professor with the School of Electrical Engineering, Xi'an University of Technology, Xi'an, China. His research interests include statistical signal processing, machine learning, artificial intelligence, and their applications in Electrical and Computer Engineering. He has published over 50 papers in various journals and conference proceedings. He is a member of IEEE, IEEE PES, and CAA. Badong Chen received BSc and MSc degrees in Control Theory and Engineering from Chongqing University in 1997 and 2003 respectively. He also received his Ph.D. in Computer Science and Technology from Tsinghua University in 2008. He was a postdoctoral associate at the University of Florida Computational Neuro Engineering Laboratory (CNEL) from 2010 to 2012. He was a visiting research scientist at the Nanyang Technological University (NTU), Singapore, 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. His research interests include signal processing, machine learning, artificial intelligence, neural engineering, and robotics. He has published four books and over 300 papers in various journals and conference proceedings. He is an IEEE Senior Member and has served as a Technical Committee Member of IEEE SPS Machine Learning for Signal Processing (MLSP). He has been an associate editor of: IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Neural Networks and Learning Systems, Journal of The Franklin Institute and Neural Networks. He has also been on the editorial board of Entropy.

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