Kalman Filtering Under Information Theoretic Criteria

本書提供了幾種在信息理論標準下的高效卡爾曼濾波器（線性或非線性）。它們在複雜的非高斯噪聲中表現出色，計算複雜度低，並具有良好的實際應用潛力。本書將所有這些觀點和結果整合成一個資源，供相關應用領域的學生和從業者使用。每一章都以簡要回顧基礎知識開始，然後專注於該主題最重要的特性，並比較評估模型，討論自由參數及其對結果的影響。每章的末尾提供了證明。本書適合對線性代數、信號處理和統計有基本了解的高年級本科生，以及具有卡爾曼濾波經驗的研究生或從業者。

- 提供在信息理論標準下的卡爾曼濾波器，以在多種應用中實現卓越性能；
- 每章以簡要回顧基礎知識開始，然後專注於主題的最重要特性；
- 針對學生對線性代數、信號處理和統計的理解。

Badong Chen 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 5500 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.

Lujuan Dang received the B.S. degree in information science and technology from Northwest University, Xi'an, China, in 2015, and the M.S. degree in electronic and information engineering from Southwest University, Chongqing, China, in 2018. She is currently pursuing the Ph.D. degree with the Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an. Her current interests focus on adaptive filtering and information theoretic learning.

Nanning Zheng graduated from the Department of Electrical Engineering, Xi'an Jiaotong University, Xi'an, China, in 1975, and received the M.S. degree in information and control engineering from Xi'an Jiaotong University in 1981 and the Ph.D. degree in electrical engineering from Keio University, Yokohama, Japan, in 1985. He is currently a professor and director of the Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University. His research interests include computer vision, pattern recognition and image processing, and hardware implementation of intelligent systems. Prof. Zheng became a member of the Chinese Academy of Engineering in 1999, and he is the Chinese Representative on the Governing Board of the International Association for Pattern Recognition. He is an IEEE Fellow and serves as an executive deputy editor of the Chinese Science Bulletin.

Jose C. Principe is a Distinguished Professor of Electrical and Computer Engineering at the University of Florida where he teaches advanced signal processing, machine learning and artificial neural networks (ANNs). He is the Eckis Professor and the Founder and Director of the University of Florida Computational NeuroEngineering Laboratory (CNEL) www.cnel.ufl.edu. The CNEL Lab innovated signal and pattern recognition principles based on information theoretic criteria, as well as filtering in functional spaces. His secondary area of interest has focused in applications to computational neuroscience, Brain Machine Interfaces and brain dynamics. Dr. Principe is a Fellow of the AAAS, IEEE, NAI, AIMBE, and IAMBE. He received the Gabor Award from the INNS, the Shannon- Nyquist Technical Achievement Award from the IEEE Signal Processing Society, the Career Achievement Award from the IEEE EMBS and the Neural Network Pioneer Award of the IEEE CIS. He has more than 33 patents awarded and over 900 publications in the areas of adaptive signal processing, control of nonlinear dynamical systems, machine learning and neural networks, information theoretic learning, with applications to neurotechnology and brain computer interfaces. He directed 108 Ph.D. dissertations and 65 Master theses. He has received four Honorary Doctor Degrees, from Finland, Italy, Brazil and Colombia, and routinely serves in international scientific advisory boards of Universities and Companies.

Badong Chen於1997年和2003年分別獲得中國重慶大學控制理論與工程的學士和碩士學位，並於2008年獲得中國清華大學計算機科學與技術的博士學位。他於2010年至2012年擔任佛羅里達大學計算神經工程實驗室的博士後研究員。2015年，他作為訪問研究科學家訪問新加坡南洋理工大學。2017年，他擔任香港理工大學的高級研究員。目前，他是中國西安交通大學人工智慧與機器人研究所的教授。他的研究興趣包括信號處理、機器學習、人工智慧、神經工程和機器人技術。他已出版兩本書籍和200多篇論文，根據Google Scholar的資料，他的論文被引用超過5500次。陳博士是IEEE高級會員，IEEE SPS信號處理機器學習技術委員會和IEEE CIS認知與發展系統技術委員會的成員，並擔任IEEE認知與發展系統期刊、IEEE神經網絡與學習系統期刊及富蘭克林學會期刊的副編輯，並曾擔任《Entropy》的編輯委員會成員。

Lujuan Dang於2015年獲得中國西北大學信息科學與技術的學士學位，並於2018年獲得中國重慶西南大學電子與信息工程的碩士學位。她目前正在西安交通大學人工智慧與機器人研究所攻讀博士學位。她目前的研究興趣集中在自適應過濾和信息理論學習上。

Nanning Zheng於1975年畢業於中國西安交通大學電機工程系，並於1981年獲得該校信息與控制工程的碩士學位，1985年獲得日本慶應義塾大學電機工程的博士學位。他目前是西安交通大學人工智慧與機器人研究所的教授及所長。他的研究興趣包括計算機視覺、模式識別和圖像處理，以及智能系統的硬體實現。鄭教授於1999年成為中國工程院院士，並擔任國際模式識別協會的中國代表。他是IEEE Fellow，並擔任《中國科學通報》的執行副編輯。

Jose C. Principe是佛羅里達大學電機與計算機工程的傑出教授，教授高級信號處理、機器學習和人工神經網絡（ANNs）。他是Eckis教授，也是佛羅里達大學計算神經工程實驗室（CNEL）的創始人和主任。CNEL實驗室基於信息理論標準創新了信號和模式識別原則，以及在功能空間中的過濾。他的次要研究興趣集中在計算神經科學、腦機介面和腦動力學的應用上。Principe博士是AAAS、IEEE、NAI、AIMBE和IAMBE的Fellow。他曾獲得INNS的Gabor獎、IEEE信號處理學會的Shannon-Nyquist技術成就獎、IEEE EMBS的職業成就獎以及IEEE CIS的神經網絡先驅獎。他擁有超過33項專利和900多篇在自適應信號處理、非線性動態系統控制、機器學習和神經網絡、信息理論等領域的出版物。