Badong Chen's Books

Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms

By: Xinghua Liu,Rui Jiang,Badong Chen,Shuzhi Sam Ge

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Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms

By: Xinghua Liu,Rui Jiang,Badong Chen,Shuzhi Sam Ge

Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms Enables readers to understand important new trends in multimodal perception for mobile robotics This book provides a novel perspective on secure state estimation and multimodal perception for robotic mobility platforms such as autonomous vehicles. It thoroughly evaluates filter-based secure dynamic pose estimation approaches for autonomous vehicles over multiple attack signals and shows that they outperform conventional Kalman filtered results. As a modern learning resource, it contains extensive simulative and experimental results that have been successfully implemented on various models and real platforms. To aid in reader comprehension, detailed and illustrative examples on algorithm implementation and performance evaluation are also presented. Written by four qualified authors in the field, sample topics covered in the book include: Secure state estimation that focuses on system robustness under cyber-attacks Multi-sensor fusion that helps improve system performance based on the complementary characteristics of different sensors A geometric pose estimation framework to incorporate measurements and constraints into a unified fusion scheme, which has been validated using public and self-collected data How to achieve real-time road-constrained and heading-assisted pose estimation This book will appeal to graduate-level students and professionals in the fields of ground vehicle pose estimation and perception who are looking for modern and updated insight into key concepts related to the field of robotic mobility platforms.

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Page Count

228

Publisher

John Wiley & Sons

Published Date

ISBN 10

111987601X

ISBN 13

9781119876014

System Parameter Identification

Information Criteria and Algorithms

By: Badong Chen,Yu Zhu,Jinchun Hu,Jose C. Principe

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System Parameter Identification

Information Criteria and Algorithms

By: Badong Chen,Yu Zhu,Jinchun Hu,Jose C. Principe

Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification. The authors' research provides a base for the book, but it incorporates the results from the latest international research publications. - Named a 2013 Notable Computer Book for Information Systems by Computing Reviews - One of the first books to present system parameter identification with information theoretic criteria so readers can track the latest developments - Contains numerous illustrative examples to help the reader grasp basic methods

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Page Count

266

Publisher

Newnes

Published Date

ISBN 10

0124045952

ISBN 13

9780124045958

Adaptive Filtering Under Minimum Mean p-Power Error Criterion

By: Wentao Ma,Badong Chen

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Adaptive Filtering Under Minimum Mean p-Power Error Criterion

By: Wentao Ma,Badong Chen

Adaptive filtering still receives attention in engineering as the use of the adaptive filter provides improved performance over the use of a fixed filter under the time-varying and unknown statistics environments. This application evolved communications, signal processing, seismology, mechanical design, and control engineering. The most popular optimization criterion in adaptive filtering is the well-known minimum mean square error (MMSE) criterion, which is, however, only optimal when the signals involved are Gaussian-distributed. Therefore, many "optimal solutions" under MMSE are not optimal. As an extension of the traditional MMSE, the minimum mean p-power error (MMPE) criterion has shown superior performance in many applications of adaptive filtering. This book aims to provide a comprehensive introduction of the MMPE and related adaptive filtering algorithms, which will become an important reference for researchers and practitioners in this application area. The book is geared to senior undergraduates with a basic understanding of linear algebra and statistics, graduate students, or practitioners with experience in adaptive signal processing. Key Features: Provides a systematic description of the MMPE criterion. Many adaptive filtering algorithms under MMPE, including linear and nonlinear filters, will be introduced. Extensive illustrative examples are included to demonstrate the results.

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Page Count

389

Publisher

CRC Press

Published Date

ISBN 10

1040015921

ISBN 13

9781040015926

Kalman Filtering Under Information Theoretic Criteria

By: Badong Chen,Lujuan Dang,Nanning Zheng,Jose C. Principe

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Kalman Filtering Under Information Theoretic Criteria

By: Badong Chen,Lujuan Dang,Nanning Zheng,Jose C. Principe

This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and have great practical application potential. The book combines all these perspectives and results in a single resource for students and practitioners in relevant application fields. Each chapter starts with a brief review of fundamentals, presents the material focused on the most important properties and evaluates comparatively the models discussing free parameters and their effect on the results. Proofs are provided at the end of each chapter. The book is geared to senior undergraduates with a basic understanding of linear algebra, signal processing and statistics, as well as graduate students or practitioners with experience in Kalman filtering.

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Page Count

304

Publisher

Springer Nature

Published Date

ISBN 10

3031337646

ISBN 13

9783031337642

Adaptive Filtering Under Minimum Mean p-Power Error Criterion

By: Wentao Ma,Badong Chen

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Adaptive Filtering Under Minimum Mean p-Power Error Criterion

By: Wentao Ma,Badong Chen

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Page Count

372

Publisher

CRC Press

Published Date

ISBN 10

1040015956

ISBN 13

9781040015957

Efficient Nonlinear Adaptive Filters

Design, Analysis and Applications

By: Haiquan Zhao,Badong Chen

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Efficient Nonlinear Adaptive Filters

Design, Analysis and Applications

By: Haiquan Zhao,Badong Chen

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 written to accompany a graduate/PhD course in the area of nonlinear system and adaptive signal processing.

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Page Count

271

Publisher

Springer Nature

Published Date

ISBN 10

3031208188

ISBN 13

9783031208188

Kalman Filtering Under Information Theoretic Criteria

By: Badong Chen,Lujuan Dang,Nanning Zheng,Jose C. Principe

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Kalman Filtering Under Information Theoretic Criteria

By: Badong Chen,Lujuan Dang,Nanning Zheng,Jose C. Principe

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Page Count

304

Publisher

Springer Nature

Published Date

ISBN 10

3031337646

ISBN 13

9783031337642

Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms

By: Xinghua Liu,Rui Jiang,Badong Chen,Shuzhi Sam Ge

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Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms

By: Xinghua Liu,Rui Jiang,Badong Chen,Shuzhi Sam Ge

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Write a review

Solve jigsaw puzzle

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Page Count

228

Publisher

John Wiley & Sons

Published Date

ISBN 10

111987601X

ISBN 13

9781119876014

Book's by Badong Chen

Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms

Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms

System Parameter Identification

System Parameter Identification

Adaptive Filtering Under Minimum Mean p-Power Error Criterion

Adaptive Filtering Under Minimum Mean p-Power Error Criterion

Kalman Filtering Under Information Theoretic Criteria

Kalman Filtering Under Information Theoretic Criteria

Adaptive Filtering Under Minimum Mean p-Power Error Criterion

Adaptive Filtering Under Minimum Mean p-Power Error Criterion

Efficient Nonlinear Adaptive Filters

Efficient Nonlinear Adaptive Filters

Kalman Filtering Under Information Theoretic Criteria

Kalman Filtering Under Information Theoretic Criteria

Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms

Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms

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