Fuchun Sun – författare

This book adopts a systematic view of the control systems in cyber-physical systems including the security control of the optimal control system, security control of the non-cooperative game system, quantify the impact of the Denial-of-Service attacks on the optimal control system, and the adaptive security control of the networked control systems. Because the cyber-physical system is a hybrid system, it adopts cross layer approach to handle the security control of the CPS. It presents a number of attack models according to the attack scenario and defense facilities, and a number of cross-layer co-design methodologies to secure the control of CPS.

This book adopts a systematic view of the control systems in cyber-physical systems including the security control of the optimal control system, security control of the non-cooperative game system, quantify the impact of the Denial-of-Service attacks on the optimal control system, and the adaptive security control of the networked control systems. Because the cyber-physical system is a hybrid system, it adopts cross layer approach to handle the security control of the CPS. It presents a number of attack models according to the attack scenario and defense facilities, and a number of cross-layer co-design methodologies to secure the control of CPS.

This book constitutes the refereed proceedings of the Third International Conference on Cognitive Systems and Signal Processing, ICCSIP2016, held in Beijing, China, in December 2016.

This book introduces the challenges of robotic tactile perception and task understanding, and describes an advanced approach based on machine learning and sparse coding techniques. Further, a set of structured sparse coding models is developed to address the issues of dynamic tactile sensing. The book then proves that the proposed framework is effective in solving the problems of multi-finger tactile object recognition, multi-label tactile adjective recognition and multi-category material analysis, which are all challenging practical problems in the fields of robotics and automation. The proposed sparse coding model can be used to tackle the challenging visual-tactile fusion recognition problem, and the book develops a series of efficient optimization algorithms to implement the model. It is suitable as a reference book for graduate students with a basic knowledge of machine learning as well as professional researchers interested in robotic tactile perception and understanding, andmachine learning.

This two-volume set (CCIS 1005 and CCIS 1006)  constitutes the refereed proceedings of the 4th International Conference on Cognitive Systems and Signal Processing, ICCSIP2018, held in Beijing, China, in November and December 2018.

The 96 revised full papers presented were carefully reviewed and selected from 169 submissions. The papers are organized in topical sections on vision and image; algorithms; robotics; human-computer interaction; deep learning; information processing and automatic driving.

This two-volume set (CCIS 1005 and CCIS 1006)  constitutes the refereed proceedings of the 4th International Conference on Cognitive Systems and Signal Processing, ICCSIP2018, held in Beijing, China, in November and December 2018.

The 96 revised full papers presented were carefully reviewed and selected from 169 submissions. The papers are organized in topical sections on vision and image; algorithms; robotics; human-computer interaction; deep learning; information processing and automatic driving.

Over the next few decades, millions of people, with varying backgrounds and levels of technical expertise, will have to effectively interact with robotic technologies on a daily basis. This means it will have to be possible to modify robot behavior without explicitly writing code, but instead via a small number of wearable devices or visual demonstrations. At the same time, robots will need to infer and predict humans’ intentions and internal objectives on the basis of past interactions in order to provide assistance before it is explicitly requested; this is the basis of imitation learning for robotics.

This book introduces readers to robotic imitation learning based on human demonstration with wearable devices. It presents an advanced calibration method for wearable sensors and fusion approaches under the Kalman filter framework, as well as a novel wearable device for capturing gestures and other motions. Furthermore it describes the wearable-device-based and vision-based imitation learning method for robotic manipulation, making it a valuable reference guide for graduate students with a basic knowledge of machine learning, and for researchers interested in wearable computing and robotic learning.

This book constitutes the refereed post-conference proceedings of the 5th International Conference on Cognitive Systems and Signal Processing, ICCSIP 2020, held in Zhuhai, China, in December 2020.

The 59 revised papers presented were carefully reviewed and selected from 120 submissions. The papers are organized in topical sections on algorithm; application; manipulation; bioinformatics; vision; and autonomous vehicles.

The 41 revised papers presented were carefully reviewed and selected from 105 submissions. The papers are organized in topical sections on algorithm; vision; and robotics and application.