Machine Behavior Design And Analysis - Li, Shuai
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Présentation Machine Behavior Design And Analysis de Li, Shuai Format Relié
- Livre Littérature Générale
Résumé : Chapter 1: Introduction to Collective Machine Behavior.-  ...
Biographie:
Yinyan Zhang received his B.E. degree from Sun Yat-sen University, Guangzhou, China and Ph.D. degree from the Hong Kong Polytechnic University, Hong Kong SAR, China. He was a Postdoctoral Fellow with the Department of Computing, Hong Kong Polytechnic University. Currently, he is a Professor with the College of Cyber Security, Jinan University, Guangzhou, China. His main research interests include multi-agent systems, intelligent control, robotics, and security and control of cyber-physical systems. He has published more than 40 scientific papers as an author or co-author, including 20 IEEE transaction papers. Shuai Li received his B.E. degree in Precision Mechanical Engineering from Hefei University of Technology, China in 2005, his M.E. degree in Automatic Control Engineering from the University of Science and Technology of China in 2008, and his Ph.D. in Electrical and Computer Engineering from the Stevens Institute of Technology, USA in 2014. He iscurrently affiliated with the School of Engineering, Swansea University, UK. His main research interests include neural networks, robotics, control of networked systems, computation and optimization. He has been working on the research and application of neural networks/dynamics for more than 10 years, and has published more than 100 scientific papers. In addition, he is now serving as an associate editor of the International Journal of Advanced Robotic Systems, Frontiers in Neurorobotics, Neural Processing Letters, and Journal of Rehabilitation Robotics, and as an editorial board member for the International Journal of Distributed Sensor Networks and Neural Computation & Applications....
Sommaire:
Chapter 2: Second-Order Min-Consensus.- Chapter 3: Consensus of High-Order Discrete-Time Multi-Agent Systems.- Chapter 4: Continuous-Time Biased Min-Consensus.- Chapter 5: Discrete-Time Biased Min-Consensus.- Chapter 6: Biased Consensus Based Distributed Neural Network.- Chapter 7: Predictive Suboptimal Consensus.- Chapter 8: Adaptive Near-Optimal Consensus.
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