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Special Session 1
Recurrent neural network for computing and its robot applications

Abstract: In the past few years, we have seen great advances in intelligent computing in various fields, which thanks to the use of intelligent computing technologies such as neural network models, neuro-dynamics, evolutionary computing, as well as other computational methods inspired by biological behavior. Among them, recurrent neural network (RNN), as an improved neural network, has brought great breakthroughs in the field of robotics with its robust computing and learning capabilities. Motion generation in robotics refers to the control and planning of robots, which involves the use of various sensing devices to perceive motion data. Through the combination of data-driven control and neural network learning system, better guidance of robot movement has become a research hotspot. In addition, among the numerous applications of robots, rehabilitation robot is an important research direction. How to build an accurate network system to better estimate the movement intention of the patient/body is a very important key technology in the current research. Although RNN has been greatly developed today, it is still a challenging topic to solve the gradient explosion problem caused by long sequence modeling, further improve its calculation accuracy and reduce its computational complexity, especially in combination with the potential of data-driven and engineering applications. Based on this perspective, the main objective of the special session of the 11th International Conference on Intelligent Control and Information Processing is dedicated to promote research, sharing and development of neural networks in the field of robot control, which including theoretical and experimental research as well as practical applications in the entire society.

Keywords: Recurrent neural networks; Robotics; Intelligent computing

In this special session, we expect to contribute 6-7 articles on recurrent neural network for computing and its applications.

Organizer:

Yang Shi shiy@yzu.edu.cn
School of Information Engineering
Yangzhou University, Yangzhou, China

Special Session 2
Recurrent neural network for signal processing and its applications

Abstract: During the past few years, we have seen numerous advances in intelligent control and information processing in various fields, which thanks to the use of intelligent control and information processing techniques such as neural network models, learning and adaptive control, optimization-based and optimal control, process control, robot control, as well as other methods inspired by machine learning, signal processing, parallel and distributed processing. Among them, recurrent neural network, as an advanced neural network, has brought interesting results in the field of industrial fields and rehabilitation medicine fields with its effective computing and learning capabilities. Path planning in robotics refers to the control robots, and rehabilitation training in bio-medicine refers to the human-machine interactive, which involve the use of various sensing devices to obtain the corresponding data. The data-driven control has been applied to the optimal path planning of robot movement, which has become a research hotspot. Furthermore, among the numerous applications of robots, flexible-driven actuator which can be applied to design a flexible-driven rehabilitation robot is a very important research direction. How to design a neural network model to estimate the movement intention of patient is an important technique in the current research. Although recurrent neural network has been great proposed, analyzed and investigated today, it is still a challenging problem to online solving time-varying problem caused by real-time requirement.

Based on this perspective, the main objective of the special session of the 11th International Conference on Intelligent Control and Information Processing Conference is dedicated to promoting research, sharing and development of neural networks in the field of intelligent control and information processing, which including theoretical and experimental research as well as practical applications in the entire society.

Keywords: Neural networks; Robotics; Intelligent control; Signal processing

In this special session, we expect to contribute 6-7 articles on recurrent neural network for signal processing and its applications.

Organizer:

Zhongbo Sun zhongbosun2012@163.com zbsun@ccut.edu.cn
Professor
Changchun University of Technology