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Chaos in the fractional order Cellular Neural Network and its sychronization
Phuong Dam Thanh,Cat Pham Thuong 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
Chaos and its drive-response synchronization for a fractional-order cellular neural networks (CNN) are studied. It is found that chaos exists in the fractional-order system with six-cell. The phase sychronization of drive and response chaotic trajectories is investigated after that. These works based on lyapunov exponents (LE), lyapunov stability theory and numerical solving fractional-order system in Matlab enviroment.
Optimal Neuro Control of Robot Manipulator
Nguyen Tran Hiep,Pham Thuong Cat 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
Recently, radial basis function network (RBFN) is used quite widely when using neural networks as controllers for subjects with multiple uncertain parameters such as the robot. The most important thing when using online learning neural network system is the choice of coefficient for networks with fast convergence speed. So far this coefficient has been chosen by experience and sometimes it takes quite a long time to find a coefficient that satisfies the requirement of the controlling task. Another problem is, when finding coefficients satisfying the required study of the problem and control, we can not conclude that the optimal coefficients. This article refers to the use of genetic algorithms (GA) to find optimal learning coefficient for RBF network is used as a controller for objects whose parameters are uncertain.
Detection and Classification of Pills Moving at a Very High Speed Using a Bi-IV2 Vision System
Thi Thanh Quyen Bui,Thuong Cat Pham,Keum-Shik Hong 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
In this paper, a novel class of information?rocessing systems called Cellular Neural Networks (CNNs) is overviewed. The CNN provides solutions to some real-life problems which are difficult or time-consuming for classical digital computers. The CNN has emerged as a powerful and practically realizable paradigm of multidimensional, locally connected, nonlinear processor arrays. We will introduce a brief concept, mathematical description of CNN, and develop an application of CNN in the ultra-high frame-rate image processing: detection and classification of pills moving at a very high speed using the Bi-IV2 vision system. We also show you our experiment setup in the laboratory, and then experimental results are introduced. The classification is based on the size and shape parameters of different pills and possible missing parts are identified. The implementation of pills classification algorithm runs on Bi-IV2, the program to be run on Bi-IV2 is loaded over Ethernet, and the host computer PC can write/read data to/from the Bi-IV2 over Ethernet.