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Honghe, China

Yin Y.,East China Institute of Technology | Xu D.,East China Institute of Technology | Huang X.,Honghe University
Information Sciences | Year: 2011

This paper provides a continuation of the idea presented by Yin et al. [Yin et al., Some scheduling problems with general position-dependent and time-dependent learning effects, Inform. Sci. 179 (2009) 2416-2425]. For each of the following three objectives, total weighted completion time, maximum lateness and discounted total weighted completion time, this paper presents an approximation algorithm which is based on the optimal algorithm for the corresponding single-machine scheduling problem and analyzes its worst-case bound. It shows that the single-machine scheduling problems under the proposed model can be solved in polynomial time if the objective is to minimize the total lateness or minimize the sum of earliness penalties. It also shows that the problems of minimizing the total tardiness, discounted total weighted completion time and total weighted earliness penalty are polynomially solvable under some agreeable conditions on the problem parameters. © 2011 Elsevier Inc. All rights reserved. Source

Yang X.,Honghe University | Zhu Q.,Ningbo University | Huang C.,Changsha University of Science and Technology
Nonlinear Analysis: Real World Applications | Year: 2011

Chaotic systems in practice are always influenced by some unknown factors, which may make the chaotic behavior completely different from that of unaffected system. In this paper, generalized lag-synchronization for a general class of coupled chaotic systems with mixed delays, uncertain parameters, as well as external perturbations is investigated. A simple but all-powerful robust adaptive controller is designed to achieve this goal. Based on Lyapunov stability theory, integral inequality and Barbalat lemma, rigorous proofs are given for the asymptotic stability of the error systems of the coupled systems with or without external perturbations. Sufficient conditions for inaccuracy or accuracy estimation of unknown parameters are also given. Moreover, the designed adaptive controller has better anti-interference capacity than those of references. Numerical simulations verify the effectiveness of the theoretical results. © 2010 Published by Elsevier Ltd. All rights reserved. Source

Xu H.,Honghe University
Journal of Convergence Information Technology | Year: 2012

Mathematical basis of Hidden Markov Modeling (HMM) are presented. For the proposed application that is 2-Dimensional pattern classification, a set of ergodic continuous observation HMMs were constructed, each of them corresponding to one pattern. To classify the patterns, particular combinations of 2-D DCT coefficients have been employed for feature vectors. Forward-backward algorithm and Vitterbi formulation are explained for evaluation of models. Initial parameters were estimated via a K-means clustering algorithm and then reestimated by EM (Expectation Modification) algorithm from a multi-observation training set. To see how well this modeling can help us to successfully detect the patterns, Learning Vector Quantization and Template Matching were implemented and compared. The results show that this approach does not seem hopeful for this application. Source

Sun J.,Honghe University
2nd International Workshop on Education Technology and Computer Science, ETCS 2010 | Year: 2010

Technology is making a significant impact on modern education. Computer technology has been proposed to serve education in many papers. However, more and more teachers are complaining that students spend more time on the Internet rather than learning. It is the most head-breaking problem to parent that children addict to the Internet. Many people are going to extreme on coping with the main negative impact of the computer technology on education. In this paper, the author will present the impact of computer technology on modern education first. Then we will focus on discussing the strategies about how to cope with the negative impact of computer technology on education. And some suggestions will be proposed in this paper. © 2010 IEEE. Source

Yang X.,Honghe University | Cao J.,Nanjing Southeast University | Lu J.,Nanjing Southeast University
IEEE Transactions on Neural Networks and Learning Systems | Year: 2012

In this paper, a general model of coupled neural networks with Markovian jumping and random coupling strengths is introduced. In the process of evolution, the proposed model switches from one mode to another according to a Markovian chain, and all the modes have different constant time-delays. The coupling strengths are characterized by mutually independent random variables. When compared with most of existing dynamical network models which share common time-delay for all modes and have constant coupling strengths, our model is more practical because different chaotic neural network models can have different time-delays and coupling strength of complex networks may randomly vary around a constant due to environmental and artificial factors. By designing a novel Lyapunov functional and using some inequalities and the properties of random variables, we derive several new sufficient synchronization criteria formulated by linear matrix inequalities. The obtained criteria depend on mode-delays and mathematical expectations and variances of the random coupling strengths as well. Numerical examples are given to demonstrate the effectiveness of the theoretical results, meanwhile right-continuous Markovian chain is also presented. © 2012 IEEE. Source

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