By Ren Xiaoping, Cai Zixing, Li Zhao, Wang Wuyi (auth.), Gary Lee (eds.)
2012 overseas convention on atmosphere technological know-how and 2012 overseas convention on desktop technological know-how (ICES 2012/ICCS 2012) may be held in Australia, Melbourne, 15‐16 March, 2012.Volume 2 comprises a few subject matters in clever method. There are fifty one papers have been chosen because the general paper during this quantity. It includes the newest advancements and displays the adventure of many researchers operating in numerous environments (universities, study facilities or perhaps industries), publishing new theories and fixing new technological problems.
The function of quantity 2 is interconnection of various medical fields, the cultivation of each attainable medical collaboration, the alternate of perspectives and the advertising of recent learn goals in addition to the extra dissemination, the diffusion of clever process, together with yet now not constrained to clever process, Neural networks, computer studying, Multimedia approach and functions, Speech Processing, photo & video sign Processing and Computer‐Aided community layout the dispersion.
We are certain that the efforts of the authors in addition to the reviewers to supply excessive point contributions might be preferred via the suitable clinical group. we're confident that offered quantity can be a resource of data and proposal for all educational participants, researchers and practitioners operating in a box of the subject coated by means of the book.
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Additional resources for Advances in Intelligent Systems: Selected papers from 2012 International Conference on Control Systems (ICCS 2012), March 1-2, Hong Kong
Fig. 1. Output tracking performance 5 Conclusion In this paper, an adaptive neural network control approach is proposed for a class of strict-feedback nonlinear time-delay systems, with both unknown nonlinearities and uncertain disturbances. The unknown time delay functions are approximated by neural networks, such that the requirement on unknown time delay functions is relaxed. The uncertain disturbances are solved by nonlinear damping technique. Finally, a numerical simulation is given to show the effectiveness of the approach.
1001–1006 (1992) 5. : Out-of-control pattern recognition and analysis for quality control charts using lisp-based systems. Computers & Industrial Engineering 28, 81–91 (1995) 6. : A neural network based model for abnormal pattem recognition of control charts. Computers & Industrial Engineering 36, 97–108 (1999) 7. : Control chart pattern recognition using back propagation artificial neural networks. International Journal of Production Research 39, 3399–3418 (2001) 8. : Recognizing control chart patterns with neural network and numerical fitting.
To economically generate the data to train and test the Multi-class SVM used for control charts pattern recognition, this paper use Monte-Carlo simulation method to produce the required data sets. In this research, the six different pattern data sets for training and testing are simulated using Equation (1). (1) For normal pattern, y (t ) = x(t ) , where x(t ) ~ N (0 ,1) . (2) For cyclic pattern, y (t ) = a × sin(2πt Ω ) + x(t ) where, a is cycle amplitude in terms of σ, σ ≤ a ≤ 3σ , in this paper.