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International Journal of Computational Cognition (ISSN 1542-5908(online); ISSN 1542-8060(print))

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Volume 4, Number 2, June 2006.

The discipline of intelligent systems has evolved towards its critical goal of embedding non-computable human sensations, perceptions and creativity into machines in 21st century. This critical goal can only be achieved with the help of a new engineering paradigm called machinself(from machine itself). Before building a machinself we need to build cognition systems into machines; namely, to invent a computational cognition. This is a multidisciplinary challenge. 

The primary objective of The International Journal of Computational Cognition (ISSN 1542-5908(online); ISSN 1542-8060(print)) is to provide a forum for an interdisciplinary audience, a forum accessible and affordable to scientists, educators, students and engineers.  It encourages readers to contribute their thoughts and experiences. With its peer-reviewed format and its traditional paper and e-paper forms, it services the scientific and engineering community as an easy and simple platform for developing the understandings and applications of advanced studies of creative and intelligent systems. 

Rakesh K. Arya , Approximations of Mamdani Type Multi-Fuzzy Sets Fuzzy Controller by Simplest-Fuzzy Controller, International Journal of Computational Cognition, vol.4, no.2, June 2006, pages 35-47.  [full-text pdf file] [References] .

REFERENCES

[1] Bezine, Hale, Derbel, Nabil, Alime, Adel M., “Fuzzy Control of Robotic Manipulator: Some Issue on Design and Rule Base Size Reduction,” Engineering Application of Artificial Intelligence, Vol. 15, pp. 401-416, 2002.
[2] Ciliz, M. Kemal, “Rule Base Reduction for Knowledge Based Fuzzy Controller with Application to Vacuum Cleaner,” Expert System with Applications, Vol. 28, pp 175-184, 2005.
[3] Hampel, Rainer, Chaker, Nasredin, “Minimizing the Number of Variable Parameters for Optimizing the Fuzzy Controller,” Fuzzy Sets and Systems, Vol. 100, pp. 131-142, 1998.
[4] Moser, Bernhard, Navarata, Mirko, “Fuzzy Controllers with Conditionally Firing Rules,” IEEE Trans. of Fuzzy Systems, Vol. 10, no. 3, pp. 340-349, 2002.
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[6] Patel, Ambalal V., Mohan, B. M., “Analytical Structure and Analysis of Simplest Fuzzy PI Controller,” Automatica, Vol. 38, Issue 6, pp. 981-993, 2002.
[7] Rakesh K. Arya , R. Mitra and Vijay Kumar, “Approximations of Large Rule Takagi-Sugeno Fuzzy Controller by Four Rule Takagi-Sugeno Fuzzy Controller”, Proceedings of IEEE Conference on Cybernetics and Intelligent Systems CIS-04, Vol. 3, pp 1340-1345, 1-3 Dec., Singapore, 2004.
[8] Rakesh K. Arya, R. Mitra and Vijay Kumar, “A New Robust Fuzzy Controller for Nonlinear and Large Dead Time Systems”, IEICE Transactions on Fundamentals/Special Sections on Nonlinear Analysis and Applications”, Vol. E-88-A, no. 10, pp. 2527-2534, October 2005.
[9] Rakesh K. Arya, R. Mitra and Vijay Kumar, “Approximations of Large Rule Fuzzy Controller by Simplest Fuzzy Controller”, Proceedings of IEEE International Conference of Fuzzy System FUZZ-04, Vol.3 pp 1239-1244, Hungary Budapest, 2004.
[10] Tadanari Taniguchi, Kazuo Tanaka, Hiroshi Ohtake, Hua O. Wang, “Model Construction, Rule Reduction, and Robust Compensation for Generalized Form of TKS Fuzzy Systems,” IEEE Trans. on Fuzzy Systems, Vol. 9, no. 4, pp. 525-538, 2001.
[11] Wang, S. V., Hamouda, A. M. S., “Optimization of Fuzzy Rules Design Using Genetic Algorithms,” Advance in Engineering Software, Vol. 31, pp. 251-262, 2000.
[12] Ying, H., ”A Fuzzy Controller with Linear Control Rules is the Sum of a Global Two-dimensional Multilevel Relay and a Local Nonlinear Proportional-Integral Controller,” Automatica, Vol. 29, pp. 499-505, 1993.
[13] Ying, H., “A Fuzzy Controller with Linear Control Rules is the Sum of a Global Two-dimensional Multilevel Relay and a Local Nonlinear Proportional-Integral Controller,” Automatica, Vol. 29, pp. 499-505, 1993.
[14] Ying, H., “Fuzzy Control and Modeling: Analytical foundations and applications,” IEEE press, 2000.
[15] Zadeh, L. A., “Fuzzy sets,” Information and Control, Vol. 8, pp. 338-353, 1965.
[16] Zeng, Xiao-Jun, Singh, Madan G., “Approximation Theory of Fuzzy Systems-SISO Case,” IEEE Trans. on Fuzzy Systems, Vol. 2, no. 2, pp. 162-194, 1994.
[17] Zeng, Xiao-Jun, Singh, Madan G., “Approximation Theory of Fuzzy Systems-MIMO Case,” IEEE Trans. on Fuzzy Systems, Vol. 3, no.2, pp. 219-235, 1995.

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