Download Adaptive and Natural Computing Algorithms: 8th International by Sarunas Raudys (auth.), Bartlomiej Beliczynski, Andrzej PDF

By Sarunas Raudys (auth.), Bartlomiej Beliczynski, Andrzej Dzielinski, Marcin Iwanowski, Bernardete Ribeiro (eds.)

The quantity set LNCS 4431 and LNCS 4432 constitutes the refereed complaints of the eighth foreign convention on Adaptive and ordinary Computing Algorithms, ICANNGA 2007, held in Warsaw, Poland, in April 2007.

The 178 revised complete papers offered have been conscientiously reviewed and chosen from a complete of 474 submissions. The ninety four papers of the 1st quantity are geared up in topical sections on evolutionary computation, genetic algorithms, particle swarm optimization, studying, optimization and video games, fuzzy and tough structures, simply as type and clustering. the second one quantity includes eighty four contributions concerning neural networks, help vector machines, biomedical sign and picture processing, biometrics, machine imaginative and prescient, in addition to to regulate and robotics.

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Read Online or Download Adaptive and Natural Computing Algorithms: 8th International Conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007, Proceedings, Part II PDF

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Additional info for Adaptive and Natural Computing Algorithms: 8th International Conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007, Proceedings, Part II

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1 Introduction The scope of applications of mathematical models in the industrial systems is very broad and includes the design of the systems, the control and the system diagnosis [1,2,5,8]. As the most of industrial systems exhibit a non-linear behaviour, this has been the main reason for further development of non-linear system identification theory such as the Artificial Neural Networks (ANNs) [3]. They enable to model the behaviour of complex systems without a priori information about the system structure or parameters.

Cholewa, W. ): Fault Diagnosis. Models, Artificial Intelligence, Applications, Springer-Verlag, Berlin (2004) 6. , Walter, E. ): Bounding Approaches to System Identification, Plenum Press, New York (1996) 7. D. Thesis, University of Zielona G´ora, Zielona G´ora (2004) (In Polish) 8. : Advances in Model-based Fault Diagnosis with Evolutionary Algorithms and Neural Networks. Int. Journal of Applied Mathematics and Computer Science. 16 (2006) 85–99 9. : A GMDH neural network based approach to robust fault detection and its application to solve the DAMADICS benchmark problem.

Fast homogeneous algorithms of cosine transforms, type II and III with tangent multipliers. (in Polish) Automatics 7 AGH University of Science and Technology Press, Cracow (2003) 727-741 10. : Recursive learning of fast orthogonal neural networks. In: Proc. of the International Conf. on Signals and Electronic Systems. (2006) 653-656 11. : Methods and techniques of artificial intelligence. (in Polish) Polish Scientific Publishers PWN (2005) 12. edu]. jp 1 Abstract. Nonlinearity is an important factor in the biological visual neural networks.

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