Download PDF by Bernadete Ribeiro, Rudolf F. Albrecht, Andrej Dobnikar,: Adaptive and Natural Computing Algorithms: Proceedings of

By Bernadete Ribeiro, Rudolf F. Albrecht, Andrej Dobnikar, David W. Pearson, Nigel C. Steele

ISBN-10: 3211249346

ISBN-13: 9783211249345

The papers during this quantity current theoretical insights and document sensible functions either for neural networks, genetic algorithms and evolutionary computation. within the box of ordinary computing, swarm optimization, bioinformatics and computational biology contributions are not any much less compelling. a big variety of contributions document functions of neural networks to method engineering, robotics and regulate. Contributions additionally abound within the box of evolutionary computation really in combinatorial and optimization difficulties. Many papers are devoted to computing device studying and heuristics, hybrid clever structures and smooth computing purposes. a few papers are dedicated to quantum computation. additionally, kernel dependent algorithms, in a position to clear up projects except type, signify a revolution in trend acceptance bridging present gaps. extra subject matters are clever sign processing and laptop imaginative and prescient.

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Extra resources for Adaptive and Natural Computing Algorithms: Proceedings of the 7th International Conference in Coimbra, Portugal, March 21-23 2005

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Inc. George (1997) Stochastic approximation algorithms and applications, Applications of Mathematics. 35. , Bengio Y, Haffner, P. (1998) Gradient-based learning applied to document recognition. Proc. of the IEEE, vol. 86, nr. 11, 1998. [4] Spall, J. , IEEE Trans. Autom. 45, nr. 10: 1839-1853. [5] Silva, F. , Almeida, L. B. (1990),Speeding up backpropagation, Advanced Neural Computers, ed. R. Eckmiller, Elsevier Science Publishers, Amsterdam, ppl51-158. , Hemmen, van J. , (1996), Accelerating Backpropagation through Dynamic Self-Adaptation, Neural Networks, vol.

Et al. (2002), The Special Trans Function Theory of the AM Detector Transfer Factor Analytical Analysis, ICECS 9th IEEE Conference Proceedings, Dubrovnik, Croatia, pp 991994. [10] Perovich S. , Bauk S. I. (2003), The STFT Time Signal Analysis to the Nonlinear Greatz's Circuits, 7th ISSPA/IEEE Conference, Paris, France [11] Perovich S. , Bauk S. , et al. (2002), Concerning the Improvement of the Error Function of the AM Detector Transfer Factor Numerical Calculations by Special Trans Function Theory, ISSAT Conference, Anaheim, California [12] Perovich S.

21 We display in Figure 7 the 2-D data we use in our tests, in figure 8 the result of 2-D interpolation using Mexican hat WNN on which we see some distortion in amplitude and at the edges. In figure 9 using Beta 2 WNN we reduce the amplitude distortion. In figure 10 we display the result of interpolation using Mexican hat WNN on which distortion becomes greater than its homolog using Beta 2 WNN displayed in figure 11. 4 Conclusion We present two experimental results of the proposed Beta Wavelet Neural Networks (BWNN) on approximating two functions using the Stepwise selection by orthogonalization training algorithm.

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Adaptive and Natural Computing Algorithms: Proceedings of the 7th International Conference in Coimbra, Portugal, March 21-23 2005 by Bernadete Ribeiro, Rudolf F. Albrecht, Andrej Dobnikar, David W. Pearson, Nigel C. Steele


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