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Least Mean Square vs. Outer Bounding Ellipsoid Algorithm in Confidence Estimation of the GMDH Neural Networks

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Adaptive and Natural Computing Algorithms (ICANNGA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4432))

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Abstract

The paper deals with the problem of determination of the model uncertainty during the system identification with the application of the Group Method of Data Handling (GMDH) neural network. The main objective is to show how to employ the Least Mean Square (LMS) and the Outer Bounding Ellipsoid (OBE) algorithm to obtain the corresponding model uncertainty.

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Bartlomiej Beliczynski Andrzej Dzielinski Marcin Iwanowski Bernardete Ribeiro

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© 2007 Springer Berlin Heidelberg

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Mrugalski, M., Korbicz, J. (2007). Least Mean Square vs. Outer Bounding Ellipsoid Algorithm in Confidence Estimation of the GMDH Neural Networks. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71629-7_3

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  • DOI: https://doi.org/10.1007/978-3-540-71629-7_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71590-0

  • Online ISBN: 978-3-540-71629-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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