Abstract
A problem of learning in non-stationary environment is solved by making use of order statistics in combination with the Parzen kernel-type regression neural network. Probabilistic properties of the algorithm are investigated and weak convergence is established. Experimental results are presented.
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Jaworski, M., Er, M.J., Pietruczuk, L. (2012). On the Application of the Parzen-Type Kernel Regression Neural Network and Order Statistics for Learning in a Non-stationary Environment. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_11
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DOI: https://doi.org/10.1007/978-3-642-29347-4_11
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