THE EVOLVING ADAPTIVE NEURAL NETWORK FOR DATA PROCESSING WITH MISSING OBSERVATIONS

A. Shafronenko, I. Pliss, Ye. Bodyanskiy

Abstract


The problem of computational intelligence systems synthesis in on-line mode, capable for processing stochastic signals with missing observations in the data is considered. An adaptive approach based on using of orthogonal polynomials is developed.

Keywords


neural network, orthogonal polynomials, Chebyshev polynomials, incomplete data with missing observations

References


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GOST Style Citations






DOI: https://doi.org/10.15588/1607-3274-2013-2-19



Copyright (c) 2014 A. Shafronenko, I. Pliss, Ye. Bodyanskiy

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