Work place: Kharkiv National University of Radio Electronics, Kharkiv, Ukraine
E-mail: anastasiya.deineko@gmail.com
Website:
Research Interests: Computational Engineering, Engineering
Biography
Anastasiia Deineko graduated from Kharkiv National University of Radio Electronics in 2011. She is a PhD student in Computer Science at Kharkiv National University of Radio Electronics. Her current interests are
By Yevgeniy V. Bodyanskiy Oleksii K. Tyshchenko Anastasiia O. Deinekob
DOI: https://doi.org/10.5815/ijmecs.2015.02.01, Pub. Date: 8 Feb. 2015
A new neuro-fuzzy system’s architecture and a learning method that adjusts its weights as well as automatically determines a number of neurons, centers’ location of membership functions and the receptive field’s parameters in an online mode with high processing speed is proposed in this paper. The basic idea of this approach is to tune both synaptic weights and membership functions with the help of the supervised learning and self-learning paradigms. The approach to solving the problem has to do with evolving online neuro-fuzzy systems that can process data under uncertainty conditions. The results proves the effectiveness of the developed architecture and the learning procedure.
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