Advances in Fractional-Order Neural Networks, Volume II
This special issue belongs to the section "Complexity".
Special Issue Information
Dear Colleagues,
Fractional-order neural network models have become an active research subject and have attracted increasing attention in many fields. For instance, fractional-order neural networks are recognized as effective tools for modeling, validation, and guaranteed learning of dynamical processes in biology, biochemistry, neurocomputing, engineering, physics, economics, etc. Advances in fractional calculus lead to the development of new fractional-order neural network models. On the other side, challenges and knowledge from research in science and engineering motivate new advancements in the area of fractional-order neural networks.
Following the successful production of Volume I of this Special Issue, we are pleased to invite investigators to contribute original research articles as well as review articles focused on the latest achievements in modeling, control, and applications of fractional-order neural networks.
Dr. Ivanka Stamova
Dr. Gani Stamov
Prof. Dr. Xiaodi Li
Guest Editors
Manuscript Submission Information
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Keywords
- fractional cellular neural networks
- fractional Hopfield neural networks
- fractional bidirectional associate memory neural network
- fractional neural networks with reaction-diffusion terms
- fractional Lotka–Volterra neural networks
- fractional Cohen–Grossberg neural networks
- fractional gene regulatory neural networks
- delayed fractional neural network models
- impulsive fractional neural models
- uncertain fractional neural networks
- modeling qualitative theory (stability, periodicity, almost periodicity, oscillation theory)
- control stabilization applications to real-world phenomena
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Published Papers
Fractal Fract. - ISSN 2504-3110