Computational Mathematics and Neural Systems

Dear Colleagues,

The Special Issue, Computational Mathematics and Neural Systems, of MDPI is devoted to exploring the latest advancements in the field of computational techniques for solving forward and inverse problems. The real world offers numerous application problems of interest in several fields. Mathematical modelling is the first step to handle real-world problems. Translating application problems into suitable mathematical formulations entails some issues. The derived models are often complex, and they require numerical techniques able to provide the originating application with insightful answers, especially in the presence of uncertainty. Another important aspect that cannot be neglected nowadays is the explosive growth of available data. This has motivated research on artificial neural systems, in several versions, over the last decades. Such kinds of computing systems seem to be able to address the modelling and numerical issues, at least to some extent, in some contexts.

This Special Issue aims at bringing together the above-mentioned areas of investigation from a broader perspective. Topics of interest include, but are not restricted to fractional systems, uncertain systems, biological neural network modelling, computational learning theory, and analysis of network dynamics applications.

Dr. Stefania Tomasiello
Dr. Carla M.A. Pinto
Dr. Ivanka Stamova
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.