Neural Networks and Learning Systems II
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Network Science".
Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 16251
Special Issue Editors
Interests: bifurcation; memristor circuits; memristors; chaos; nonlinear dynamical systems; oscillators; Chua's circuit; Hopfield neural nets; Lyapunov methods; asymptotic stability; cellular neural nets; convergence; coupled circuits; hysteresis; piecewise linear techniques; stability; synchronization; time-varying networks; neural nets; circuit stability
Special Issues, Collections and Topics in MDPI journals
Interests: complex networks; control systems, robotics and automation; nonlinear dynamics
Special Issue Information
Dear Colleagues,
In recent decades, systems based on artificial neural networks and machine learning devices have become increasingly present in everyday life. Artificial intelligence is considered one of the most useful tools in data analysis and decision making. The fields of application involve all sectors of our life, including medicine, engineering, economy, manufacturing, and so on. In this context, the importance of research based on artificial neural network systems is evident, and for these reasons, some disciplines related to this topic are rapidly growing in terms of project financing and research scope. As a result, part of the scientific community is devoted to investigating learning machines and artificial neural network systems from a point of view of their application and theory, which is fundamental in order to provide validation for mathematical models.
The main goal of this Special Issue is to collect papers regarding state-of-the-art and the latest studies on neural networks and learning systems. Moreover, it is an opportunity to provide a place where researchers can share and exchange their views on this topic in the fields of theory, design, and applications. The area of interest is wide and includes several categories such as stability and convergence analysis, learning algorithms, artificial vision, and speech recognition.
Prof. Dr. Luca Pancioni
Dr. Giacomo Innocenti
Prof. Dr. Fernando Corinto
Guest Editors
Manuscript Submission Information
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Keywords
- neural networks
- neurons
- stability
- circuit theory
- nonlinear systems
- synchronization
- network topology
- couplings
- convergence
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