Neural networks are widely used learning machines with strong learning ability and adaptability, which have been extensively applied in intelligent control field on parameter optimization, anti-disturbance of random factors, etc., and neural network- based stochastic optimization and control have applications in a broad range of areas. As one of the most important control models, stochastic systems widely exist in real world, such as mobile sensor networks, multi-agent systems, unmanned aerial vehicles and aircrafts, etc. However, due to the influence of random factors, there are still many challenging issues arising from nonlinear stochastic systems. In particular, some challenges existing in the implementation and controller design which are related to neural networks, intelligent data sensing, secure information processing due to network resource constraints. As a result, it is indispensable to understand how to reliably, resiliently and safely apply neural networking technology to nonlinear stochastic systems with a large number of distributed sensors, controllers and actuators, which renders some fundamental problems regarding real-time and intelligent information processing.
The main focus of this special issue is to provide an opportunity for researchers and engineers to present their latest results in nonlinear stochastic optimization and controller design based on neural networks. We thus welcome both theoretical work and application-oriented studies. All submitted papers will be peer-reviewed and selected based on both their quality and relevance.
The list of possible topics includes, but is not limited to:
Neural-Network-based Nonlinear Stochastic Optimization
Neural-Network- based Synthesis for Nonlinear Stochastic Systems
Multi-agent Analysis for Networked Stochastic Systems
Synchronization, Consensus and Estimation for Stochastic Neural Networks
Neural Representation for Nonlinear Stochastic Systems
Novel Deep Neural Networks and Related Learning-based Methods in Nonlinear Stochastic Systems
2. Submission Guidelines
Authors should prepare their manuscripts according to the \”Instructions for Authors\” guidelines of \”Neurocomputing\” outlined in the journal website
All of the papers will be peer-reviewed following a regular reviewing procedure. Each submission should clearly demonstrate evidence of benefits to society or large communities. Originality in theory and technique and correlation to the content of this special issue will be the major evaluation criteria.
3. Important Dates
Submission Deadline: August 10, 2019
First Review Decision: October 30, 2019
Revisions Due: December 30, 2019
The acceptance deadline : May 10, 2020
Expected publication date: June 10, 2020
4. Leader Guest Editor
College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, P. R. China,
5. Guest Editors
Institute of Automation, Qufu Normal University, Qufu 273165, P. R. China,
School of Mathematics, Southeast University, Nanjing 210096, P. R. China,