Dynamically Predicting Wi-Fi Coverage Mapping Using Bioinspired Neural Networks

Abstract

Neural networks have applications in many areas, including biomedicine, robotics, telecommunications, image processing, etc. Differential equations play an essential role in solving challenges in the physical world. All this encourages researchers to develop various neural network systems to address problems for which analytical solutions may not be available. Our paper explains how to use a bio-inspired neural network as a solver for systems of differential equations. Wave propagation problems within computational simulations are presented. Applications of the obtained results to Wi-Fi coverage prediction problems are considered.