Neural networking study of worms in a wireless sensor model in the sense of fractal fractional
Aziz Khan, Thabet Abdeljawad, Manar A. Alqudah
Abstract
<abstract><p>We are concerned with the analysis of the neural networks of worms in wireless sensor networks (WSN). The concerned process is considered in the form of a mathematical system in the context of fractal fractional differential operators. In addition, the Banach contraction technique is utilized to achieve the existence and unique outcomes of the given model. Further, the stability of the proposed model is analyzed through functional analysis and the Ulam-Hyers (UH) stability technique. In the last, a numerical scheme is established to check the dynamical behavior of the fractional fractal order WSN model.</p></abstract>
Topics & Concepts
FractalContext (archaeology)Computer scienceWireless sensor networkArtificial neural networkStability (learning theory)MathematicsTopology (electrical circuits)Applied mathematicsMathematical analysisArtificial intelligenceComputer networkMachine learningCombinatoricsPaleontologyBiologyFractional Differential Equations SolutionsNumerical methods for differential equationsNonlinear Differential Equations Analysis