Novel Lagrange sense exponential stability criteria for time-delayed stochastic Cohen–Grossberg neural networks with Markovian jump parameters: A graph-theoretic approach

This paper concerns the issues of exponential stability in Lagrange sense for a class of stochastic Cohen–Grossberg neural networks (SCGNNs) with Markovian jump and mixed time delay effects. A systematic approach of constructing a global Lyapunov function for SCGNNs with mixed time delays and Markovian jumping is provided by applying the association of Lyapunov method and graph theory results. Moreover, by using some inequality techniques in Lyapunov-type and coefficient-type theorems we attain two kinds of sufficient conditions to ensure the global exponential stability (GES) through Lagrange sense for the addressed SCGNNs. Ultimately, some examples with numerical simulations are given to demonstrate the effectiveness of the acquired result

Existence, Uniqueness and Exponential Stability of Periodic Solution for Discrete-Time Delayed BAM Neural Networks Based on Coincidence Degree Theory and Graph Theoretic Method

In this work, a general class of discrete time bidirectional associative memory (BAM) neural networks (NNs) is investigated. In this model, discrete and continuously distributed time delays are taken into account. By utilizing this novel method, which incorporates the approach of Kirchhoff’s matrix tree theorem in graph theory, Continuation theorem in coincidence degree theory and Lyapunov function, we derive a few sufficient conditions to ensure the existence, uniqueness and exponential stability of the periodic solution of the considered model. At the end of this work, we give a numerical simulation that shows the effectiveness of this work

Strategy for Multifunctional Hollow Shelled Triple Oxide Mn–Cu–Al Nanocomposite Synthesis via Microwave-Assisted Technique

A facile route for assembling hollow shelled triple Mn–Cu–Al oxide nanomaterials (HMCA) using the microwave-assisted reduction technique is demonstrated, and the energy and environmental applications such as supercapacitor and photocatalyst are investigated. During the reaction time, MnO₂, CuO, and Al₂O₃ formed a shell layer over the core SiO₂ and assembled as a hollow geometrical nanostructure with a uniform size densely populated hairy outer appearance. We have shown that the resultant HMCA exhibited the synergistic effects of a nanocomposite and thereby revealed a distinctive collection of physical and chemical properties such as improved electrochemical capacitive performance capacities, enhanced photocatalytic activities, and increased adsorption. These features collectively confirmed the potential of HMCA as an attractive material for resourceful applications in environmental and energy storage issues