Radiation Pattern Synthesis of the Coupled Almost Periodic Antenna Arrays Using Artificial Neural Network ANN Model

This paper proposes a radiation pattern synthesis of the almost periodic antenna arrays including mutual coupling effects (that extracted by the Floquet analysis according to our previous work), which principally has a high directivity and large bandwidth. For modeling the given structures, the moment method combined with the Generalized Equivalent Circuit (MoM-GEC) is proposed. The artificial neural network (ANN) as a powerful computational model has been successfully applied to the antenna array pattern synthesis. The results showed that the multilayer feedforward neural networks are rugged and can successfully and efficiently resolve various distinctive complex almost periodic antenna patterns (with different source amplitudes) (in particular, both periodic and randomly aperiodic structures are taken into account). However, the artificial neural network (ANN) is capable of quickly producing the synthesis results using generalization with the early stopping (ES) method. A significant time gain and memory consumption are achieved by using this given method to improve the generalization (called early stopping). To justify this work, several examples are developed and discussed.

Weyl almost periodic solutions for quaternion-valued shunting inhibitory cellular neural networks with time-varying delays

<abstract><p>We consider the existence and stability of Weyl almost periodic solutions for a class of quaternion-valued shunting inhibitory cellular neural networks with time-varying delays. In order to overcome the incompleteness of the space composed of Weyl almost periodic functions, we first obtain the existence of a bounded continuous solution of the system under consideration by using the fixed point theorem, and then prove that the bounded solution is Weyl almost periodic by using a variant of Gronwall inequality. Then we study the global exponential stability of the Weyl almost periodic solution by using the inequality technique. Even when the system we consider degenerates into a real-valued one, our results are new. A numerical example is given to illustrate the feasibility of our results.</p></abstract>