Projection Recurrent Neural Network Model: A New Strategy to Solve Weapon-Target Assignment Problem

摘要

In the present research, we are going to obtain the solution of the Weapon-Target Assignment (WTA) problem. According to our search in the scientific reported papers, this is the first scientific attempt for resolving of WTA problem by projection recurrent neural network (RNN) models. Here, by reformulating the original problem to an unconstrained problem a projection RNN model as a high-performance tool to provide the solution of the problem is proposed. In continuous, the global exponential stability of the system was proved in this research. In the final step, some numerical examples are presented to depict the performance and the feasibility of the method. Reported results were compared with some other published papers.