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This paper presents an overview of emerging artificial neural network (ANN) techniques and applications for electromagnetic (EM) simulation and design. Accurate time domain EM modeling using recurrent neural networks (RNNs) is reviewed. Advanced robust training algorithm combining particle swarm optimization (PSO) and quasi-Newton method is described through frequency domain EM modeling, showing its...
Multi-target detection is crucial in modern warfare. It is challenging to distinguish radar returns of multiple, separate targets from those of multiple reflection points on a single target. Methods developed so far use straightforward discrimination, which is computationally complex. In this paper, we propose ideas to detect multi-targets by using electromagnetic modeling and neural networks (NNs)...
We present a new technique for training microwave neural network models. The proposed technique combines quasi-Newton algorithm with a recent global optimization algorithm called Particle Swarm Optimization (PSO). The quasi-Newton process for searching optimal solutions is incorporated into PSO to speed up local search, while the PSO performs global search avoid being trapped in local minima of training...
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