Modeling stripline discontinuities by neural network with knowledge-based neurons

Abstract

A three-layer neural network with knowledge-based neurons in the hidden layer (NNKBN) is presented for modeling stripline discontinuities. In NNKBN, prior knowledge for stripline discontinuity is incorporated into each hidden neuron. With knowledge-based neurons, the learning ability and generalization of the neural network are improved. Compared with conventional multi-layer perceptron neural network, the NNKBN can map the input-output relationships with fewer hidden neurons and has higher reliability for extrapolation beyond training data range. Two examples are given to illustrate the potential power of this approach.