Creating neural models using an adaptive algorithm for optimal size of neural network and training set

An adaptive algorithm generating neural models of linear microwave components, capable of determining an optimal size of training set and network size is presented. Several waveguide and microstrip models were created and verified by comparing neural calculations to mode-matching and method of moments results of analysis of bandpass filters.