A linear regression inverse space mapping algorithm for EM-based design optimization of microwave circuits

Summary form only given, as follows. A new simplified formulation for inverse space mapping optimization of microwave circuits is presented in this work. In contrast to previous inverse space mapping algorithms, where artificial neural networks are trained to approximate the inverse space mapping at each iteration, our approach makes use of a linear regression formulation to calculate in closed form the inverse mapping parameters at each iteration. Our technique is illustrated by the EM-based design of several microstrip circuits.