Automated Model Generation of Analog Circuits Through Modified Trajectory Piecewise Linear Approach With ChebyShev Newton Interpolating Polynomials

In this paper we propose an efficient scalability
approach for the trajectory piecewise linear (TPWL)
macromodels through the utilization of Chebyshev
interpolating polynomials in each piecewise region. The
scalability achieved is in two dimensions (2D) that mainly
improve the local approximation properties of TPWL
macromodels. Horizontal scalability is achieved by decreasing the number of linearization points along the trajectory;vertical scalability is obtained by extending the range of macromodel to predict the response of a nonlinear system for inputs far from training trajectory. In this way more efficient macromodels are obtained in terms of simulation speed up of complex nonlinear systems. We provide the implementation details and illustrate the 2D scalability concept with an example using nonlinear transmission line.