We present a piecewise-polynomial based associated transform algorithm (PWPAT) for macromodeling nonlinear circuits in system-level circuit design. The generated reduced model can provide both global and local accuracies with the most compact dimension. Numerical examples compare it with existing algorithms and verify its superior accuracy in higher order harmonics simulation over traditional Trajectory Piecewise-Linear (TPWL) approach.

We present a new and fast way of computing the projection matrices serving high-order Volterra transfer functions in the context of (weakly and strongly) nonlinear model order reduction. The novelty is to perform, for the first time, the association of multivariate (Laplace) variables in high-order multiple-input multiple-output (MIMO) transfer functions to generate the standard single-s transfer functions. The consequence is obvious: instead of finding projection subspaces about every si, only that about a single s is required. This translates into drastic saving in computation and memory, and much more compact reduced-order nonlinear models, without compromising any accuracy.