Modeling nonlinear circuits with linearized dynamical models via kernel regression

Abstract

This paper introduces a novel method for the solution of guitar distortion circuits based on the use of kernels. The proposed algorithm uses a kernel regression framework to linearize the inherent nonlinear dynamical systems created by such circuits and proposes data and kernel selection algorithms well suited to learn the required regression parameters. Examples are presented using the One Capacitor Diode Clipper and the Common-Cathode Tube Amplifier.