DATA-BASED MODELING OF ANALOG-MIXED SIGNAL SYSTEMS IN AUTOMOTIVE APPLICATIONS WITH SUPPORT VECTOR MACHINES

摘要

Functional verification by simulation is an important step during the development of present microelectronic solutions for automotive applications. Its relevance is based on the capability to compare the behavior of a developed circuit with its specification. Since the transient simulation of application specific integrated circuits (ASICs) normally shows long runtimes, the behavior of time-critical components is manually modeled in order to speed up simulation. The present article describes a data-based approach for semi-automated generation of behavioral models for analog mixed-signal (A/MS) systems. The approach is based on support vector machines and a transformation dictionary for extraction of dynamic properties. The application of this method results in highly accurate pin-compatible behavioral models for A/MS systems with a significant reduction in simulation times. Additionally, the generated models can be easily integrated in description languages like VDHL-AMS, Verilog-AMS, Simulink and MAST. Another benefit of the proposed method consists in its flexibility to model systems of different physical domains. The emphasized properties will be illustrated by the modeling of two examples belonging to analog-digital and electromechanic systems respectively.