Modeling of eye diagram height in high-speed links via support vector machine

This paper presents a preliminary application of the support vector machine regression to the modeling of the eye diagram heights in high speed links for design and optimization purposes. The support vector machine regression is applied to generate a compact surrogate model of the eye diagram heights at a specific node of the link from a set of randomly selected training samples. The surrogate can be suitably adopted both for design optimization and for stochastic analysis. The feasibility and accuracy of the surrogate model calculated via the support vector machine regression are investigated on a realistic high-speed communication channel.