抄録
We introduce our studies on optical nonlinearity compensation schemes that are based on machine learning
technology for optical communication systems. We examine the performance of nonlinear equalization
using an artificial neural network (ANN) by comparing our scheme with others, including a support
vector machine (SVM) and the Volterra series transfer function (VSTF). We describe an SVM-based
nonlinear equalizer and our improved version. We also discuss the problem of the computational complexity
of a conventional VSTF-based nonlinear equalizer and introduce our investigation for improving
VSTF’s computational complexity
