S. Chen, S. Gunn and C. Harris, “Decision Feedbach Equalizer Design Using Support Vector Machines,” Vision, Image and Signal Processing, Vol. 147, No. 3, 2000, pp. 213-219.

has been cited by the following article:

• TITLE: Using Least Squares Support Vector Machines for Frequency Estimation

  AUTHORS: Xiaoyun Teng, Xiaoyi Zhang, Hongyi Yu

  KEYWORDS: Carrier Recovery, LS-SVM, Pattern Recognition

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.3 No.10, October 27, 2010

  ABSTRACT: Frequency estimation is transformed to a pattern recognition problem, and a least squares support vector machine (LS-SVM) estimator is derived. The estimator can work efficiently without the need of statistics knowledge of the observations, and the estimation performance is insensitive to the carrier phase. Simulation results are presented showing that proposed estimators offer better performance than traditional Maximum Likelihood (ML) estimator at low SNR, since classification-based method does not have the threshold effect of nonlinear estimation.