Using Least Squares Support Vector Machines for Frequency Estimation

• 作者: Hongyi Yu Xiaoyi Zhang Xiaoyun Teng
• 来源期刊: 通讯、网络与系统学国际期刊(英文)
• 学科: 地球科学
• 关键词: CARRIER RECOVERY LS-SVM PATTERN RECOGNITION
• 年，卷（期）: 2010,（10）
• 页码范围: 821-825
• 页数: 5页
• 分类号: P1

摘要

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.