Iterative parameter estimation algorithms for dual-frequency signal models

作者：Liu Siyu; Xu Ling; Ding Feng^*

来源：Algorithms, 2017, 10(4): 118.

DOI：10.3390/a10040118

• Comparative simulation
• Dual-frequency signals
• Gradient based iterative algorithms
• Gradient search
• Iterative algorithm
• Iterative parameter estimation
• Moving data window
• Nonlinear functions

This paper focuses on the iterative parameter estimation algorithms for dual-frequency signal models that are disturbed by stochastic noise. The key of the work is to overcome the difficulty that the signal model is a highly nonlinear function with respect to frequencies. A gradient-based iterative (GI) algorithm is presented based on the gradient search. In order to improve the estimation accuracy of the GI algorithm, a Newton iterative algorithm and a moving data window gradient-based iterative algorithm are proposed based on the moving data window technique. Comparative simulation results are provided to illustrate the effectiveness of the proposed approaches for estimating the parameters of signal models.

• 单位
  江南大学