A multi-innovation generalized extended stochastic gradient algorithm for output nonlinear autoregressive moving average systems

作者：Hu Yuanbiao^*; Liu Baolin; Zhou Qin

来源：Applied Mathematics and Computation, 2014, 247: 218-224.

DOI：10.1016/j.amc.2014.08.096

• Parameter estimation
• Recursive identification
• Gradient algorithm
• Nonlinear system

This paper proposes a generalized extended stochastic gradient (GESG) algorithm for estimating the parameters of a class of Wiener nonlinear autoregressive moving average systems using the gradient search. In order to improve the convergence rates of the GESG algorithm, a multi-innovation GESG algorithm is derived. The simulation results indicate that the proposed algorithms can effectively estimate the parameters of a class of output nonlinear systems.

• 出版日期2014-11-15
• 单位中国地质大学（北京）