Some Stochastic Gradient Algorithms for Hammerstein Systems with Piecewise Linearity

2020 ◽  
Author(s):  
Yan Pu ◽  
Yongqing Yang ◽  
Jing Chen
Keyword(s):  
Stochastic Gradient ◽  
Hammerstein Systems ◽  
Gradient Algorithms ◽  
Piecewise Linearity

Identification of Hammerstein Systems with Two-Segment Preload Nonlinearity Based on the Gradient Search

2014 ◽  
Vol 651-653 ◽  
pp. 2314-2317 ◽  
Author(s):  
Hong Fen Zou
Keyword(s):  
Convergence Rate ◽  
Special Form ◽  
Approximation Theorem ◽  
Stochastic Gradient ◽  
Gradient Algorithm ◽  
Gradient Search ◽  
Unknown Parameters ◽  
Hammerstein System ◽  
Hammerstein Systems ◽  
Stochastic Gradient Algorithm

This paper deals with the parameter identication problem for Hammerstein systems with two-segment preload nonlinearity. Taking into account the complexity of Hammerstein systems, we use theWeierstrass approximation theorem to convert a Hammerstein system into a special form that has linear-in-parameters, and propose a stochastic gradient algorithm to estimate all unknown parameters of Hammerstein systems. Furthermore, a modified stochastic gradient algorithm is given to improve the convergence rate. The applicability of the approach is illustrated by a simulation example.

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