scholarly journals Asymptotic bias of stochastic gradient search

2017 ◽  
Vol 27 (6) ◽  
pp. 3255-3304 ◽  
Author(s):  
Vladislav B. Tadić ◽  
Arnaud Doucet
Keyword(s):  
Stochastic Gradient ◽  
Asymptotic Bias ◽  
Gradient Search

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.

scholarly journals Generalized Deterministic Perturbations For Stochastic Gradient Search

2018 ◽  
Author(s):  
K. Chandramouli ◽  
K.J. Prabuchandran ◽  
D. Sai Koti Reddy ◽  
Shalabh Bhatnagar
Keyword(s):  
Stochastic Gradient ◽  
Gradient Search
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