Nonlinear System Identification Using Extreme Learning Machine

2006 ◽  
Author(s):  
Ming-Bin Li ◽  
Meng Joo Er
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Extreme Learning Machine ◽  
Nonlinear System Identification ◽  
Learning Machine

scholarly journals Wavelet Network: Online Sequential Extreme Learning Machine for Nonlinear Dynamic Systems Identification

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Dhiadeen Mohammed Salih ◽  
Samsul Bahari Mohd Noor ◽  
Mohammad Hamiruce Merhaban ◽  
Raja Mohd Kamil
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Extreme Learning Machine ◽  
Nonlinear System Identification ◽  
Wavelet Network ◽  
Building Models ◽  
Random Initialization ◽  
Learning Machine ◽  
Hidden Layer ◽  
Initialization Procedure

A single hidden layer feedforward neural network (SLFN) with online sequential extreme learning machine (OSELM) algorithm has been introduced and applied in many regression problems successfully. However, using SLFN with OSELM as black-box for nonlinear system identification may lead to building models for the identified plant with inconsistency responses from control perspective. The reason can refer to the random initialization procedure of the SLFN hidden node parameters with OSELM algorithm. In this paper, a single hidden layer feedforward wavelet network (WN) is introduced with OSELM for nonlinear system identification aimed at getting better generalization performances by reducing the effect of a random initialization procedure.

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