Convergence and robustness analysis of disturbed gradient neural network for solving LMS problem

In this paper, we introduce a kind of method for solving least mean square problems based on the gradient neural network, including the network model construction, quantitative analysis of the network global convergence and the network convergence rate about the different activation functions. MATLA...

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Bibliographic Details
Published in2012 8th International Conference on Natural Computation pp. 398 - 401
Main Authors Wudai Liao, Xingfeng Wang, Yuyu Yang, Junyan Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2012
Subjects
Computational modeling
Convergence
Equations
gradient neural network global convergence
least squares problem
Mathematical model
MATLAB
MATLAB simulation
Neural networks
Robustness
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Summary:In this paper, we introduce a kind of method for solving least mean square problems based on the gradient neural network, including the network model construction, quantitative analysis of the network global convergence and the network convergence rate about the different activation functions. MATLAB simulation results and theoretical analysis results are accordingly consistent, which further confirm the method based on Hopfield neural network has a good effect on solving the least mean square problems.
ISBN:9781457721304
1457721309
ISSN:2157-9555
DOI:10.1109/ICNC.2012.6234546