Title : ( An Efficient Neural Network Model for Solving the Absolute Value Equations )
Authors: Amin Mansoori , mohammad eshaghnezhad , Sohrab Effati ,
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Abstract
In this paper, we obtain the exact solution of the absolute value equation (AVE). To the best of our knowledge, there is not an attempt to obtain the exact solution to this problem. However, there exist many numerical methods to get the approximation solution of the AVE. Here, we try to present a neural network model in order to find the solution of the AVE, analytically. Furthermore, the Lyapunov stability and the global convergence of the model are proved. Finally, the simulation results show the performance, the effectiveness, and the accuracy of the method
Keywords
, Absolute value equations, Linear complementarity problem, Neural network, Globally stable in the sense of Lyapunov
@article{paperid:1064237,
author = {Mansoori, Amin and Eshaghnezhad, Mohammad and Effati, Sohrab},
title = {An Efficient Neural Network Model for Solving the Absolute Value Equations},
journal = {IEEE Transactions on Circuits and Systems Part II: Express Briefs},
year = {2017},
volume = {65},
number = {3},
month = {March},
issn = {1549-7747},
pages = {391--395},
numpages = {4},
keywords = {Absolute value equations; Linear complementarity problem; Neural network; Globally stable in the sense of
Lyapunov},
}
%0 Journal Article
%T An Efficient Neural Network Model for Solving the Absolute Value Equations
%A Mansoori, Amin
%A Eshaghnezhad, Mohammad
%A Effati, Sohrab
%J IEEE Transactions on Circuits and Systems Part II: Express Briefs
%@ 1549-7747
%D 2017
