DocumentCode :
1593754
Title :
Research on Optimization Algorithm of Minimum Entropy Value Using Hopfield Neural Network
Author :
Wei, Yong-qin ; Wu, Na ; Gao, Jian-feng
Author_Institution :
Coll. of Inf. & Electr. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
fYear :
2012
Firstpage :
485
Lastpage :
488
Abstract :
In high speed processing system, using common optimization algorithm to solve minimum entropy, it is slow and could produce "explosive" with computation dimension increasing. According to this problem, this paper carry out an improved Hop field neural network optimization algorithm, introducing the punish operator, and make it applied to the minimum entropy value calculation. Calculation results show that Hop field neural network can efficiently solve the minimum entropy of constraint condition, high speed and cann\´t happen "explosive".
Keywords :
Hopfield neural nets; minimum entropy methods; optimisation; Hop field neural network optimization algorithm; common optimization algorithm; high speed processing system; minimum entropy value calculation; punish operator; Entropy; Equations; Hopfield neural networks; Mathematical model; Neurons; Optimization; Power system stability; Hopfield neural; minimum entropy; optimization algorithm; punish operator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-1-4577-2120-5
Type :
conf
DOI :
10.1109/ISdea.2012.518
Filename :
6173250
Link To Document :
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