DocumentCode
1940095
Title
A K-Winners-Take-All Neural Network Based on Linear Programming Formulation
Author
Gu, Shenshen ; Wang, Jun
Author_Institution
Chinese Univ. of Hong Kong, Hong Kong
fYear
2007
fDate
12-17 Aug. 2007
Firstpage
37
Lastpage
40
Abstract
In this paper, the K-Winners-Take-All (KWTA) problem is formulated equivalently to a linear program. A recurrent neural network for KWTA is then proposed for solving the linear programming problem. The KWTA network is globally convergent to the optimal solution of the KWTA problem. Simulation results are further presented to show the effectiveness and performance of the KWTA network.
Keywords
linear programming; recurrent neural nets; k-winners-take-all neural network; linear programming; recurrent neural network; Associative memory; Computer networks; Electrical capacitance tomography; Feature extraction; Linear programming; Neural networks; Recurrent neural networks; Signal processing; Vectors; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location
Orlando, FL
ISSN
1098-7576
Print_ISBN
978-1-4244-1379-9
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2007.4370927
Filename
4370927
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