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author:

Xia, Y. (Xia, Y..) [1]

Indexed by:

Scopus

Abstract:

This paper presents a new cooperative projection neural network for fast solving quadratic convex programming problems, including linear reconstruction problems. The proposed cooperative projection neural network consists of a weighted combination of two projection terms. Compared with conventional projection neural networks and numerical optimization methods, the proposed cooperative projection neural network has a small model size and no limit condition of initial points. Numerical results demonstrate that the proposed cooperative projection neural network has a faster speed than the existing projection neural networks. Therefore, the proposed cooperative projection neural network can fast solve linear reconstruction problems. © Springer International Publishing AG 2017.

Keyword:

Continuous-time neural network; Fast computation; Linear reconstruction problems; Low-dimensional model

Community:

  • [ 1 ] [Xia, Y.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China

Reprint 's Address:

  • [Xia, Y.]College of Mathematics and Computer Science, Fuzhou UniversityChina

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Source :

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISSN: 0302-9743

Year: 2017

Volume: 10261 LNCS

Page: 511-520

Language: English

0 . 4 0 2

JCR@2005

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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