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A Projection Neural Network for Circular Cone Programming
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
A projection neural network method for circular cone programming is proposed.
In the KKT condition for the circular cone programming, the complementary slack equation is transformed into an equivalent projection equation.
The energy function is constructed by the distance function and the dynamic differential equation is given by the descent direction of the energy function.
Since the projection on the circular cone is simple and costs less computation time, the proposed neural network requires less state variables and leads to low complexity.
We prove that the proposed neural network is stable in the sense of Lyapunov and globally convergent.
The simulation experiments show our method is efficient and effective.
American Psychological Association (APA)
Zhang, Yaling& Liu, Hongwei. 2018. A Projection Neural Network for Circular Cone Programming. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1207543
Modern Language Association (MLA)
Zhang, Yaling& Liu, Hongwei. A Projection Neural Network for Circular Cone Programming. Mathematical Problems in Engineering No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1207543
American Medical Association (AMA)
Zhang, Yaling& Liu, Hongwei. A Projection Neural Network for Circular Cone Programming. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1207543
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1207543