A Discrete-Time Projection Neural Network for Solving Degenerate Convex Quadratic Optimization

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• 作者：Zican Zhang ; Chuandong Li ; Xing He…
• 关键词：Degenerate quadratic optimization ; Discrete ; time neural network ; Convex optimization ; Algorithm convergence
• 刊名：Circuits, Systems, and Signal Processing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：36
• 期：1
• 页码：389-403
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Circuits and Systems; Electrical Engineering; Signal,Image and Speech Processing; Electronics and Microelectronics, Instrumentation;
• 出版者：Springer US
• ISSN：1531-5878
• 卷排序：36

文摘

This paper presents a discrete-time neural network to solve convex degenerate quadratic optimization problems. Under certain conditions, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to an optimal solution. Compared with the existing continuous-time neural networks for degenerate quadratic optimization, the proposed neural network in this paper is more suitable for hardware implementation. Results of two experiments of this neural network are given to illustrate the effectiveness of the proposed neural network.