Stability and synchronization of delayed fractional-order projection neural network with piecewise constant argument of mixed type
Stability and synchronization of delayed fractional-order projection neural network with piecewise constant argument of mixed type
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DOI：
10.1515/tmj-2017-0003
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发表时间：
2017-02
影响因子：
0.5
通讯作者：
Swati Tyagi;Syed Abbas
中科院分区：
文献类型：
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作者：
Swati Tyagi;Syed Abbas
摘要投影方程是最优化问题中的一类重要方程，在科学和工程的许多领域有着重要的应用。在本文中，我们提出了一个分数阶投影神经网络来解决二次规划问题。研究了一类基于脉冲控制的混合型时滞投影神经网络的稳定性和同步问题。利用分数阶微积分的概念，我们研究了解的存在性和全局渐近稳定性。此外，我们提出了一个有效的脉冲控制方案，以实现同步的系统。我们证明了适当的例子的帮助下，所提出的神经网络的有效性和瞬态行为。
Abstract Projection equations arise in several optimization problems and possess significant applications in many areas of science and engineering. In this paper, we propose a fractional-order projection neural network to solve quadratic programming problems. We study stability and synchronization for a class of delayed projection neural networks of mixed type via impulsive control. Using concepts of fractional calculus, we investigate the existence of solution and study its global asymptotic stability. Moreover, we propose an effective impulsive control scheme to achieve synchronization for the system. We demonstrate the validity and transient behaviour of the proposed neural network with the help of suitable examples.