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Time-varying complex reciprocals solved by ZD via different complex Zhang functions

机译:通过Zd通过不同复杂的Zhang函数解决的时变复数倒数

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A novel type of neural dynamics, which is named Zhang dynamics (ZD), has been proposed by Zhang et al. since 2001. Such a ZD, which is based on an indefinite Zhang function (ZF), is designed for online solution of various time-varying problems. As the design basis of ZD, ZF is introduced as an error monitoring-and-control function in the design procedure, and is quite different from the norm-based positive-definite energy function which is usually associated with the gradient-based dynamics (GD). In this paper, the ZD method is extended and exploited for online solution of time-varying complex reciprocals for the first time. Then, different complex ZFs are introduced in this paper, and the corresponding complex ZD models are proposed and developed for the time-varying complex reciprocal computation. Through illustrative examples, the efficacy of the proposed complex ZD models for online solution of time-varying complex reciprocals is substantiated evidently.
机译:张等人提出了一种名为Zhang Dynamics(ZD)的新型神经动力学。 自2001年以来。这种基于无限张功能(ZF)的ZD,专为各种时差问题的在线解决方案而设计。 作为ZD的设计基础,ZF被引入设计过程中的错误监视和控制功能,与基于范数的正面能量函数完全不同,通常与基于梯度的动态相关联(GD )。 在本文中,ZD方法延长并利用了第一次时变化复合倒数的在线解决方案。 然后,本文介绍了不同的复合ZFS,并提出了相应的复杂ZD模型,并为时变复合互易计算开发。 通过说明性的示例,显然,提出了拟议的复合ZD模型的在线溶液的在线溶液的效果。

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