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

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.