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Publications (15)
This paper primarily demonstrates the effectiveness of the Z-type methodology for solving the problem of time-variant matrix inverse (termed Zhang matrix inverse, ZMI). As a case study of ZMI with examples, the online solution of ZMI is investigated in this paper. Specifically, different Zhang functions (ZFs), which lead to different effective Z-ty...
A special class of neural dynamics called Zhang dynamics (ZD), which is different from gradient dynamics (GD), has recently been proposed, generalized, and investigated for solving time-varying problems by following Zhang et al.’s design method. In view of potential digital hardware implemetation, discrete-time ZD (DTZD) models are proposed and inv...
The dynamic system, i.e., gradient dynamic system (GDS), is theoretically designed by defining a square-based nonnegative or at least lower-bounded error-monitoring function, which is termed the energy function (EF). Such a dynamic system is then cast in the form of a first-order differential equation. To compute scalar square roots, in this paper,...
In view of the great potential in parallel processing and ready implementation via hardware, neural networks are now often employed to solve online nonlinear matrix equation problems. Recently, a novel class of neural networks, termed Zhang neural network (ZNN), has been formally proposed by Zhang et al. for solving online time-varying problems. Su...
Zhang dynamics (ZD) has been proved a powerful alternative for solving online time-varying problems. Such a dynamic system is elegantly designed by defining an indefinite error-monitoring function, called Zhang function (ZF). The dynamic system is then cast in the form of a first-order differential equation. In this paper, different ZFs, which lead...
Different from conventional gradient-based neural dynamics, a special type of neural dynamics has been proposed by Zhang et al. for online solution of time-varying and/or static (or termed, time-invariant) problems. The design of Zhang dynamics (ZD) is based on the elimination of an indefinite error function, instead of the elimination of a square-...
A special class of recurrent neural network (RNN), i.e., Zhang neural network (ZNN), has been proposed for a decade for solving online various time-varying problems. In this paper, we generalize and investigate a continuous-time ZNN model for online solution of the time-varying convex quadratic programming (QP) subject to a time-varying linear equa...
A special class of recurrent neural network (RNN) termed Zhang neural network (ZNN) has recently been proposed for time-varying matrix square roots finding. Such a ZNN model can be constructed via monotonically-increasing odd activation functions to obtain the theoretical time-varying matrix square roots in an error-free manner. Different choices o...
A special class of recurrent neural network, termed Zhang neural network (ZNN) depicted in the implicit dynamics, has recently been proposed for online solution of time-varying matrix square roots. Such a ZNN model can be constructed by using monotonically-increasing odd activation functions to obtain the theoretical time-varying matrix square root...
Our previous work has shown the efficacy and promising performance of continuous-time Zhang dynamics (CTZD) for solving online
nonlinear equations, as compared with conventional gradient dynamics (GD). It has also shown that, with linear activation
functions used and with step-size being 1, the discrete-time Zhang dynamics (DTZD) reduces to the New...
Our previous work shows the efficacy and better performance of the Zhang dynamics (ZD) model for solving online nonlinear equations, as compared with the conventional gradient dynamics (GD) model. It is also discovered that, if a nonlinear equation possesses a local minimum point, the ZD state, starting from some initial value close to it, may move...
Different from conventional gradient-based neural dynamics, a special class of neural dynamics have been proposed by Zhang et al. since 12 March 2001 for online solution of time-varying and static (or termed, time-invariant) problems (e.g., nonlinear equations). The design of Zhang dynamics (ZD) is based on the elimination of an indefinite error-fu...
For better manipulability, a criterion in the form of a quadratic function is presented for the self-motion planning (SMP) of redundant manipulators with no target-configuration assigned. Such SMP scheme could automatically select the desirable configuration so that the manipulator could be more flexible and maneuverable. As physical limits general...
Since 12 March 2001, Zhang et al have proposed a special class of recurrent neural networks for online time-varying problems solving, especially for matrix inversion. For possible hardware (e.g., digital-circuit) realization, such Zhang neural networks (ZNN) could also be reformulated in the discrete-time form, which incorporates Newton iteration a...
For online solution of time-varying linear equations, a special kind of recurrent neural networks has recently been proposed by Zhang et al. It has been proved that global exponential convergence of such recurrent neural networks (or termed Zhang neural networks, ZNN, for presentation convenience) can be achieved. For easier hardware-realization, a...
