Different from gradient-based neural networks, a special kind of recurrent neural network (RNN)
has recently been proposed by Zhang for online matrix inversion. Such an RNN is …

Differing from gradient-based neural networks (GNN), a special kind of recurrent neural
network has recently been proposed by Zhang et al. for real-time inversion of time-varying …

For online solution of nonlinear equation f(x) = 0, this paper generalizes a special kind of
recurrent neural dynamics by using a recent design method proposed by Zhang et al. Different …

In view of parallel-processing nature and circuit-implementation convenience, recurrent
neural networks are often employed to solve optimization problems. Recently, a primal-dual …

Different from gradient-based neural networks, a special kind of recurrent neural network has
recently been proposed by Zhang et al for online matrix inversion. Such a neural network is …

Recently, a special kind of recurrent neural networks has been proposed by Zhang et al for
online solution of Sylvester equation with time-varying coefficients. Their neural dynamics are …

This paper investigates the simulation of a gradient-based recurrent neural network for
online solution of the matrix-inverse problem. Several important techniques are employed as …

Recently, a special kind of recurrent neural networks (RNN) with implicit dynamics has been
proposed by Zhang et al for online time-varying problems solving (such as time-varying …

A special kind of recurrent neural network has recently been proposed by Zhang et al for
matrix inversion. Then, for possible hardware and digital-circuit realization, the corresponding …

In recent years, many studies have been reported on real-time solutions of algebraic
problems including matrix inversion and linear equations solving. Recently, a special kind of …