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 …

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 …

Recently, a general recurrent neural network (RNN) with implicit dynamics has been
proposed by Zhang et al for online time-varying algebraic equations solving; namely Zhang …

A new algorithm is presented for the determination of the coefficients of an n-dimensional
(nD) transfer function. The nD state-space system is described by the nD Fornasini …

In symbolic computation, variables are stored as exact without numerical values to ensure
precision throughout the calculations, which makes it an important area in computer algebra …

In this paper the discrete Fourier transform (DFT) is applied for determining the transfer
function coefficients for second {order generalized state space linear systems, Ex (2)= A1x+ …

The time‐variant matrix inversion (TVMI) problem solving is the hotspot of current research
because of its frequent appearance and application in scientific research and industrial …

In this paper, an innovative design approach is proposed to solve time-varying dynamical
equation, including matrix inverse equation and Sylvester equation. Based on the …

New algorithms for the derivation of the transfer-function matrices of two-dimensional (2-D)
discrete systems from the Roesser and Fornasini-Marchesini state-space models are …

An improved Zhang neural network (IZNN) together with its implementation architecture is
presented and investigated for matrix inversion in real time. It is theoretically proved that the …