Nonholonomic systems provide an important class of mechanical control systems. One
reason for this importance is that nonintegrability is essential to both the mechanics and the …

In this paper, the existing recurrent neural network (RNN) models for solving zero-finding
(eg, matrix inversion) with time-varying parameters are revisited from the perspective of …

In the previous work, Zhang et al. developed a special type of recurrent neural networks
called Zhang neural network (ZNN) with continuous-time and discrete-time forms for time …

As a special class of recurrent neural network, Zhang neural network (ZNN) has been
recently proposed since 2001 for solving various time-varying problems, and has shown …

This dissertation introduces the notion of a dynamic inverse of a nonlinear map. The
dynamic inverse is used in the construction of nonlinear dynamical system, called a dynamic …

The Zhang neural network (ZNN) has recently realized remarkable success in solving time-
varying problems. Harmonic noise widely exists in industrial applications and can severely …

Time-dependent linear system (TDLS) is usually encountered in scientific research, which is
the mathematical formulation of many practical applications. Different from conventional …

In this paper, we present, develop and investigate a special kind of recurrent neural network
termed Zhang neural network (ZNN) for time-varying matrix inversion. Comparing with the …

In this paper, a special class of recurrent neural network, termed Zhang neural network
(ZNN), is investigated for the online solution of the time-varying matrix pseudoinverse …

Inevitable noises and limited computational time are major issues for time-variant matrix
inversion in practice. When designing a time-variant matrix inversion algorithm, it is highly …