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 …

Several characterizations and representations for the core-EP inverse are presented and
investigated. To that goal, several explicit bordering technique for characterizing and …

As we know, harmonic noises widely exist in industrial fields and have a crucial impact on
the computational accuracy of the zeroing neural network (ZNN) model. For tackling this …

Extreme learning machine (ELM) is a learning algorithm for single-hidden layer feedforward
neural networks (SLFNs) which randomly chooses hidden nodes and analytically …

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 …

This paper analyzes the existing zeroing neural network (ZNN) models from the perspective
of control theory. It proposes an exclusive ZNN model for solving the dynamic complex …

In this article we provide a fast computational method in order to calculate the Moore–
Penrose inverse of singular square matrices and of rectangular matrices. The proposed …

An integration-enhanced noise-tolerant zeroing neural network (IENTZNN) model for
computing various expressions involving outer inverses is defined and considered. The …

The computation of the Moore–Penrose inverse of structured strictly totally positive matrices
is addressed. Since these matrices are usually very ill-conditioned, standard algorithms fail …

To handle the future Moore–Penrose inverse problem effectively, the continuous gradient-
zeroing neural dynamics (CGZND) model without inverse computing is proposed via …