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

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

This paper is a study on main properties and characterizations of the DMP inverse. Also,
corresponding representations and computational procedures are derived. Particularly, an …

Based on a quadratical convergence method, a family of iterative methods to compute the
approximate inverse of square matrix are presented. The theoretical proofs and numerical …

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

In this paper, we extend the iterative method for computing the inner inverse of a matrix
proposed in Li and Li [WG Li, Z. Li, A family of iterative methods for computing the …

An improved complex varying-parameter Zhang neural network (CVPZNN) for computing
outer inverses is established in this paper. As a consequence, three types of complex Zhang …

The aim of this paper is to provide new representations and characterizations of the weak
group inverse. We give a relation between the weak group inverse and a corresponding …

An iterative algorithm for estimating the Moore–Penrose generalized inverse is developed.
The main motive for the construction of the algorithm is simultaneous usage of Penrose …

Our first aim is to extend the Zhang Neural Network (ZNN) algorithmic conceptual
framework, developed so far in the computation of the matrix inverse, pseudoinverse, and …