A supervised learning algorithm for quantum neural networks (QNN) based on a novel
quantum neuron node implemented as a very simple quantum circuit is proposed and …

This paper presents an overview of research in Weightless Neural Models. Weightless
Neural Networks (WNNs) do not have weighted connections between nodes. They use a …

A linear tubular switched reluctance motor is presented. This actuator is devoted to be used
as a left ventricular assist device (LVAD). In order to avoid thrombosis, this actuator includes …

Several compile time transformations of loops with simple dependencies have been
developed in order to expose possible parallelism in these loops. However, once an …

Soft computing (SC) emerged as an integrating framework for a number of techniques that
could complement one another quite well (artificial neural networks, fuzzy systems …

In order to investigate the dynamics of a quantum weightless neuron node we feed its output
back as input. Due to the fact that controlled operators used in the neuron circuit usually …

Researches in natural neuron dynamics have shown that phase transition and chaos
provide optimal behaviour for information processing. In artificial neural models that …

In this paper we investigate the computational power of the quantum weightless neural
networks (q-WNN) and propose a novel quantum weightless neural node. The new quantum …

This article is written in recognition of W. Bledsoe, who with Browning, introduced the N-
tuple subspace classifier in 1959. This 1959 article was the first article to introduce subspace …

Despite neural networks have super-Turing computing power, there is no known algorithm
for obtaining a classical neural networks that solves NP-complete problems in polynomial …