One of the biggest problems for major airline is predicting flight delay. Airlines try to reduce
delays to gain the loyalty of their customers. Hence, a prediction model that airliners can use …

Hopfield networks are artificial neural networks which store memory patterns on the states of
their neurons by choosing recurrent connection weights and update rules such that the …

Recently, the concept of evaluating an unusually large learning effort of an adaptive system
to detect novelties in the observed data was introduced. The present paper introduces a new …

Established recurrent neural networks are well-suited to solve a wide variety of prediction
tasks involving discrete sequences. However, they do not perform as well in the task of …

Artificial vision using computational models that can mimic biological vision is an area of
ongoing research. One of the main themes within this research is the study of the retina and …

A standard approach to model retinal ganglion cells uses reverse correlation to construct a
linear-nonlinear model using a cascade of a linear filter and a static nonlinearity. A major …

Geometry and topology offer rich mathematical worlds and perspectives with which to study
and improve our understanding of cognitive function. Here I present the following …

This paper developed a new open box and nonlinear model of Ultra High Frequency
Sigmoid and Cosine Artificial Higher Order Neural Network (UGC-HONN). This paper also …

Logic-based problems such as planning, theorem proving, or puzzles, typically involve
combinatoric search and structured knowledge representation. Artificial neural networks are …

New open box and nonlinear system model of Ultra High Frequency Sigmoid and Sine
Artificial Higher Order Neural Network (UGS-HONN) is presented in this paper. A new …