We show that temporal logic and combinations of temporal logics and modal logics of knowledge can be effectively represented in artificial neural networks. We present a Translat...
The analysis of social networks often assumes the time invariant scenario while in practice node attributes and links in such networks often evolve over time. In this paper, we pro...
This book covers several topics such as: overview of neural networks, matrix operations in Java, Hopfield Neural Network, machine learning, feedforward backpropagation, Simulated a...
Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
Abstract. In this paper, we will address the endeavors of three disciplines, Psychology, Neuroscience, and Artificial Neural Network (ANN) modeling, in explaining how the mind perc...