Abstract. Finite-state machines are the most pervasive models of computation, not only in theoretical computer science, but also in all of its applications to real-life problems, a...
In this article, we consider unsupervised learning from the point of view of applying neural computation on signal and data analysis problems. The article is an introductory surve...
Computational neuroscience is an appealing interdisciplinary domain, at the interface between biology and computer science. It aims at understanding the experimental data obtained...
This paper presents an alternative to distance-based neural networks. A distance measure is the underlying property on which many neural models rely, for example self-organizing ma...
We analyze in this article the significance of the edge of chaos for real-time computations in neural microcircuit models consisting of spiking neurons and dynamic synapses. We ...