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NEUROSCIENCE
2001
Springer
13 years 12 months ago
Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?
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...
Mikel L. Forcada, Rafael C. Carrasco
TCS
2002
13 years 7 months ago
Unsupervised learning in neural computation
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...
Erkki Oja
ESANN
2008
13 years 9 months ago
Neural networks for computational neuroscience
Computational neuroscience is an appealing interdisciplinary domain, at the interface between biology and computer science. It aims at understanding the experimental data obtained...
David Meunier, Hélène Paugam-Moisy
IDA
2003
Springer
14 years 23 days ago
Similarity-Based Neural Networks for Applications in Computational Molecular Biology
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...
Igor Fischer
NN
2007
Springer
13 years 7 months ago
Edge of chaos and prediction of computational performance for neural circuit models
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 ...
Robert A. Legenstein, Wolfgang Maass