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» Introduction to artificial neural networks
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BMCBI
2010
149views more  BMCBI 2010»
13 years 8 months ago
A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context
Background: Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex eti...
Ioannis K. Valavanis, Stavroula G. Mougiakakou, Ke...
BMCBI
2008
123views more  BMCBI 2008»
13 years 8 months ago
Validation of protein models by a neural network approach
Background: The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure re...
Paolo Mereghetti, Maria Luisa Ganadu, Elena Papale...
EH
2005
IEEE
158views Hardware» more  EH 2005»
14 years 1 months ago
Hardware Evolution of Analog Circuits for In-situ Robotic Fault-Recovery
We present a method for evolving and implementing artificial neural networks (ANNs) on Field Programmable Analog Arrays (FPAAs). These FPAAs offer the small size and low power usa...
Dmitry Berenson, Nicolás S. Estévez,...
NN
2002
Springer
115views Neural Networks» more  NN 2002»
13 years 7 months ago
A self-organising network that grows when required
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow
ESANN
2004
13 years 9 months ago
Computational model of amygdala network supported by neurobiological data
Abstract. The amygdala has repeatedly been involved in the processing of emotional reactions and conditioning. This paper presents a neurobiologically inspired computational model ...
Mélanie Falgairolle, Agnès Gorge, Je...