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ACSC
2008
IEEE
15 years 8 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish
ICPR
2002
IEEE
16 years 7 months ago
Learning and Extracting Edges from Images by a Modified Hopfield Neural Network
This paper introduced a modified unsupervised Hopfield network that can learn the underlying process in an edge detection task from grey level images. After the learning phase, th...
Sylvain Chartier, Richard Lepage
GECCO
2008
Springer
196views Optimization» more  GECCO 2008»
15 years 7 months ago
ADANN: automatic design of artificial neural networks
In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
Juan Peralta, Germán Gutiérrez, Arac...
ICANN
2001
Springer
15 years 10 months ago
Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension
Abstract. It has remained an open question whether there exist product unit networks with constant depth that have superlinear VC dimension. In this paper we give an answer by cons...
Michael Schmitt
IWANN
2001
Springer
15 years 10 months ago
Landmark Recognition for Autonomous Navigation Using Odometric Information and a Network of Perceptrons
In this paper two methods for the detection and recognition of landmarks to be used in topological modeling for autonomous mobile robots are presented. The first method is based o...
Javier de Lope Asiaín, Darío Maraval...