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IJON
1998
140views more  IJON 1998»
13 years 9 months ago
Comment on "Discrete-time recurrent neural network architectures: A unifying review"
Paper [1] aimed at providing a unified presentation of neural network architectures. We show in the present comment (i) that the canonical form of recurrent neural networks presen...
Léon Personnaz, Gérard Dreyfus
ICPR
2002
IEEE
14 years 11 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
14 years 4 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
JCP
2008
121views more  JCP 2008»
13 years 10 months ago
Relation Organization of SOM Initial Map by Improved Node Exchange
The Self Organizing Map (SOM) involves neural networks, that learns the features of input data thorough unsupervised, competitive neighborhood learning. In the SOM learning algorit...
Tsutomu Miyoshi
IJCNN
2008
IEEE
14 years 4 months ago
Numerical condition of feedforward networks with opposite transfer functions
— Numerical condition affects the learning speed and accuracy of most artificial neural network learning algorithms. In this paper, we examine the influence of opposite transfe...
Mario Ventresca, Hamid R. Tizhoosh