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TNN
2010
139views Management» more  TNN 2010»
14 years 10 months ago
Identification of finite state automata with a class of recurrent neural networks
A class of recurrent neural networks is proposed and proven to be capable of identifying any discrete-time dynamical system. The application of the proposed network is addressed in...
Sung Hwan Won, Iickho Song, Sun-Young Lee, Cheol H...
EVOW
2006
Springer
15 years 7 months ago
A Neural Evolutionary Classification Method for Brain-Wave Analysis
This paper presents an approach to the joint optimization of neural network structure and weights which can take advantage of backpropagation as a specialized decoder. The approach...
Antonia Azzini, Andrea Tettamanzi
ESANN
2003
15 years 5 months ago
A new rule extraction algorithm based on interval arithmetic
In this paper we propose a new algorithm for rule extraction from a trained Multilayer Feedforward network. The algorithm is based on an interval arithmetic network inversion for p...
Carlos Hernández-Espinosa, Mercedes Fern&aa...
ISNN
2007
Springer
15 years 10 months ago
Integrated Analytic Framework for Neural Network Construction
Abstract. This paper investigates the construction of a wide class of singlehidden layer neural networks (SLNNs) with or without tunable parameters in the hidden nodes. It is a cha...
Kang Li, Jian Xun Peng, Minrui Fei, Xiaoou Li, Wen...
GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
15 years 4 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee