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CONIELECOMP
2006
IEEE
14 years 1 months ago
Chaotic Time Series Approximation Using Iterative Wavelet-Networks
This paper presents a wavelet neural-network for learning and approximation of chaotic time series. Wavelet-networks are inspired by both feed-forward neural networks and the theo...
E. S. Garcia-Trevino, Vicente Alarcón Aquin...
TNN
2010
139views Management» more  TNN 2010»
13 years 2 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...
ICT
2004
Springer
194views Communications» more  ICT 2004»
14 years 1 months ago
Competitive Neural Networks for Fault Detection and Diagnosis in 3G Cellular Systems
We propose a new approach to fault detection and diagnosis in third-generation (3G) cellular networks using competitive neural algorithms. For density estimation purposes, a given ...
Guilherme De A. Barreto, João Cesar M. Mota...
ANNPR
2006
Springer
13 years 11 months ago
Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
Yusuke Torii, Shigeo Abe
IDEAL
2005
Springer
14 years 1 months ago
Generating Predicate Rules from Neural Networks
Artificial neural networks play an important role for pattern recognition tasks. However, due to poor comprehensibility of the learned network, and the inability to represent expl...
Richi Nayak