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IEEEICCI
2003
IEEE
14 years 3 months ago
Signal Classification through Multifractal Analysis and Complex Domain Neural Networks
This paper describes a system capable of classifying stochastic, self-affine, nonstationary signals produced by nonlinear systems. The classification and analysis of these signals...
Witold Kinsner, V. Cheung, K. Cannons, J. Pear, T....
IJCNN
2000
IEEE
14 years 2 months ago
Design and Evaluation of Neural Networks for Coin Recognition by Using GA and SA
In this paper, we propose a method to design a neural network(NN) by using a genetic algorithm(GA) and simulated annealing(SA). And also, in order to demonstrate the effectivenes...
Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu
ICANN
2007
Springer
14 years 2 months ago
Topology Aware Internet Traffic Forecasting Using Neural Networks
Forecasting Internet traffic is receiving an increasing attention from the computer networks domain. Indeed, by improving this task efficient traffic engineering and anomaly detect...
Paulo Cortez, Miguel Rio, Pedro Sousa, Miguel Roch...
ANNPR
2006
Springer
14 years 4 days ago
A Convolutional Neural Network Tolerant of Synaptic Faults for Low-Power Analog Hardware
Abstract. Recently, the authors described a training method for a convolutional neural network of threshold neurons. Hidden layers are trained by by clustering, in a feed-forward m...
Johannes Fieres, Karlheinz Meier, Johannes Schemme...
NN
1998
Springer
13 years 9 months ago
Statistical estimation of the number of hidden units for feedforward neural networks
The number of required hidden units is statistically estimated for feedforward neural networks that are constructed by adding hidden units one by one. The output error decreases w...
Osamu Fujita