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BMCBI
2006
146views more  BMCBI 2006»
13 years 7 months ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...
APPINF
2003
13 years 8 months ago
Preventing Computational Chaos in Asynchronous Neural Networks
One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...
Jacob Barhen, Vladimir Protopopescu
AAAI
1994
13 years 8 months ago
CHATTERBOTS, TINYMUDS, and the Turing Test: Entering the Loebner Prize Competition
The Turing Test was proposed by Alan Turing in 1950; he called it the Imitation Game. In 1991 Hu Loebner prize competition, offering a f h Loebner started the 100,000 prize to the...
Michael L. Mauldin
ISTCS
1993
Springer
13 years 11 months ago
Analog Computation Via Neural Networks
We pursue a particular approach to analog computation, based on dynamical systems of the type used in neural networks research. Our systems have a xed structure, invariant in time...
Hava T. Siegelmann, Eduardo D. Sontag
ICNC
2005
Springer
14 years 26 days ago
Segmentation of SAR Image Using Mixture Multiscale ARMA Network
Abstract. A mixture multiscale autoregressive moving average (ARMA) network is proposed for unsupervised segmentation of synthetic aperture radar (SAR) image. The network combines ...
Haixia Xu, Tian Zheng, Fan Meng