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IBPRIA
2003
Springer
13 years 10 months ago
A Probabilistic Model for the Cooperative Modular Neural Network
Abstract. This paper presents a model for the probability of correct classification for the Cooperative Modular Neural Network (CMNN). The model enables the estimation of the perf...
Luís A. Alexandre, Aurélio C. Campil...
TNN
2008
96views more  TNN 2008»
13 years 5 months ago
Global Convergence and Limit Cycle Behavior of Weights of Perceptron
In this paper, it is found that the weights of a perceptron are bounded for all initial weights if there exists a nonempty set of initial weights that the weights of the perceptron...
Charlotte Yuk-Fan Ho, Bingo Wing-Kuen Ling, Hak-Ke...
AIA
2007
13 years 6 months ago
Optimizing number of hidden neurons in neural networks
In this paper, a novel and effective criterion based on the estimation of the signal-to-noise-ratio figure (SNRF) is proposed to optimize the number of hidden neurons in neural ne...
Yue Liu, Janusz A. Starzyk, Zhen Zhu
PAMI
2006
215views more  PAMI 2006»
13 years 5 months ago
Bayesian Feature and Model Selection for Gaussian Mixture Models
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
DSP
2007
13 years 5 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...