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» Training Methods for Adaptive Boosting of Neural Networks
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ISNN
2007
Springer
15 years 3 months ago
Recurrent Fuzzy CMAC for Nonlinear System Modeling
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...
Floriberto Ortiz Rodriguez, Wen Yu, Marco A. Moren...
IJCNN
2007
IEEE
15 years 4 months ago
A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters
— Neurons are point process systems, in the sense that the inputs and output which are spike trains can be treated as point processes. System identification of a point process s...
Il Park, António R. C. Paiva, Jose C. Princ...
ISNN
2005
Springer
15 years 3 months ago
A Block-Adaptive Subspace Method Using Oblique Projections for Blind Separation of Convolutive Mixtures
This paper presents a block-adaptive subspace algorithm via oblique projection for blind source separation (BSS) problem of convolutive mixtures. In the proposed algorithm, the pro...
Chunyi Peng, Xianda Zhang, Qutang Cai
IWANN
2001
Springer
15 years 2 months ago
Is Neural Network a Reliable Forecaster on Earth? A MARS Query!
: Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and ...
Ajith Abraham, Dan Steinberg
IDEAL
2010
Springer
14 years 8 months ago
Dimension Reduction for Regression with Bottleneck Neural Networks
Dimension reduction for regression (DRR) deals with the problem of finding for high-dimensional data such low-dimensional representations, which preserve the ability to predict a ...
Elina Parviainen