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ISNN
2005
Springer
10 years 1 months ago
Post-nonlinear Blind Source Separation Using Neural Networks with Sandwiched Structure
Abstract. This paper proposes a novel algorithm based on informax for postnonlinear blind source separation. The demixing system culminates to a neural network with sandwiched stru...
Chunhou Zheng, Deshuang Huang, Zhan-Li Sun, Li Sha...
ESANN
2003
9 years 9 months ago
Neural Net with Two Hidden Layers for Non-Linear Blind Source Separation
In this paper, we present an algorithm that minimizes the mutual information between the outputs of a perceptron with two hidden layers. The neural network is then used as separati...
Rubén Martín-Clemente, Susana Hornil...
EAAI
2006
157views more  EAAI 2006»
9 years 8 months ago
Blind source separation based on self-organizing neural network
This contribution describes a neural network that self-organizes to recover the underlying original sources from typical sensor signals. No particular information is required abou...
Anke Meyer-Bäse, Peter Gruber, Fabian J. Thei...
ESANN
2003
9 years 9 months ago
Comparison of neural algorithms for blind source separation in sensor array applications
- A test bed of experiments with real and artificially generated data has been designed to compare the performance of three well-known algorithms for BSS. The main goal of these ex...
Guillermo Bedoya, Sergio Bermejo, Joan Cabestany
ISNN
2005
Springer
10 years 1 months ago
A Learning Framework for Blind Source Separation Using Generalized Eigenvalues
This paper presents a learning framework for blind source separation (BSS), in which the BSS is formulated as generalized Eigenvalue (GE) problem. Compared to the typical informati...
Hailin Liu, Yiu-ming Cheung
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