Abstract
The paper proposes new neuron model with an aggregation function based on Generalized harmonic mean of the inputs. Information-maximization approach has been used for training the new neuron model. The paper focuss on illustrating the efficiency of the proposed neuron model for blind source separation. It has been shown on various generated mixtures (for blind source separation) that the new neuron model performs far superior compared to the conventional neuron model. © 2009 Springer Berlin Heidelberg.
Cite
CITATION STYLE
Shiblee, M., Chandra, B., & Kalra, P. K. (2009). New neuron model for blind source separation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5507 LNCS, pp. 27–36). https://doi.org/10.1007/978-3-642-03040-6_4
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