Hebbian- and anti-Hebbian-type neural network for blind separation of nonstationary signals

Anke Meyer-Baese

doi:10.1117/12.421166

21 March 2001 Hebbian- and anti-Hebbian-type neural network for blind separation of nonstationary signals

Anke Meyer-Baese

Proceedings Volume 4390, Applications and Science of Computational Intelligence IV; (2001) https://doi.org/10.1117/12.421166
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

This contribution describes a neural network that self- organizes to recover the original signals from sensor signals. No particular information is required about the statistical properties of the sources and the coefficients of the linear-transformation, except the fact that the source signals are statistically independent and non- stationary. The learning rule for the network's parameters is derived from the steepest descent minimization of a time- dependent cost function that takes the minimum only when the network outputs are correlated with each other.

Citation Download Citation

Anke Meyer-Baese "Hebbian- and anti-Hebbian-type neural network for blind separation of nonstationary signals", Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, (21 March 2001); https://doi.org/10.1117/12.421166

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