Abstract
Introducing partial connectivity to an associative memory network increases the variance of the dendritic sum distributions, reducing the performance. A coding scheme to compensate for this effect is considered, in which output patterns are self-organised by the network. It is shown using signal-to-noise ratio analysis that when the output patterns are self-organised the performance is greater than in a network with a higher connectivity and random patterns, in the regime of low connectivity and a high memory load. This analysis is supported by simulations. The self-organising network also outperforms the random network with input activity-dependent thresholding mechanisms in simulations.
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Longden, K. (2005). Recovery of Performance in a Partially Connected Associative Memory Network Through Coding. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_31
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DOI: https://doi.org/10.1007/11550822_31
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