Synaptic Depression in Associative Memory Networks

I
IJCNN
2000
IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5
Abstract - Synaptic Depression in Associative Memory Networks

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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5

Como, Italy

July 24-July 27

ISBN: 0-7695-0619-4

	ASCII Text	x
	Dmitri Bibitchkov, J. Michael Herrmann, Theo Geisel, "Synaptic Depression in Associative Memory Networks," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 5, pp. 5050, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5, 2000.

	BibTex	x
	@article{ 10.1109/IJCNN.2000.861434, author = {Dmitri Bibitchkov and J. Michael Herrmann and Theo Geisel}, title = {Synaptic Depression in Associative Memory Networks}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {5}, year = {2000}, issn = {1098-7576}, pages = {5050}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861434}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on TI - Synaptic Depression in Associative Memory Networks SN - 1098-7576 SP EP A1 - Dmitri Bibitchkov, A1 - J. Michael Herrmann, A1 - Theo Geisel, PY - 2000 VL - 5 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER -

Dmitri Bibitchkov, Max-Planck-Institut f?r Str?mungsforschung

J. Michael Herrmann, Max-Planck-Institut f?r Str?mungsforschung

Theo Geisel, Max-Planck-Institut f?r Str?mungsforschung

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861434

We analyze the effects of synaptic depression on the stability of patterns stored in neural networks with low activity level. Applying mean-field theory, we show that the stationary states remain unaffected by the synaptic depression. However, the stability of memory patterns changes drastically causing a reduction of memory capacity. Further, it is demonstrated and confirmed by numerical calculations that the sensitivity of the network to input changes is enhanced.

Citation:

Dmitri Bibitchkov, J. Michael Herrmann, Theo Geisel, "Synaptic Depression in Associative Memory Networks," ijcnn, vol. 5, pp.5050, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5, 2000

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