On Learning Mean Values in Hopfield Associative Memories Trained with Noisy Examples Using the Hebb Rule

I
IJCNN
2000
IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4
Abstract - On Learning Mean Values in Hopfield Associative Memories Trained with Noisy Examples Using the Hebb Rule

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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4

Como, Italy

July 24-July 27

ISBN: 0-7695-0619-4

	ASCII Text	x
	Bruno Cernuschi-Frías, Enrique C. Segura, "On Learning Mean Values in Hopfield Associative Memories Trained with Noisy Examples Using the Hebb Rule," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 4, pp. 4023, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4, 2000.

	BibTex	x
	@article{ 10.1109/IJCNN.2000.860740, author = {Bruno Cernuschi-Frías and Enrique C. Segura}, title = {On Learning Mean Values in Hopfield Associative Memories Trained with Noisy Examples Using the Hebb Rule}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {4}, year = {2000}, issn = {1098-7576}, pages = {4023}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.860740}, 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 - On Learning Mean Values in Hopfield Associative Memories Trained with Noisy Examples Using the Hebb Rule SN - 1098-7576 SP EP A1 - Bruno Cernuschi-Frías, A1 - Enrique C. Segura, PY - 2000 KW - Neural Networks KW - Unsupervised Learning KW - Classification KW - Clustering VL - 4 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER -

Bruno Cernuschi-Frías, Universidad de Buenos Aires and CONICET.

Enrique C. Segura, Universidad de Buenos Aires and CONICET.

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.860740

We study, using standard Probability Theory results, the ability of the Hopfield model of associative memory using the Hebb rule to learn mean values from examples in the presence of noise. We state and prove properties concerning this ability.

Index Terms:

Neural Networks, Unsupervised Learning, Classification, Clustering

Citation:

Bruno Cernuschi-Frías, Enrique C. Segura, "On Learning Mean Values in Hopfield Associative Memories Trained with Noisy Examples Using the Hebb Rule," ijcnn, vol. 4, pp.4023, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4, 2000

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