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

	This Article
	Subscribers, please Login Purchase article: $19 PDF IEEE Xplore Subscribers RSS feed
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Bruno Cernuschi-Frías Articles by Enrique C. Segura

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

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.