Linked Life Data

11031527

Source:http://linkedlifedata.com/resource/pubmed/id/11031527

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5 Pt A
pubmed:dateCreated
2000-11-14
pubmed:abstractText
We consider the categorization problem in a Hopfield network with an extensive number of concepts p = alpha N and trained with s examples of weight lambda tau, tau = 1,...,s in the presence of synaptic noise represented by a dimensionless "temperature" T. We find that the retrieval capacity of an example with weight lambda 1, and the corresponding categorization error, depend also on the arithmetic mean lambda m of the other weights. The categorization process is similar to that in a network trained with Hebb's rule, but for lambda 1/lambda m > 1 the retrieval phase is enhanced. We present the phase diagram in the T-alpha plane, together with the de Almeida-Thouless line of instability. The phase diagrams in the alpha-s plane are discussed in the absence of synaptic noise and several values of the correlation parameter b.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1063-651X
pubmed:author
pubmed:issnType
Print
pubmed:volume
61
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
4860-5
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Categorization in a Hopfield network trained with weighted examples: extensive number of concepts.
pubmed:affiliation
Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't