dc.contributor.author | Davey, N. | |
dc.contributor.author | Adams, R.G. | |
dc.contributor.author | Hunt, S. | |
dc.date.accessioned | 2011-11-21T15:01:08Z | |
dc.date.available | 2011-11-21T15:01:08Z | |
dc.date.issued | 2001 | |
dc.identifier.citation | Davey , N , Adams , R G & Hunt , S 2001 , High performance associative memory models and weight dilution . in Procs of Int Conf on Neural Information Processing : ICONIP'01 . vol. 2 , pp. 597-602 . | |
dc.identifier.other | PURE: 455208 | |
dc.identifier.other | PURE UUID: 57faea69-222d-4004-8309-5b53c690ebe7 | |
dc.identifier.other | dspace: 2299/824 | |
dc.identifier.uri | http://hdl.handle.net/2299/7048 | |
dc.description.abstract | The consequences of diluting the weights of the standard Hopfield architecture associative memory model, trained using perceptron like learning rules, is examined. A proportion of the weights of the network are removed; this can be done in a symmetric and asymmetric way and both methods are investigated. This paper reports experimental investigations into the consequences of dilution in terms of: capacity, training times and size of basins of attraction. It is concluded that these networks maintain a reasonable performance at fairly high dilution rates. | en |
dc.language.iso | eng | |
dc.relation.ispartof | Procs of Int Conf on Neural Information Processing | |
dc.title | High performance associative memory models and weight dilution | en |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Science & Technology Research Institute | |
dc.contributor.institution | Centre for Computer Science and Informatics Research | |
rioxxterms.version | AM | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |