An almost sure central limit theorem for the overlap parameters in the Hopfield model

Barbara Gentz

Stochastic Processes and their Applications, 1996, vol. 62, issue 2, 243-262

Abstract: We consider the Hopfield model with a finite number of randomly chosen patterns above and below the critical temperature and prove an almost sure conditional central limit theorem for the vector of overlap parameters. For this purpose we analyse the almost sure asymptotic behaviour of the partition function.

Keywords: Fluctuations; Hopfield; model; Overlap; parameter; Neural; networks; Laplace's; method (search for similar items in EconPapers)
Date: 1996
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0304-4149(96)00055-5
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:62:y:1996:i:2:p:243-262

Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().