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A palimpsest memory...
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Sandberg, AndersKTH,Numerisk analys och datalogi, NADA
(author)
A palimpsest memory based on an incremental Bayesian learning rule
- Article/chapterEnglish2000
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LIBRIS-ID:oai:DiVA.org:kth-19860
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https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-19860URI
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https://doi.org/10.1016/S0925-2312(00)00270-8DOI
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http://kipublications.ki.se/Default.aspx?queryparsed=id:1946102URI
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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The 8th Annual Computational Neuroscience Meeting (CNS'99); Pittsburgh, PA, USA; 18 July 1999 through 22 July 1999
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Capacity limited memory systems need to gradually forget old information in order to avoid catastrophic forgetting where all stored information is lost. This can be achieved by allowing new information to overwrite old, as in the so-called palimpsest memory. This paper describes a new such learning rule employed in an attractor neural network. The network does not exhibit catastrophic forgetting, has a capacity dependent on the learning time constant and exhibits recency effects in retrieval.
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Lansner, AndersKTH,Numerisk analys och datalogi, NADA(Swepub:kth)u12s8cr8
(author)
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Petersson, K. M.Karolinska Institutet
(author)
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Ekeberg, ÖrjanKTH,Numerisk analys och datalogi, NADA(Swepub:kth)u1oppomp
(author)
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KTHNumerisk analys och datalogi, NADA
(creator_code:org_t)
Related titles
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In:Neurocomputing32, s. 987-9940925-23121872-8286
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