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Raport Badawczy = Research Report ; RB/29/2004
Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences
24 stron ; 21 cm ; Bibliografia s. 21-24
In this paper the Hopfield neural network model of associative memory that uses evolutionary approach as a learning method is analyzed. Several types of genetic algorithms will be investigated. In resulting networks quality measures (such as storage capacity, error correcting capabilities and the usage of additional knowledge) will be carefully examined. The basic criterion for algorithm’s evaluation is the storage capacity. The well-known Hebbian rule provides the capacity to be 15% of the number of the neurons. It has been shown that genetic algorithms allow us to improve this result.
Raport Badawczy = Research Report
Licencja Creative Commons Uznanie autorstwa 4.0
Zasób chroniony prawem autorskim. [CC BY 4.0 Międzynarodowe] Korzystanie dozwolone zgodnie z licencją Creative Commons Uznanie autorstwa 4.0, której pełne postanowienia dostępne są pod adresem: ; -
Instytut Badań Systemowych Polskiej Akademii Nauk
Biblioteka Instytutu Badań Systemowych PAN
Oct 19, 2021
Sep 17, 2020
34
https://rcin.org.pl./publication/175021
Edition name | Date |
---|---|
RB-2004-29 : Wilbik Anna : Genetic algorithms in learning methods of associative memory | Oct 19, 2021 |
Gorączko, Marcin Cichowska, Jolanta
Stańczak, Jarosław
Novotny, Antonio Szulc, Katarzyna Żochowski, Antoni
Grądzki, Piotr
Kacprzyk, Janusz (1947– ) Wilbik, Anna
Kacprzyk, Janusz (1947– ) Wilbik, Anna