Structure Identification of an Associative Memory Network Using Genetic Algorithm

• Autorzy: Horbowski R. , Białko M.
• Języki publikacji: EN

Abstrakty

EN

In the paper a novel approach to the structure identification of the lattice associative memory network is presented. In the investigated network B-spaline basis functions are used, and the network structure (i.e.a number, a distribution and a shape of the basis functions) is determined by means of a genetic algorithm. The proposed approach is partly able to make use of structural dependencies existing in training data which, in connection with high interpretability of the lattice network, can provide the modeller with valuable knowledge about the process or system being modelled. This knowledge can help to select relevant model inputs and hence the model size.

Słowa kluczowe

EN

neural networks; associative memory networks; genetic algorithms; neurofuzzy modelling

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2001
• Tom: vol. 49, nr 1
• Strony: 125--139
• Opis fizyczny: 7 rys., 1 tabela, bibliogr. 13 poz.

Twórcy

autor

Horbowski R.

autor

Białko M.

• Technical University of Gdańsk, Department of Electronics, Telecommunication and Informatics, ul. G. Narutowicza 11/12, 80-952 Gdańsk, Poland (Wydział Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej)