- Tytuł:
- Beta neuro-fuzzy systems
- Autorzy:
- Alimi, A. M.
- Powiązania:
- https://bibliotekanauki.pl/articles/1931568.pdf
- Data publikacji:
- 2003
- Wydawca:
- Politechnika Gdańska
- Tematy:
-
beta function
kernel based neural networks
Sugeno fuzzy model
neuro-fuzzy systems
universal approximation property
learning algorithms
incremental learning - Opis:
- In this paper we present the Beta function and its main properties. A key feature of the Beta function, which is given by the central-limit theorem, is also given. We then introduce a new category of neural networks based on a new kernel: the Beta function. Next, we investigate the use of Beta fuzzy basis functions for the design of fuzzy logic systems. The functional equivalence between Beta-based function neural networks and Beta fuzzy logic systems is then shown with the introduction of Beta neuro-fuzzy systems. By using the SW theorem and expanding the output of the Beta neuro-fuzzy system into a series of Beta fuzzy-based functions, we prove that one can uniformly approximate any real continuous function on a compact set to any arbitrary accuracy. Finally, a learning algorithm of the Beta neuro-fuzzy system is described and illustrated with numerical examples.
- Źródło:
-
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2003, 7, 1; 23-41
1428-6394 - Pojawia się w:
- TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
- Dostawca treści:
- Biblioteka Nauki
Artykuł