| Autor: |
Sakar, F. Müge, Aydoğan, S. Melike |
| Předmět: |
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| Zdroj: |
International Journal of Open Problems in Computer Science & Mathematics; Jun2023, Vol. 16 Issue 2, p71-82, 12p |
| Abstrakt: |
The sigmoid function increases the size of the hypothesis space that the network can represent. Neural networks can be used for complex learning tasks. It is therefore necessary to investigate the role of sigmoid function in geometric function theory. In this study, a new subclass of bi-starlike functions involving Sigmoid function and Bernol li Lemniscate was defined. Some coefficient bounds belonging to this newly defined subclass were also obtained by using subordination principle. The key tools in the proof of our main results are the coefficient Fekete-Szegö inequalities for this subclass. The results obtained agree and extend some earlier results. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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