Complete Stability of Delayed Recurrent Neural Networks With New Wave-Type Activation Functions.
IEEE Trans Neural Netw Learn Syst
; PP2024 May 06.
Article
en En
| MEDLINE
| ID: mdl-38709607
ABSTRACT
Activation functions have a significant effect on the dynamics of neural networks (NNs). This study proposes new nonmonotonic wave-type activation functions and examines the complete stability of delayed recurrent NNs (DRNNs) with these activation functions. Using the geometrical properties of the wave-type activation function and subsequent iteration scheme, sufficient conditions are provided to ensure that a DRNN with n neurons has exactly (2m + 3)n equilibria, where (m + 2)n equilibria are locally exponentially stable, the remainder (2m + 3)n - (m + 2)n equilibria are unstable, and a positive integer m is related to wave-type activation functions. Furthermore, the DRNN with the proposed activation function is completely stable. Compared with the previous literature, the total number of equilibria and the stable equilibria significantly increase, thereby enhancing the memory storage capacity of DRNN. Finally, several examples are presented to demonstrate our proposed results.
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Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
IEEE Trans Neural Netw Learn Syst
Año:
2024
Tipo del documento:
Article