1.
IEEE Trans Neural Netw
; 14(6): 1576-9, 2003.
Article
in English
| MEDLINE
| ID: mdl-18244604
ABSTRACT
A novel fuzzy-based activation function for artificial neural networks is proposed. This approach provides easy hardware implementation and straightforward interpretability in the basis of IF-THEN rules. Backpropagation learning with the new activation function also has low computational complexity. Several application examples ( XOR gate, chaotic time-series prediction, channel equalization, and independent component analysis) support the potential of the proposed scheme.