| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1713248 | Journal of Systems Engineering and Electronics | 2006 | 5 Pages |
Abstract
A new equalization method is proposed in this paper for severely nonlinear distorted channels. The structure of decision feedback is adopted for the non-singleton fuzzy regular neural network that is trained by gradient-descent algorithm. The model shows a much better performance on anti-jamming and nonlinear classification, and simulation is carried out to compare this method with other nonlinear channel equalization methods. The results show the method has the least bit error rate (BER).
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Song Heng, Wang Chen, He Yin, Ma Shiping, Zuo Jizhang,