A chaotic neural network for reducing the peak-to-average power ratio of multicarrier modulation

被引：0
|
作者：
Ohta, M [1 ]
Yamashita, K [1 ]
机构：
[1] Univ Osaka Prefecture, Grad Sch Engn, Dept Elect & Elect Syst, Sakai, Osaka 5998531, Japan
来源：
PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4 | 2003年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel method for the peak-to-average power ratio reduction on multicarrier modulation systems is proposed. The reduction problem is formulated as a combinatorial optimization, and is solved by using the chaotic neural network (CNN), which has easy structure and is suitable for real time optimization. Experimental results show that CNN has better performance than conventional methods. Finally we consider relationship between a parameter of CNN and the chaotic behavior.
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页码：864 / 868
页数：5
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