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

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

降低多载波调制峰均功率比的混沌神经网络

DOI：
10.1109/ijcnn.2003.1223803
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发表时间：
2003
期刊：
Proceedings of the International Joint Conference on Neural Networks, 2003.
影响因子：
--
通讯作者：
K. Yamashita
K. Yamashita
中科院分区：
--
文献类型：
--
作者：
M. Ohta;K. Yamashita

文献摘要

被引文献

相似文献

提出了一种降低多载波调制系统的峰均功率比的新方法。将约简问题表述为组合优化问题，采用结构简单、适合实时优化的混沌神经网络（CNN）进行求解。实验结果表明，与传统方法相比，CNN具有更好的性能。最后考虑了CNN参数与混沌行为之间的关系。
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 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.