电子学报2013，Vol.41Issue(2)：255-259,5.DOI:10.3969/j.issn.0372-2112.2013.02.008
基于实虚型连续多值复数Hopfield神经网络的QAM盲检测
Blind Detection of QAM Signals with a Complex Hopfield Neural Network with Real-Imaginary-Type Soft-Multistate-Activation-Function
摘要
Abstract
Considering the disadvantage of the algorithms based on statistics, a novel algorithm based on Complex Hopfield Neural Network with Real-Imaginaiy-type Soft-Multistate-activatlon-funetion (CHNN_ RISM) is proposed to detect QAM signals blindly. A multi-valued continuous activation function is constructed in both of the real part and imaginary part of CHNN_ RISM. A new energy function for CHON. RISM is constructed in this paper and the stabilities with asynchronous and synchronous operating mode are also analyzed separately. While the weighted matrix of CHNN_ RISM is constructed by the complementary projection operator of received signals, the problem of quadratic optimization with integer constraints can successfully solved with the CHNN_ RISM, and the QAM signals are blindly detected. Simulation results show that the algorithm reaches the real equilibrium points with shorter received signals and appropriate for channel with common zeros.关键词
QAM信号/实虚型连续多值复数Hopfield神经网络/盲检测/含公零点信道Key words
QAM signal/ complex hopfield neural network with real-imaginary-type soft-midtistate-activation-function (CHNN_ RISM)/blind detection/channel with common zeros分类
信息技术与安全科学引用本文复制引用
张昀,于舒娟,张志涌,郭宇峰..基于实虚型连续多值复数Hopfield神经网络的QAM盲检测[J].电子学报,2013,41(2):255-259,5.基金项目
国家自然科学基金(No.60772060,No.NY212022) （No.60772060,No.NY212022）
