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Blind 8PSK signals detection using discrete complex-valued Hopfield network

机译:使用离散复数值Hopfield网络进行盲8PSK信号检测

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The conventional neural networks which are limited to two-state neurons are not able to solve the problem of blind multi-state signal detection. A new algorithm based on discrete complex-valued Hopfield neural network(DCHNN) is proposed to detect MPSK signals blindly. Based on the energy minimization performed by the network, this paper suggests an direct design procedure that gives a Hermitian weight matrix such that each constellation signal in the MPSK state space is an attractive fixed point of the network‥ Simulation results show that the algorithm reaches the real equilibrium points and show satisfactory performance in detecting MPSK signals blindly.
机译:限于二态神经元的常规神经网络不能解决盲多态信号检测的问题。提出了一种基于离散复值Hopfield神经网络(DCHNN)的盲检测MPSK信号的新算法。基于网络执行的能量最小化,本文提出了一种直接设计程序,该程序给出了一个Hermitian权重矩阵,使得MPSK状态空间中的每个星座信号都是网络的一个吸引人的固定点。仿真结果表明,该算法达到了真实的平衡点,在盲目检测MPSK信号方面表现出令人满意的性能。

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