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

机译:盲8Psk信号检测使用离散复合值Hopfield网络

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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:常规神经网络限于两个状态神经元不能解决盲多状态信号检测的问题。提出了一种基于离散复值的Hopfield神经网络(DCHNN)的新算法来盲目地检测MPSK信号。基于网络执行的能量最小化,本文提出了一种直接的设计过程,其给出了隐士权重矩阵,使得MPSK状态空间中的每个星座信号是网络的有吸引力的固定点,仿真结果表明该算法达到了盲目地检测MPSK信号的实际均衡点并显示出令人满意的性能。

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