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利用Lagrange神经网络的基本原理,在线性约束恒模算法(LCCMA)基础上,通过增加约束条件,提出了一种多约束Lagrange神经网络恒模“盲多用户检测”算法.通过仿真实验表明,算法比传统最陡下降恒模算法(SDCMA)在误码率等方面有所改善.
By using the basic principle of Lagrange neural network and based on Linear Constrained Constant Modulus Algorithm (LCCMA), a constrained Lagrange neural network (LCCMA) algorithm is proposed to simulate Lagrange neural networks with multi-constraint Lagrange neural networks. Compared with the traditional Steepest Descent Constant Modulus Algorithm (SDCMA), the proposed algorithm improves the bit error rate.