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Block based Partial update NLMS Algorithm for Adaptive Decision Feedback Equalization

机译:基于块的适应性判定反馈均衡的部分更新NLMS算法

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Decision feedback equalizers are commonly employed to reduce the intersymbol interference that is caused by the time dispersive channel.In this paper a block based partial update normalized LMS algorithm is proposed,which significantly reduces the computational complexity over the other LMS based algorithms .The important characteristic of this algorithm is that only a part of the filter coefficients are updated in every iteration. The frequency domain representation facilitates, easier to choose step size with which the proposed algorithm convergent in the mean squared sense, whereas in the time domain it requires the information on the largest eigen value of the correlation matrix of the input sequence. Simulation studies shows that the proposed realization gives good performance characteristic in terms of convergence rate.
机译:判定反馈均衡器通常用于降低由时间分散通道引起的偶尔ymbol干扰。本文提出了一种基于块的部分更新归一化LMS算法,这显着降低了基于LMS的基于LMS的计算复杂性。重要的特征其中该算法是每次迭代中只更新滤波器系数的一部分。频域表示便于,更容易选择步骤尺寸,其中所提出的算法会聚在平均平方义中,而在时域中,它需要关于输入序列的相关矩阵的最大特征值的信息。仿真研究表明,建议的实现在收敛速度方面具有良好的性能特征。

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