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Effective adaptive noise canceller design using normalized LMS

机译:使用归一化LMS的有效自适应噪声消除器设计

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This paper presents the application of Adaptive filters in noise cancellation during various communication processes, where non-stationary signals are transmitted. Adaptive filter estimates the noise signal and by applying the appropriate weights the estimated noise signal is eliminated from the information. For noise cancellation applications most efficient Adaptive filter Algorithms LMS and its normalized form NLMS are used and their comparative analysis is done in form of their output power, error power and SNR. In both of the algorithms concept of negative feedback is utilized in the cancellation of noise from the signal and thus both of these are also called negative feedback algorithms. Implementation and analysis is done by applying different step sizes on different order of filter. Order of filter is taken as 4, 8, 12 and then by changing the values of coefficients the graphical and computational analysis is done. Finally an efficient design using NLMS algorithm is implemented where order is taken as 8 and step size 0.2. This results as a low error power (11.7221 db) and a high value of SNR (1.1445) than that of LMS algorithms.
机译:本文介绍了自适应滤波器在各种传输非平稳信号的通信过程中的噪声消除中的应用。自适应滤波器估计噪声信号,并通过施加适当的权重,从信息中消除估计的噪声信号。对于噪声消除应用,使用了最有效的自适应滤波器算法LMS及其规范化形式NLMS,并以输出功率,误差功率和SNR的形式进行了比较分析。在这两种算法中,都使用负反馈来消除信号中的噪声,因此,这两种方法也都称为负反馈算法。通过在不同阶数的滤波器上应用不同的步长来执行和分析。滤波器的阶数取为4、8、12,然后通过更改系数的值进行图形和计算分析。最终实现了使用NLMS算法的高效设计,其中阶数为8,步长为0.2。与LMS算法相比,这导致较低的错误功率(11.7221 db)和较高的SNR(1.1445)。

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