| 高斯白噪声下LMS算法的改进 |
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| 引用本文： | 李小红,钱源诚. 高斯白噪声下LMS算法的改进[J]. 合肥工业大学学报(自然科学版), 1998, 0(5) |
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| 作者姓名： | 李小红 钱源诚 |
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| 摘 要： | 自适应（ＡＲ）模型是数字信号处理中广为应用的一种模型，它的系数可以通过ＬＭＳ算法求解。但当输入信号受到高斯白噪声干扰时，用ＬＭＳ算法求得的解误差很大，所以提出了改进的算法。通过理论分析，指出这种算法的有效性。
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| 关 键 词： | AR模型 LMS算法 高斯噪声 |
THE IMPROVING METHOD FOR THE LEAST MEAN SQUARE(LMS) ALGORITHM UNDER WHITE GAUSSIAN NOISE |
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| Li Xiaohong Qian Yuancheng. THE IMPROVING METHOD FOR THE LEAST MEAN SQUARE(LMS) ALGORITHM UNDER WHITE GAUSSIAN NOISE[J]. Journal of Hefei University of Technology(Natural Science), 1998, 0(5) |
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| Authors: | Li Xiaohong Qian Yuancheng |
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| Affiliation: | Li Xiaohong Qian Yuancheng |
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| Abstract: | Auto regressive (AR) modeling is widely used in signal processing. The coefficients of an AR model can be easily obtained with an LMS algorithm. But the filter gives a biased solution when the input signal is contaminated by white Gaussian noise. This paper develops an improved LMS algorithm with theoretical analysis showing its better performance. |
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| Keywords: | auto regressive (AR) modeling least mean square algorithm white Gaussian noise |
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