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首页> 外文期刊>Journal of Computers >Algorithms and Applications for Estimating the Standard Deviation of AWGN when Observations are not Signal-Free
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Algorithms and Applications for Estimating the Standard Deviation of AWGN when Observations are not Signal-Free

机译：用于估计AWGN的标准偏差的算法和应用，当观察不是无信号时

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—Consider observations where random signals are randomly present or absent in independent and additive white Gaussian noise (AWGN). By using a recently established limit theorem, we introduce a new estimator for the estimation of the noise standard deviation when the signals are less present than absent and have unknown probability distributions. The bias, the consistency and the minimum attainable mean square estimation error of the estimator we propose are still unknown. However, the experimental results that are presented are very promising. First, when the Minimum- Probability-of-Error decision scheme for the non-coherent detection of modulated sinusoidal carriers in independent AWGN is tuned with the outcome of our estimator instead of the true value of the noise standard deviation, the Binary Error Rate tends to the optimal error probability when the number of observations is large enough. Second, given some speech signal corrupted by independent AWGN, our estimator can be used to estimate the noise standard deviation so as to adjust the standard Wiener filtering of the noisy speech. The objective performance measurements obtained by so proceeding are very close to those achieved when the Wiener filtering is tuned with the true value of the noise standard deviation.
机译：- 在独立和添加剂白色高斯噪声（AWGN）中随机存在或不存在随机信号的分析率。通过使用最近建立的限制定理，我们将介绍一个新的估计器，用于估计噪声标准偏差，当信号较小而非不存在并且具有未知的概率分布时。我们提出的估计器的偏差，一致性和最小可达到的均值均值估计误差仍然未知。然而，提出的实验结果非常有前途。首先，当与我们的估计器的结果进行独立的AWGN中的调制正弦载波的不相干检测的最小概率判定方案，而不是我们的估计器的结果而不是噪声标准偏差的真实值，则二进制错误率趋于当观察数足够大时，最佳误差概率。其次，考虑到由独立的AWGN损坏的一些语音信号，我们的估算器可用于估计噪声标准偏差，以便调整嘈杂语音的标准维纳滤波。通过如此继续获得的客观性能测量值非常接近当用噪声标准偏差的真实值调整维纳滤波时所实现的那些。

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