该方法还可以用于其它信号处理领域高斯白噪声的估计。
This method can also be used in other signal processing field to estimate white Gaussian noise.
高阶统计量在信号处理中成功的应用例子之一是估计高斯相关噪声中非高斯信号的时延参数。
One of the primary applications of higher order statistics has been for the time delay estimation of non-Gaussian signal in Gaussian spatially correlated noise.
自适应IIR陷波器在许多不同的信号处理场合，尤其在估计淹没在噪声中的正弦波频率方面得到广泛应用。
The Adaptive IIR notch filter has been widely used in many signal processing applications, especially in the estimation of the sinusoid component with unknown frequency buried in noise.
自适应噪声抵消器在高信噪比条件下往往难以取得良好的处理效果，从而使其在参数估计方面的应用受到了很大的限制。
The application of an adaptive noise canceller to parameter estimating is restricted for its unsatisfactory performance in the condition of high SNR input.
在图像处理中，噪声估计是个重要问题。
Noise estimation is one of the most important research topics in image processing.
目前的处理方法普遍需要估计噪声或者信噪比，从而其性能依赖于噪声估计的好坏。
Most resent approaches to the problem employ noise estimate or Signal-Noise Ratio (SNR) estimate, and hence their performances depend on the estimation of noise.
我们将稀疏信号处理应用于冲击噪声下的OFDM信道估计问题。
We apply sparse signal processing to OFDM channel estimation under impulse noise.
利用实际航路数据比较噪声在四种情况下的目标位置估计性能，验证了处理有色噪声的必要性。
With the state augmentation approach and the measurement difference approach, the effect of colored noise can be alleviated.
它不仅能够获取信号的最佳估计，并且能够克服信号处理中存在的模型和噪声的不确定性、不完备性。
The adaptive noise cancellation based on the AFNNS can achieve an optimal reconstruction of signals and a desired robust against the effect of uncertainties in signal processing.
噪声的方差估计是含噪图像处理中的常见问题之一，其基本思想是通过某种方法寻找含噪图像中的“纯”噪声子图像来估计原噪声方差。
Variance estimation is a common problem in noised image processing. The basic idea is to get a sub-image that includes only "pure" noise to estimate the variance of original noise.
噪声的方差估计是含噪图像处理中的常见问题之一，其基本思想是通过某种方法寻找含噪图像中的“纯”噪声子图像来估计原噪声方差。
Variance estimation is a common problem in noised image processing. The basic idea is to get a sub-image that includes only "pure" noise to estimate the variance of original noise.
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