噪

First, SNR of point target echo and gain of SAR signal processing are analyzed in detail.

主要研究了对SAR的噪声干扰，分析了点目标回波的信噪比以及SAR信号处理的增益，在此基础上建立了两种干扰噪声的模型。

The experimental results show that this method performs better than that based on short energy in low SNR.

实验结果表明它能够在极低信噪比下对语音段的端点进行准确的检测，明显优于传统的能量检测算法。

In this paper,the interference among the multi-carrier is analyzed and regarded as degradation of SNR.

首先分析了由载波引起的载波间干扰，将其等效为系统信噪比的降低。

Through the computer simulation, all of these algorithms can work in lower SNR.

仿真实验表明，总体上这些方法可以作到较低的信噪比容限。

How to improve the performance of modulation recognition algorithms in low SNR becomes an important theme for their applications.

如何提高调制识别算法在低信噪比时的识别性能，是调制识别技术工程应用中必须解决的重要课题。

But the performance of these methods becomes poor in the lower SNR.

但是这些方法在低信噪比的条件下，性能均出现不同程度的下降。

Simulations indicate that significant SNR can be obtained and the system performance is better than that of single antenna case.

仿真实验结果表明，本文所提出的模型可以获得较好的信噪比，与单天线相比MIMO-OFDM系统性能明显提高。

And then an improved approach is proposed for estimating the SNR of SDR receiver.

进而提出一种改进的估计SDR接收机信噪比的方法。

Simulation results are mainly embodied in SNR.

仿真结果主要体现为信噪比。

First of all, modeling image by fractional-order derivative and negative Sobolev space, this paper presents a fractional-order multi-scale variation PDE model, and the proposes the adaptive parameter selection method and obtains the field and scale adaptively algorithm for SAR image denoising.

首先利用分数阶导数以及负指数Sobolev 空间对图像进行建模，建立了分数阶多尺度变分PDE 模型，然后给出了模型参数自适应选择方法，并在此基础上提出了区域、尺度自适应的SAR 图像去噪算法。

In the negative and interrogative forms, of course, this is identical to the non-emphatic forms.

。但是，在否定句或疑问句里，这种带有"do"的方法表达的效果却没有什么强调的意思。

Go down on one's knees;kneel down

屈膝跪下。。。下跪祈祷