signal hypothesis

In machine learning, the sparsity of hypothesis functions is expected to improve the generalization performance and the test speed. Moreover the sparse signal reconstruction is a crucial problem in compressed sensing ( CS).

在机器学习中假设函数的稀疏性对检验速度和推广性能是至关重要的，而稀疏信号的重构在压缩感知中也扮演着举足轻重的作用。

The watermark embedded in this algorithm is a significant binary image and adaptively embedded according to frequency masking threshold of audio signal. The watermark can be extracted by hypothesis test.

嵌入的水印为视觉可辨的二值图像，水印能根据音频信号的频域掩蔽阈值进行自适应调整，水印的提取采用假设检验的方法。

All analysis and conclusions build on monopulse radar and high signal-to-noise ratio hypothesis.

所有结论及分析都是在高信噪比假设下针对单脉冲测角体制而言的.

Therefore the experiments provide an example to validate the hypothesis that the binaural masking effect is the result of the high level auditory system processing binaural sound signal, and it also hints that by using stereophonic, reproduction speech intelligibility can be improved in communication systems.

因此文中的实验为双耳掩蔽是听觉系统的高层对双耳信号处理这假设提供了例证，并提示通信系统采用立体声作可提高重发语言清晰度。

Finally, for complex variable background noise, the adaptive threshold is proposed to improve the constant threshold test method of hypothesis testing to detect the RF signal in low SNR.

最后针对复杂时变背景噪声，提出采用自适应门限以改进恒定门限检验的假设检验方法，在低信噪比下对射频信号进行检测。