1、

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。

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2、

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。

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3、

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。

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4、

according to hypothesis about the implementation of multi-user signal detector with continuous hopfield neural network a kind of hopfield-based multi-user signal detector for synchronous ds/ cdma ( direct sequence code division multiple access) system has been constructed.

用连续Hopfield神经网络实现CDMA通信系统中多用户信号检测的设想,并针对同步CDMA系统构造了基于连续Hopfield神经网络的用户信号检测器。

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5、

the signal detection is modeled by the binary hypothesis test.

建立了部分极化信号检测模型;

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6、

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.

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