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- Alternating notch periodogram algorithm (ACPA) based on maximum likelihood (ML) can regarded as a complete solution to the discrete spectrum estimation problem since it achieves superresolution, very high accuracy, and low SNR threshold. 基于最大似然法的交替陷波周期图算法（ANPA）是一种超分辨率的谱估计算法，它同时具有超分辨率、高精度和低信噪比门限的特性。
- Lower SNR threshold 低信噪比门限
- A new method, the wavelet based neural network method is presented to estimate hearing threshold from BAEP signal.The results of test show that this method has high performance in low SNR. 本文提出了一种新的听阈检测方法:基于小波变换的神经网络检测方法。
- The proposed method may estimate Doppler rate robustly in the case of low SNR. 在信噪比较低的条件下此方法可以稳健地估计多普勒调频率。
- Moreover, the SNR threshold for correctly identifying type parameter is so high so that it is infeasible in complex environment. 另外，鉴别散射中心类型要求非常高的信噪比，在复杂环境下难以实现。
- In addition, a SAR interferogram noise reduction algorithm based on the SNR threshold is proposed with detailed flow graph analysis. 在此滤波方法的基础上， 进一步提出了基于信噪比门限判断的干涉图两级处理滤波法，并对其处理流程做了详细的讨论。
- The simulation used Db3 wavelet and two original images with low SNR. 此后许多研究成果都拓宽了此方法的应用前景[3]。
- Then cumulant invariants are used to classify bandlimited MPSK signals.The method can work with lower SNR. 并利用此基带序列的高阶累积量构造分类特征不变量,在宽信噪比范围内实现了带限MPSK信号的调制分类。
- It is an unfathomed and difficult problem that weak and small targets are detected in complicated background and low SNR. 摘要复杂背景下低信噪比弱小目标的自动检测是当今目标自动探测研究尚未解决的一个难题。
- Fluctuation complexity is a valid feature to make speech/non-speech decision for the low SNR cases. 涨落复杂性测度技术可以较好地实现在动态噪声环境下对语音端点的检测。
- The effective detection for small targets in low SNR images has becoming a hot research field these years. 摘要低信噪比条件下的小目标检测问题一直是近些年来国内外学者研究的一个热门课题。
- The simulating results show that the proposed method can detect the endpoint exactly in the low SNR environments. 仿真实验表明此方法快速有效，具有较强的抗噪能力，特别适合低信噪比下的端点检测。
- Conventional methods cannot work well in the condition of low SNR or at a variable background noise level. 常规的检测算法在低信噪比尤其在背景噪声能量可变的环境下不能有效工作。
- Two low SNR image sequences energy accumulation algorithms in common use are discussed. 讨论了两种常用的低信噪比图像序列能量累加算法,一种是针对帧间运动速度较小的多帧累加;
- Track-Before-Detect(TBD) is an efficient approach which detects and tracks targets in low SNR environment. 检测前跟踪技术是低信噪比环境下目标检测与跟踪的有效方法。
- Simulation shows that this method can accurately recover the modulating signal in low SNR circumstance. 仿真结果显示,该方法在较低信噪比环境下能够准确地恢复调制信号。
- Based on cyclic diagonal codes, an improved design of unitary space-time codes (USTC) at low SNR is proposed. 摘要在低信噪比情况下，提出了一种基于循环对角码的改进的酉空时码设计。
- Conclusion Fluctuation complexity is a valid feature to make speech/non-speech decision for the low SNR cases. 结论涨落复杂性测度技术可以较好地实现在动态噪声环境下对语音端点的检测。
- Based on cyclic diagonal codes,an improved design of unitary space-time codes(USTC) at low SNR is proposed. 在低信噪比情况下,提出了一种基于循环对角码的改进的酉空时码设计。
- Track before Detect technology for dim small moving targets in low SNR image sequences was surveyed. 对低信噪比下图像序列运动小目标先跟踪后检测技术进行了较为系统地研究。
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