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- 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。
- 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]。
- 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。
- Theoretical analysis and simulation results indicate this algorithm's validity, with low SNR and colored noise environment. 理论分析和仿真结果均表明在低信噪比色噪声情况下该算法的有效性。
- The computer simulation and practical application can justify the effectiveness and reliability of this algorithm in low SNR. 计算机仿真实验及实际应用证明了该算法在较低的信噪比条件下具有良好的工作性能。
- Sinc data interpolation method is more suitable for those systems which have a stringent demand for low SNR environment and acquisition time. Sinc内插算法更适合在低信噪比下工作和对捕获时间有严格要求的系统。
- By simulation, it shows that this method can realize precise sorting under low SNR, and it is better than other methods. 计算机仿真结果表明,较现有方法,该方法在较低的信噪比情况下,可以更准确地实现雷达辐射源信号的分选。
- Simulations show by this method we can precisely estimate time delay for narrow band and line spectrum source in low SNR. 通过计算仿真结果证明这种方法对低信噪比下窄带和单频信号具有较高时延估计精度。
- The experiments show that the method can fleetly and reliably detect the small target with low SNR, which has achieved the demand of high performance. 实验结果表明:该方法可以快速、可靠的检测出极低信噪比下的小目标,满足了系统性能指标。