背景噪声

  • 网络background noise;noise floor
背景噪声背景噪声
  1. 一种用于3G系统中复杂背景噪声环境下的话音激活检测算法

    A novel VAD algorithm applied for 3G system in complex background noise environment

  2. 考虑CCD的背景噪声,对粒子图像做了降噪及增强处理。

    Considering the background noise of CCD , the particles images are reduced noise and enhanced .

  3. 背景噪声限下直接检测光PPM编码系统的性能研究

    A Study fo Coding for Background-limited Direct-detection Optical PPM Systems

  4. 自回归背景噪声生成方法及其VLSI实现

    On Generation of Background Noise with Autoregressive Data Model Technique and its VLSI Implementation

  5. 强背景噪声下AE信号的提取。

    Extraction of AE signals mixed with the strong background noise was studied .

  6. 在CDMA系统中,用户数的增加相当于背景噪声的增加。

    In the CDMA system , the equivalent to the increase in the number of users increased background noise .

  7. 模拟实验和实验结果的比较证明了对于PET重建,该先验在抑制背景噪声和保持边缘方面均具有很好的表现。

    Simulation experiments and comparisons proved that for PET reconstruction the new hybrid prior performs well in both lowering noise effect and preserving edges .

  8. ICA特征提取技术在背景噪声建模与分析中的应用

    The Application of Independent Component Analysis ( ICA ) Feature Extraction in Modeling and Analysis of Noises

  9. 计算机测量肺动脉和背景噪声的信号强度,计算出肺动脉的信噪比(SNR),并对肺动脉分支数量进行计数定量分析。

    Image quality were quantified by measuring signal-to-noise ratio ( SNR ) of pulmonary arteries and counting the numbers of pulmonary arteries .

  10. 脉冲LD测距系统的噪声主要包括热噪声、散粒噪声、背景噪声、暗电流噪声及放大器噪声。

    Such noises include thermal noise , particle noise , background noise , dark current noise as well as amplifier noises .

  11. 利用DSP实现时域信号的取样积累平均算法,改善信噪比,有效恢复淹没于强背景噪声中的微弱信号。

    The system adopt DSP accomplishing the arithmetic of sampling accumulate average of signal , improving Signal - to-Noise Rate , acquiring weak signal which shielded by vast powerful noise .

  12. 而且,发现疲劳裂纹信号与水轮机组现场背景噪声的AE参数值相差较大。

    In addition , the ranges of the AE parameters of fatigue crack signals and the background noise onsite are different .

  13. AnnexB提出了一种静音压缩算法(VAD),它将语音信号分为话音信号和背景噪声信号。

    Annex B introduce a voice activity decision ( VAD ) algorithm which class speech signal as voice signal and background noise signal .

  14. 该方法分析了辐射图像背景噪声的特征,在合理假设其为一阶Gaussian有色噪声的基础上改写了图像的观测方程;

    The method first analyzes the characteristics of the background noise in the radiation images , and then assumes first-order Gaussian color noise to define the equivalent observation equation .

  15. 针对长春人造卫星观测站KHz测距系统论述了在白天运转条件下,典型的背景噪声量,估算白天探测概率。

    Typical background noise and successful detection rate in daytime is discussed base on KHz SLR system in Changchun Satellite Observatory .

  16. 脑电信号(Electroencephalograph,EEG)处理的目的是为了从复杂的背景噪声中提取出隐含或微弱的脑电特征。

    The purpose of EEG signal processing is to extract the hidden or weak patterns from EEG signals in sophisticated noise background .

  17. 由于每个EEG扫程是由相同刺激序列所诱发,故在背景噪声的掩盖下含有相同的AEP成分。

    Since the EEG sweeps are induced by the same stimulus sequence , They contain the same AEP components contaminated by strong background noise .

  18. 舒适噪声产生技术(CNG)就是发送端在静音期间发送一些分组信息帧,从而生成使用户感觉舒服一些的背景噪声。

    Comfort Noise Generator ( CNG ) is that sender sends a few frames in silent time and receiver generates comfortable background noise using those frames .

  19. 临床上常用的平均脑干听觉诱发电位(brainstemauditoryevokedpotential,BAEP)无法描述脑干功能的动态特性,从背景噪声中单次或少次动态提取的BAEP才是反映脑干功能的理想信号。

    The common-used averaged brainstem auditory evoked potential ( BAEP ) can not describe the dynamic characteristics of brainstem , while single-trial BAEP extracted from background noises would be the ideal signal .

  20. 为了消除诸如微型轴承噪声测试分析中存在的强大背景噪声问题,本文引入了一种新的信号处理方法&自适应消噪技术ANC(AdaptiveNoiseCancelling)。

    In order to cancell the influence of the enormous background noise , this paper introduces a new kind of signal processing method & the Adaptive Noise Cancelling technique ( abbreviated as ANC ) .

  21. 结果表明,基于ICA的SCS去噪方法能够从水轮机组运行的背景噪声中提取出叶片裂纹信号和断铅信号。

    It shows that the SCS method can extract the crack signal of the blade and the pressing lead signal buried in the operating noise of the turbine unit .

  22. 船研所空泡水筒背景噪声和ITTC标准螺旋浆空化噪声测量

    The Measurements of Background Noise in SSSRI Cavitation and Cavitation Noise of ITTC Standard Propeller Model

  23. 传统的做法是在假设背景噪声为平稳随机过程的前提下,通过多次单实验信号的叠加平均(Superpositionandaverage,SA)来获得。

    Conventional methods , which are based on the assumption that the background noise is stationary random processes , often obtain the ERPs signal by adopting superposition and average ( SA ) of single experiment signal through many times .

  24. 由于小波模极大值去噪方法在强背景噪声的情况下提取碰摩信号的能力变弱甚至失效,在本文中提出应用独立分量分析(ICA)方法对碰摩信号进行特征提取。

    As Wavelet modules maximum de-noising methods weaken or fail in the intensive noises environment , a method based on independent component analysis feature extraction was applied for rub-impact signals in this paper .

  25. 对山西数字遥测台网“十五”勘选的19个子台台址背景噪声进行分析和计算,得出了各台址背景噪声地动速度均方根值(RMS值)、有效测量动态范围、噪声信号功率谱。

    RMS ( root-mean-square ) values of ground motion noises , effective dynamic ranges and noise power spectrums of 19 stations selected by " the tenth-five-year project " are calculated and analyzed .

  26. 虽然CDMA体制和MC-CDMA体制对PCM/FM信号来说可以看成背景噪声,但是这种干扰仍然会造成PCM/FM信号检测性能的下降。

    Although the signal of CDMA or MC-CDMA system can be seen as background noise by PCM / FM system , the interference can decrease the performance of the PCM / FM detection .

  27. 其次,本实验系统地研究了饱和条件下染料激光器的光稳定性对DFWM信号和背景噪声的问题。

    Also , photostability of dye laser on the DFWM signal and ambient noise is detailed investigated in saturation regime .

  28. 相关背景噪声下ETDE算法研究

    An Explicit Time Delay Estimation ( ETDE ) Algorithm for Correlated Noise Environment

  29. 试验结果证明,刀具破损前会出现预兆性的AE信号,并可把该信号从背景噪声中检测出来。

    Tests show that AE signals may be detected from background noises in cutting process , a few hundreds millisecond before tool break down abrupt . The predictability of cutting tool breakage is proved .

  30. 经仿真分析和实际电路调试,证明该电路可有效抑制背景噪声和干扰,可用于BCI中实现对微弱低频脑电信号的提取。

    Through simulation and actual circuit debugging , the results indicate that this circuit can filtrate the noise and interference effectively , and detect the EEG signals well for BCI .