自适应噪声抵消的英文

• adaptive noise cancellation

• "自"英文翻译    self; oneself; one's own
• "适应"英文翻译    suit; adapt; get with it; fi ...
• "噪声"英文翻译    noise; stew; swishing; yawp; ...
• "抵消"英文翻译    offset; set-off; neutralize; ...
• "自适应噪声滤波" 英文翻译 :    autoadapted noise filteringg
• "自适应噪声消除" 英文翻译 :    adaptive noise cancelling
• "声抵消" 英文翻译 :    sound cancellation
• "回声抵消法" 英文翻译 :    echo canceling method ecm
• "回声抵消器" 英文翻译 :    echo canceller
• "交流声抵消" 英文翻译 :    hum balance; humbalance
• "感应噪声" 英文翻译 :    induced noise
• "哼声抵消电阻器" 英文翻译 :    hum-balancing resistor
• "数字回声抵消器" 英文翻译 :    digital echo canceller
• "噪声自适应自动驾驶仪" 英文翻译 :    noise adaptive autopilot
• "自适应" 英文翻译 :    adaptive predictor; adaptiver lambda-regelung; autosensing; rj45; self adaptation; self adapting; self-adaptation; self-adapting; self-adaptive
• "磁感应噪声级" 英文翻译 :    noise level of magnetic induction
• "电力感应噪声" 英文翻译 :    power induced noise
• "多路感应噪声" 英文翻译 :    babble
• "偏离感应噪声" 英文翻译 :    bias-induced noise
• "散粒效应噪声" 英文翻译 :    shot noise
• "闪变效应噪声" 英文翻译 :    flicker noise
• "栅路感应噪声" 英文翻译 :    grid induced noise
• "自适应，（端口自适应）" 英文翻译 :    autosensing
• "后向自适应" 英文翻译 :    backward adaptation
• "空时自适应" 英文翻译 :    stap

• An application study of adaptive noise cancelling
  自适应噪声抵消的应用研究
• Genetic algorithm approach to optimal adaptive noise cancellation for multi - sensory signals
  基于遗传算法的多传感器自适应噪声抵消器
• Nanc has two adaptive filters : a main filter ( mf ) and a subfilter ( sf ) . the signal - to - noise ratio ( snr ) of the input signals is estimated using the sf
  该自适应噪声抵消系统由主自适应滤波器( mf )与分自适应滤波器( sf )组成。
• This paper proposes a new adaptive noise canceller ( nanc ) with low signal distortion for speech enhancement after presenting an overview , in a unified perspective , for a number of the speech enhancement algorithms
  论文首先介绍了各种语音增强算法。然后，重点提出了一种低信号失真的新的自适应噪声抵消( nanc )语音增强算法。
• On the basis of analysing multilayer forward artificial neural networks which based on back propagation algorithms and basic principles of the adaptive noise cancellation system , this paper sets up an adaptive noise cancellation controller based on artificial neural network , which is proved to be more efficient in the noise cancellation and has robust performance based on simulink of matlab at the end , this paper proposes some advices of model and algorithms
  在对基于误差反向传播学习算法的多层前向人工神经网络进行分析基础上，结合传统自适应噪声抵消系统基本原理，建立了基于人工神经网络的自适应噪声抵消器，经基于matlab的simulink仿真实例证明，具有很强的噪声滤除能力和鲁棒性。最后并提出了网络及算法进一步改进的方法。
• Because the adaptive algorithm of conventional adaptive noise canceller is the least mean squares ( lms ) , and the convergence rate of lms is heavily dependent on the eigenvalue distribution of the autocorrelation matrix of the input signal , thus lms converges at unacceptably low rates when the input signal is colored noise or speech
  由于传统自适应噪声抵消系统( anc )自适应算法主要采用lms算法，而lms算法收敛速度依赖于输入信号自相关矩阵特征值的分散程度。因此，当输入信号是语音或有色噪声时， lms的收敛速度很慢。
• If the computation complexity is permitted , we can combine two methods together , which is the improvement trend of noise estimation . there are many speech enhancement techniques , such as filtering , correlation of speech , nonlinear processing , spectrum subtraction , and the adaptive wiener filter
  语音增强算法,包括滤波法语音增强、利用相关特性的语音增强、非线性处理语音增强、谱减法语音增强、利用wiener滤波法的语音增强、自适应噪声抵消法语音增强等,我们采用的是目前使用最为广泛的基于短时谱的语音增强算法。
• Computer simulation results show that the proposed algorithm reduces the signal distortion and the reverberation which are caused by misadjustment errors in the adaptive filter and the correlated component of the speech in the reference signal compared with a conventional adaptive noise canceller ( anc )
  仿真结果证明nanc算法有效克服了影响传统自适应噪声抵消系统( anc )性能的一些瓶颈，如两输入中的非相关噪声，参考输入中的信号成分与自适应滤波器失调误差而产生的信号失真、回响等情况。
• This dissertation is different from traditional speech enhancement methods which are based on noise characteristic such as adaptive noise cancellation or spectral subtraction processing . in this dissertation the speech signal conducted by bone was taken as the object to be studied and the exploitive study on the acoustical characteristic of speech signal conducted by bone was performed by the method of theory combined with experiment . then a proposition about speech reconstruction based on speech signal conducted by bone was presented , and the design of software and hardware was completed
  本文与传统的基于噪声特性的自适应噪声抵消法、频谱减法等语音增强降噪技术不同，是以骨导语言为研究对象，采用理论与实验相结合的方法对骨导信号的声学特性进行了探索性研究，进而提出了基于骨导信号的语音重构技术，并完成了相应的软硬件开发。