1) process noise estimation
处理噪声估计
2) noise estimation
噪声估计
1.
Speech enhancement with noise estimation in bark domain;
一种基于巴克域噪声估计的语音增强算法
2.
During the noise estimation,the estimation of its spectrum is updated by tracking the speech-absent frames.
噪声估计过程中通过跟踪带噪语音帧来更新噪声估计。
3.
After capturing theneighborhoods of discontinuity in the image and acquiring their spatial features based on noise estimation,adaptive optimal.
它首先通过噪声估计捕捉图象中可能存在边界的邻域，然后获取邻域中有关边界的空间参数，由此选择最佳微分滤波算子对相应邻域进行滤波，以获取边界点。
3) Noise estimate
噪声估计
1.
The method can track eigenvalue minima on each eigenvector without any distinction between the speech activity and the speech pause,thus updating the noise estimate throughout the entire signal.
针对传统子空间方法中,采用语音活动检测(Voice activity detection,VAD)估计噪声的缺陷,提出了一种基于子空间域的最小统计噪声估计算法。
2.
When the statistics of noise are changing or signal-noise-ratio(SNR)is low,the noise estimated value by voice activity detection is not exact.
结合语音存在概率对带噪语音协方差矩阵在每个特征向量上的特征值递归平滑得到噪声估计,可以在每一帧内更新噪声特征值。
4) noise processing
噪声处理
1.
Like-impulse electromagnetic noise processing based wavelet transform;
基于小波变换的脉冲类电磁噪声处理
5) white noise estimation
白噪声估计
1.
By applying white noise estimation theory in Krein space,a sufficient and necessary condition on the existence of an H∞ fault estimator was derived,and a solution was obtained in terms of matrix Riccati equation.
首先将H∞故障估计问题转化为二次型问题,引入相应的Krein空间系统,然后应用Krein空间白噪声估计理论,得到了问题可解的充要条件,并通过矩阵Riccati方程设计H∞故障估计器。
2.
Based on Kalman filtering and white noise estimation theory, reduced-order Wiener state estimator for a canonical form of descriptor discrete- time stochastic linear systems is proposed by applying modern time series analysis approach.
应用现代时间序列分析方法,基于Kalman滤波和白噪声估计理论,对于广义离散随机线性系统的一种典范型,提出降阶Wiener状态估值器,可统一处理滤波、平滑和预报问题,并且能减少计算负担,便于实时应用。
6) noise estimator
噪声估计器
补充资料：处理
1.处置;办理。 2.指定刑;处罚。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条