噪声估计,noise estimation
1)noise estimation噪声估计
1.Speech enhancement withnoise estimation in bark domain;一种基于巴克域噪声估计的语音增强算法
2.During thenoise 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 onnoise 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。
英文短句/例句
1.The Algorithm on Processor Noise Estimate with Colored Measurement Noise有色测量噪声下的输入白噪声估计算法
2.Study of Measurement Noise and State Fusion Estimation Algorithms for Multi-Channel System with Multiplicative Noises;多通道带乘性噪声系统的观测噪声估计及状态融合估计算法研究
3.A Bayesian-NSCT Image Denoising Arithmetic Based on Layered Noise Estimation基于分层噪声估计的Bayesian-NSCT图像去噪算法
4.Image Noise Estimation Based on Block Neighborhood Relevance基于块内邻域相关度的图像噪声估计
5.Noise estimation for Cramer-Rao Bound analysis of multi-scale matching多分辨率匹配CRB分析中噪声估计方法
6.An Active Edge Detection Method Based on Noise Estimation of Differential Image基于微分图象噪声估计的主动型边界检测方法
7.Optimal Estimation of Measurement Noise for Singular Systems with Multiplicative Noise带乘性噪声广义系统的观测噪声最优估计算法
8.Far-end loop noise– using the estimated crosstalker profile, an estimate of the loop noise present at the far end can be made.远端环路噪声-用估计的串扰属性,就能估计远端环路的噪声。
9.Experimental Evaluation on Methods of the Hurst Parameter Estimation Using Fractional Gaussian Noise;分形高斯噪声Hurst参数估计的实验评价
10.Cross Esprit Methods Estimating The Parameters of Closesinusoids in Colored Noise;色噪声背景下正弦参量估计的互ESPRIT法
11.Simplification of finite memorial online estimation for measurement noise量测噪声有限记忆在线估计简化算法
12.MIMO-OFDM channel estimation method based on adaptive noise canceller基于自适应噪声抵消的MIMO-OFDM信道估计
13.Multi-path Channel Estimation in Strong Impulse Noise Environment强脉冲噪声环境下的多径衰信道估计
14.Estimation of the Number of Signal Source in Spatially Nonstationary Noise空间非平稳噪声下的信源数估计算法
15.H_2 white noise estimation for linear continuous-time systems with delayed measurements观测时滞连续系统的白噪声H_2估计
16.Frequency and DOA Simultaneous Estimation of LFM Signal under Impulse Noise冲击噪声背景下频率和DOA的联合估计
17.Modifying SNR-Independent Velocity Estimation Method to Make it Suitable for SNR Estimation in Shallow Water Acoustic Communication两种水声信道模型中信噪比估计算法
18.Asymptotic representation for PDF of Alpha stable distributionAlpha稳定噪声PDF的近似估计
相关短句/例句
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。
3)white noise estimation白噪声估计
1.By applyingwhite 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 andwhite 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。
4)noise estimator噪声估计器
5)noise spectrum estimation噪声谱估计
1.A fast adaptive method fornoise spectrum estimation is proposed in this paper.提出了一种快速自适应的噪声谱估计方法。
2.In this algorithm,anoise spectrum estimation approach by minima controlled recursive averaging is utilized firstly,thus no voice activity detection is needed here,secondly,the occurrence possibility of "musical noise" is reduced by making use of a recursively calculated over-subtraction factor based on sub-band signal-to-noise ratio.该算法首先利用了一种由最小值控制的递归平均的噪声谱估计算法,因而无需语音端点检测,其次利用一种通过递归计算得到的基于子带信噪比的过减因子,减小了产生"音乐噪声"的可能性。
6)blind noise estimation盲噪声估计
延伸阅读
Bayes估计量Bayes估计量Bayesian estimatorBayes估计量【Bayesi助始廿ma.件;D自狱.。眨..界..]用BayeS方法(Bayesian aPProach)由观察值对一未知参数所作的估计.统计问题使用这样的方法时,一般都假定未知参数所0 gR“是一具有给定先验分布7r=武do)的随机变量,决策空间D与集合0重合.且损失L(0,d)表示变量0与估计d的偏离.因此,函数L勿,d)通常假定为有形式L勿,d)=a(e)又(口一d),其中又是误差向量0一d的某个非负函数,若k二1,则常取又勿一d)={0一d}“(“>0).最有用且在数学上最方便的是平方损失函数L(口,d)=}‘一d1’.对这一损失函数,Bayes估计量(Ba卿决策函教(Bavesian dedsion function))占’二亡厂(x)定义为使最小总损失 !;‘p‘二·“,一,‘薯必,“一”‘·’2’〕口‘么,叮‘““,达到的函数,或与之等价,了是使最小条件损失,母‘E{[口一占(x)]2+“)达到的函数,由此推出,在平方损失函数的场合,B竹es估计量与后验均值占‘(x)=E勿{x)相等,而Bayesj双险(Bayes risk)为 。‘二,占‘)二E!D矿夕}x)]‘此处O(0}劝是后验分布的方差:o(口{x)二任{{口一E(0{x)12!,、}. 例设二=(x,,,二,戈),这里x,,,二,x。为具正态分布N勿,。’)的独立同分布变量,护己知,而未知参数0有正态分布N扭,铲).因为当x给定时口的后验分布为正态N(拜。,T:一、其中 n又。2一十“下一2灿。二一—,,。一二n口‘一奋了一_n口一汁~下且万=(x,十一+凡)/。,可知在平方损失函数{分一引’之下,Bayes估计量为占’(x)=线,而Bayes风险则为《二犷六伽铲十护).AH川畔即撰[补注]
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