共查询到18条相似文献,搜索用时 114 毫秒
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为了解决观观测噪声和信道噪声概率分布不完全已知时的多传感器分布式量化估计融合问题,提出了一种期望极大化算法(EM算法)的分布式量化估计融合方法。该方法将未知的噪声参数以及局部量化器量化概率建模为EM算法中二元高斯混合模型参数,利用极大似然估计方法的估计不变性得到目标参数的估计融合结果。仿真实验结果表明:该方法在局部传感器观测样本数目大于6000和信噪比大于6 dB时与已有理想信道条件下的估计方法性能相当。本文方法对水下分布式协同探测问题提供了一种简化的估计融合实现途径。 相似文献
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《光学学报》2017,(4)
最大似然估计是提取目标微动特征参数的最佳估计方法,但直接用网格法求解计算量巨大,且激光探测微多普勒回波信号对应的代价函数具有高度非线性,存在多个局部最大值。为此,提出均值似然估计与蒙特卡罗结合的估计方法,给出了最大似然参数估计的闭合表达式,再通过设计压缩似然函数获得全局最大值,通过蒙特卡罗法抽样并计算循环均值估计出参数。该方法避免了传统方法中对高精度初始值和复杂迭代算法的依赖,能够实现参数的联合估计。对于多分量微多普勒信号,该方法可在参数估计的同时实现各微动分量分离,且不增加算法的复杂性。对仿真和实验数据进行估计,结果表明,该方法在达到近似于最大似然估计性能的同时可有效降低计算复杂度并确保了全局收敛,实现信号的分离和参数估计。 相似文献
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针对小尺寸传声器阵列多声源方位估计易受混响噪声影响的问题,提出了一种适用于差分传声器阵列的期望最大化多声源方位估计方法。首先,该方法利用期望最大化算法求解出各个时频点瞬时方位估计所应满足的高斯混合模型参数;然后,通过时频点分离技术估计出各声源的方位值。针对现有的硬、软时频点分离技术应用于差分传声器阵列所存在的缺陷,还提出了一种改进的时频点分离方法,该方法融合了软、硬分离方法所具有的优点,有效降低了时频点分离结果对混响噪声的敏感性。仿真和实测实验结果表明:相较于现有的差分传声器阵列多声源估计方法,所提方法在混响噪声环境下具有更高的估计精度和稳健性能。 相似文献
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基于最大似然多项式回归的鲁棒语音识别 总被引:2,自引:0,他引:2
本文针对最大似然线性回归算法线性假设的缺点,将多项式回归方法用于模型自适应,构建了基于最大似然多项式回归的非线性模型自适应算法。该算法在对数谱域用多项式回归方法,逼近每个Mel子带上识别环境模型均值与训练环境模型均值之间的非线性关系。多项式系数通过EM算法和最大似然准则从识别环境下的少量自适应数据中估计。实验结果表明,二阶多项式就可以较好地逼近模型均值的非线性环境变换关系。在噪声补偿和说话人自适应实验中,最大似然多项式回归算法的误识率都明显低于最大似然线性回归算法。本文算法较好地克服了线性模型自适应算法线性假设的缺陷,可同时减小噪声,和说话人的改变或其它因素对语音识别系统的影响,尤其适合说话人和噪声的联合自适应。 相似文献
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针对稀疏信号的超分辨方位估计问题,提出一种可变因子的稀疏近似最小方差算法(α-Sparse Asymptotic Minimum Variance,简记为SAMV-α)。该算法利用一个折衷参数进行最大似然估计值和稀疏性能的折衷处理,在迭代过程中改变稀疏近似最小方差算法(Sparse Asymptotic Minimum Variance,SAMV)的指数因子,得到强稀疏性能和超低旁瓣的方位谱图,实现邻近目标的超分辨方位估计和相干处理性能,且无需预估角度和信源数目等先验信息,并且折衷参数的取值为0到1之间,取值区间明确,避免了稀疏信号处理算法中正则因子选取困难的弊端。计算机仿真表明SAMV-α算法方位估计性能明显优于波束扫描类算法和子空间类算法,与同类型稀疏信号处理类算法相比仍具有较高的方位估计精度,同时对于邻近声源分辨能力,SAMV-α算法较SAMV-1算法性能提高约3dB。海上试验数据处理给出了分辨率更高的方位时间历程(Bering-Time Recording,BTR)图,有效验证了SAMV-α算法的性能。 相似文献
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利用激光对目标微弱振动进行探测有利于获得明显的微多普勒效应,这为精确估计目标微动特征参数,实现对目标的分类和精细识别提供了可能.但对于多散射点或多目标激光探测,信号为单通道多分量微动混合的形式,而且补偿目标主体运动后,数值上相近的微动参数还会导致信号在时频域存在严重的交叠.为从这类混合信号中精确估计各分量的微动参数,本文提出了基于最大似然框架的参数分离估计方法.利用精细化扫描的奇异值比谱法从混合信号中获得目标微动频率,并得到各分量的幅值比信息.推导了微动参数最大似然估计的解析表达形式,根据激光微多普勒信号的特点从频谱能量分布的角度重新设计了似然函数,解决了传统似然函数在激光微动信号中出现的高度非线性问题,降低了初始化的要求,提高了抗噪性能,并采用马尔可夫-蒙特卡罗方法具体实现了参数的估计.在微动参数得到估计的基础上给出了信号的幅值和初相的估计方法.用本文方法对仿真和实验数据进行处理,得到了接近克拉美罗下界的估计结果,验证了方法的有效性.与传统非参数化估计方法的对比结果体现了所提方法对混合微动参数精确估计上的优势. 相似文献
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In this paper, a general framework is developed for determining the underlying parameters of general signal models through the application of maximum likelihood estimation theory for functions whose variables separate. This method extends previous work in sinusoidal and exponential estimation to include models with other functional bases, such as exponential functions with nonconstant amplitudes and Bessel functions. Nonuniform spatial sampling is also possible with this technique. The maximum likelihood method is applied to the identification of wave components along one-dimensional structural elements. Results are given which demonstrate the viability and accuracy of the technique estimating exponential and Bessel function model parameters from noisy simulation data. 相似文献
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The method of maximum likelihood has been implemented for the estimation of multiple exponential components of T2 decay curves in spin echo NMR measurements on biologic tissues. Each Each component contributes an exponential term described by two parameters (initial amplitude and T2) to the T2 decay curve. The maximum likelihood method estimates the parameters and their standard errors for all terms simultaneously, avoiding the subjectivity inherent in methods such as graphical peeling. In the model used, it was assumed that water protons are compartmentalized and that the measured spin echo signals from the protons undergoing relaxation obey the Poisson distribution. A system of non-linear equations was derived and solved iteratively for the values of the exponential parameters which maximize the likelihood of obtaining the observed data under these assumptions. The approach was implemented for bi- and tri-exponential models on a MicroVAX II computer (Digital Equipment Corporation, Maynard, MA). Simulations of bi- and tri-exponential data, with and without system noise, were analyzed to assess the accuracy and reproducibility of the method. A subset of the simulations was repeated with non-linear least squares techniques and was compared to the results obtained with maximum likelihood. Rabbit muscle and gerbil brain samples were measured and analyzed with the maximum likelihood method. The simulations showed that within specific limits on relative sizes and relaxation rates of components, these parameters can be estimated with errors less than 5%. The comparison to non-linear least squares analysis showed that the maximum likelihood method is generally superior in estimating the parameters in difficult cases. The results from tissue measurements demonstrate that the method is effective even in cases where graphical peeling would clearly not yield reliable results. 相似文献
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Hee-Suk Pang 《Applied Acoustics》2004,65(1):101-107
Characteristics of frequency vibrato are usually explained by the frequency center, rate, and extent. For analysis of vibrato tones, we apply the maximum likelihood estimation to the enhanced fundamental frequency track obtained from a short-time Fourier transform. We have also suggested the values of the parameters in the estimation and the averaging process to reduce the estimation error. Experiments show that the proposed method can be used for accurate and reliable analysis of vibrato tones. 相似文献
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Blume-Kohout R 《Physical review letters》2010,105(20):200504
This Letter proposes and analyzes a new method for quantum state estimation, called hedged maximum likelihood (HMLE). HMLE is a quantum version of Lidstone's law, also known as the "add β" rule. A straightforward modification of maximum likelihood estimation (MLE), it can be used as a plug-in replacement for MLE. The HMLE estimate is a strictly positive density matrix, slightly less likely than the ML estimate, but with much better behavior for predictive tasks. Single-qubit numerics indicate that HMLE beats MLE, according to several metrics, for nearly all "true" states. For nearly pure states, MLE does slightly better, but neither method is optimal. 相似文献
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Cramer-Rao lower bounds (CRLBs) on the estimation of the pointing parameters of a laser system using the return signal are obtained. A maximum likelihood estimator is found to obtain an estimation performance close to the CRLB in most scenarios considered. 相似文献
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In this paper, two novel joint semi-blind channel estimation and data detection techniques are proposed and investigated for Alamouti coded single-carrier (SC) multiple-input multiple-output (MIMO) communication system using Rayleigh flat fading channel model. In the first novel semi-blind technique, blind channel estimation can be performed by using singular value decomposition (SVD) of received output autocorrelation matrix and training based channel estimation for orthogonal training symbols can be performed by using orthogonal pilot maximum likelihood (OPML) algorithm. Further using, that semi-blind channel estimate and received output, data detection is performed by using Maximum likelihood (ML) detection. Finally we derived new training symbols from error covariance matrix of estimated data and known orthogonal training symbols, which further applied to OPML algorithm for final channel estimate. In the second novel semi-blind technique, blind channel estimation can be performed by using matrix triangularization based on householder QR decomposition (H-QRD) of received output autocorrelation matrix instead of SVD decomposition. Other steps are same as the first novel technique to calculate data detection and final channel estimation. Simulation results are presented under 2-PSK, 4-PSK, 8-PSK and 16-QAM data modulation schemes using 2 transmitters and different combinations of receiver antennas to investigate the performances of novel techniques compare to conventional whitening rotation (WR) and rotation optimization maximum likelihood (ROML) based semi-blind channel estimation techniques. Result demonstrates that novel techniques outperform others by achieving near optimal performance. 相似文献
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H.F. Coronel-Brizio 《Physica A》2010,389(17):3508-155
Maximum likelihood estimation and a test of fit based on the Anderson-Darling statistic are presented for the case of the power-law distribution when the parameters are estimated from a left-censored sample. Expressions for the maximum likelihood estimators and tables of asymptotic percentage points for the A2 statistic are given. The technique is illustrated for data from the Dow Jones Industrial Average index, an example of high theoretical and practical importance in Econophysics, Finance, Physics, Biology and, in general, in other related sciences such as Complexity Sciences. 相似文献