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统计信号处理，参数估计的方法，包括：最大似然，最小二乘方法，Monte_Carlo-Statistical signal processing, parameter estimation methods, including: maximum likelihood, least squares method, Monte_Carlo
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The method of maximum likelihood corresponds to many well-known estimation methods in statistics. For example, one may be interested in the heights of adult female giraffes, but be unable to measure the height of every single giraffe in a population
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极大似然参数估计，对于已知输入输出数据的情况下，对系统的参数进行估计。-Maximum Likelihood Parameter estimation, for the case of known input and output data to estimate the parameters of the system.
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We have investigated the performance of the sphere decoding algorithm.
As it has shown in the computer simulations, the decoder based on the
sphere decoding algorithm has almost the same performance of a maximum
likelihood decoder with much low
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增广最小二乘的递推算法对应的噪声模型为滑动平均噪声，扩充了参数向量和数据向量H（k）的维数，把噪声模型的辨识同时考虑进去。最小二乘法只能获得过程模型的参数估计，而增广最小二乘法同时又能获得噪声模型的参数估计，若噪声模型为平均滑动模型，，则只能用RELS算法才能获得无偏估计。当数据长度较大时，辨识精度低于极大似然法。-Augmented least squares of recursion algorithm corresponding noise model for moving average
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在统计计算中，最大期望（EM）算法是在概率（probabilistic）模型中寻找参数最大似然估计或者最大后验估计的算法，其中概率模型依赖于无法观测的隐藏变量（Latent Variable）。最大期望经常用在机器学习和计算机视觉的数据聚类（Data Clustering）领域。
-In the statistical calculations, the maximum expected (EM) algorithm parameter maximum likelihood estimate
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条件极大似然算法（Conditional Maximum Likelihood）的实现：使用十字型天线阵列对信号源的来波方向（仅限于方位角）进行估计（DOA估计），可以选择信号的传播信道为高斯，瑞利或是莱斯信道。-A program achieves DOA Estimation using Conditional Maximum Likelihood Method,and its array it s a across one.
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经典文章“Maximum marginal likelihood estimation for nonnegative dictionary learning in the Gamma-Poisson Model”源代码-Classic article " Maximum marginal likelihood estimation for nonnegative dictionary learning in the Gamma-Poisson Model" source co
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em算法计算混合高斯模型的参数估计，极大似然，EM算法用于K均值问题的参数估计。MATLAB实现有代码-em algorithm Gaussian mixture model parameter estimation, maximum likelihood parameter estimation for K-means problem EM algorithm. MATLAB implementation code
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极大似然估计是一种很有用的办法，可以用MATLAB来实现，事实上，极大似然与最小二乘估计结果是相同的-MLE is a very useful way, you can use MATLAB to achieve, in fact, maximum likelihood and least squares estimation results are the same
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基于压缩感知，利用最大似然函数进行DOA估计的两种方法-Based on compressed sensing, using the maximum likelihood function of the two methods for DOA Estimation
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2类分类高斯模型
每个类是由一个单一的多元高斯分布的3-D建模
显示如何估计高斯均值向量和协方差矩阵的最大似然（ML）估计的基础上为每个类。
meanA和meanB代表每个类的均值，varA和varB的的代表每个类的协方差矩阵.-2-class classifier with Gaussian Models
Each class is modelled by a single 3-D multivariate Gaussian distribution
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展示了线性、DFE、MLSE均衡器的信噪比性能，并通过蒙特卡罗模拟信道估计结果确定。-This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer i
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lda的matlab实现，lda is a Latent Dirichlet Allocation (Blei et al., 2001) package written both in MATLAB and C (command line interface).
This package provides only a standard variational Bayes estimation that was first proposed, but has a simple textua
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Frame collision set size: code describe different tag estimation functions: H.Vogt maximum likelihood-Frame collision set size: code describe different tag estimation functions: H.Vogt maximum likelihood...
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极大似然函数参数估计，mle参数估计实现方法-Maximum Likelihood function parameter estimation, mle parameter estimation method to achieve
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We consider the source localization problem using
time-difference-of-arrival (TDOA) measurements in sensor networks.
The maximum likelihood (ML) estimation of the source
location can be cast as a nonlinear/nonconvex optimization
problem,
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Approximate Maximum Likelihood 算法处理DOA估计的Matlab算法代码-matlab function for DOA estimation using Approximate Maximum Likelihood method
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窄带信号基于最小估计长度和最大似然估计的信号数目及波达方向的联合估计-Narrowband signals based on the number of signal joint estimate minimum and maximum likelihood estimate of the length and direction of arrival estimation
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基于CP的最大似然估计仿真图，两幅图，分别是符号定时偏差，以及频偏，从图中可以看出在符号定时估计最大处，相应的频偏估计值也是最接近的-CP-based maximum likelihood estimate simulation map, two maps, are a symbol timing offset, and frequency offset, it can be seen the figure in the symbol timing estimation is maximum,
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