Description: Classify using the maximum-likelyhood algorithm-classifies using the maximum- likelihood al gorithm Platform: |
Size: 1024 |
Author:柳风 |
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Description: LDPC码译码相关文献
Bounds on the maximum likelihood decoding error probability of low density parity check codes-LDPC Decoding literature Bounds on the maximum likelihood decoding error probability of low density parity check codes Platform: |
Size: 99328 |
Author:xzm |
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Description: 这是一个基于matlab语言的用极大似然估计法做的多项分布程序-This is a matlab-based language with maximum likelihood estimation method to do a number of distribution procedures Platform: |
Size: 1024 |
Author:杨芮 |
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Description: 程序的主要功能是做了一定范围的信噪比下，对每个信噪比：随机信号QPSK调制；
根据Alamouti方案的矩阵进行编码；发送信号经过瑞利信道和加入高斯白噪声；
接收信号采用最大比合并的方法；最后对合并信号进行最大似然判决并求误符号率。
结果表明10^-3对应大约12->13dB-Procedure main function is to do a certain range of SNR for each signal to noise ratio: random signal QPSK modulation program in accordance with Alamouti coding matrix send signals through Rayleigh channel and adding Gaussian white noise received signal using maximal-ratio combining method Finally the combined signal and the maximum likelihood decision for symbol error rate. The results showed that about 10 ^-3 corresponds to 12-> 13dB Platform: |
Size: 1024 |
Author: |
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Description: 自己编的matlab程序。用于模式识别中特征的提取。是特征提取中的Sequential Forward Selection方法，简称sfs.它可以结合Maximum-Likelihood-Classifier分类器进行使用。-The matlab own procedures. For Pattern Recognition Feature Extraction. Feature Extraction is the Sequential Forward Selection method, referred to as sfs. It can be combined with Maximum-Likelihood-Classifier classifier used. Platform: |
Size: 1024 |
Author:limingxian |
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Description: 用递推的极大似然法对系统辨识，对具有随机噪声的二阶系统的模型辨识-Using the recursive maximum likelihood method of system identification, random noise with the second-order system model identification Platform: |
Size: 7168 |
Author:david |
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Description: ％ EM algorithm for k multidimensional Gaussian mixture estimation
％
％ Inputs:
％ X(n,d) - input data, n=number of observations, d=dimension of variable
％ k - maximum number of Gaussian components allowed
％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
％ maxiter - maximum number of iteration allowed ([] for none)
％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none)
％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none)
％
％ Ouputs:
％ W(1,k) - estimated weights of GM
％ M(d,k) - estimated mean vectors of GM
％ V(d,d,k) - estimated covariance matrices of GM
％ L - log likelihood of estimates
％- EM algorithm for k multidimensional Gaussian mixture estimation Inputs: X (n, d)- input data, n = number of observations, d = dimension of variable k- maximum number of Gaussian components allowed ltol- percentage of the log likelihood difference between 2 iterations ([] for none) maxiter- maximum number of iteration allowed ([] for none) pflag- 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) Init- structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) Ouputs: W (1, k)- estimated weights of GM M (d, k)- estimated mean vectors of GM V (d, d, k)- estimated covariance matrices of GM L- log likelihood of estimates Platform: |
Size: 3072 |
Author:Shaoqing Yu |
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Description: 对平稳时间序列中的参数估计方法（包括矩估计，极大似然估计）和预测方法（包括差分方程预测方法，逆函数预测方法，格林函数预测方法）应用matlab进行编程，大家可以方便使用-For stationary time series in the parameter estimation methods (including moment estimation, maximum likelihood estimation) and forecasting methods (including the difference equation forecasting methods, inverse function of forecasting methods, Green s function prediction method) Application matlab program, we can easily use Platform: |
Size: 9216 |
Author:黄飞鸿 |
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Description: 最大似然估计算法，应用于多参数模型，例如gps领域-Maximum likelihood estimation algorithm applied to multi-parameter model, for example, the field gps Platform: |
Size: 5706752 |
Author:metallica |
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Description: 极化SAR图像多纹理最大似然处理滤波算法，可以生成处理后的四个通道图像数据。-Multi-polarization SAR image texture filtering deal with maximum-likelihood algorithm, can be generated after the deal with the four-channel image data. Platform: |
Size: 1024 |
Author:郎志超 |
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Description: Garch模型的最大似然估计方法，基于MATLAB程序。-Garch model of maximum likelihood estimation method, based on the MATLAB program. Platform: |
Size: 1024 |
Author:阿杜 |
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Description: Phase noise resulting in Common Phase Error
(CPE) and Inter-Carrier Interference (ICI) is a critical challenge
to the implementation of OFDM systems. Modeling phase noise
as a stationary Gaussian random process with the specified
power spectrum density, different from conventional approaches
which mostly relay on pilots to provide CPE estimation, we
explore the statistical characteristics of the sufficient statistics
then propose a pilot-aided decision-directed approach according
to maximum-likelihood criterion. Numerical results demonstrate
that the proposed algorithm enjoys 2dB gain at moderate SNR
and is quite robust against possible model mismatch Platform: |
Size: 6144 |
Author:xiaobo |
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Description: 关于模型辨识的MATLAB仿真源码。有使用最小二乘的建模，有极大似然估计建模的方法。每个重点例句都有详细的解释。-On the MATLAB simulation model of source identification. Modeling the use of least squares, and maximum likelihood estimation method of modeling. Each key has a detailed explanation of examples. Platform: |
Size: 9216 |
Author:Ronnie.Lu |
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Description: MATLAB Toolbox for econometric modeling of time series. E4 makes up for the lack of PC software for estimating econometric models by exact maximum likelihood. Platform: |
Size: 1586176 |
Author:Christian Hagglof |
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Description: How to use the HMM toolbox
HMMs with discrete outputs
Maximum likelihood parameter estimation using EM (Baum Welch)
Platform: |
Size: 16384 |
Author:q |
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Description: Probabilistic Principal Component Analysis
– Latent variable models
– Probabilistic PCA
• Formulation of PCA model
• Maximum likelihood estimation
– Closed form solution
– EM algorithm
» EM Algorithms for regular PCA
» Sensible PCA (E-M algorithm for probabilistic PCA)
– Mixtures of Probabilistic Principal Component
Analysers-Probabilistic Principal Component Analysis
– Latent variable models
– Probabilistic PCA
• Formulation of PCA model
• Maximum likelihood estimation
– Closed form solution
– EM algorithm
» EM Algorithms for regular PCA
» Sensible PCA (E-M algorithm for probabilistic PCA)
– Mixtures of Probabilistic Principal Component
Analysers Platform: |
Size: 263168 |
Author:Tatyana |
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Description: 在统计学中，最大后验（英文为Maximum a posteriori，缩写为MAP）估计方法根据经验数据获得对难以观察的量的点估计。它与最大似然估计中的 Fisher 方法有密切关系，但是它使用了一个增大的优化目标，这种方法将被估计量的先验分布融合到其中。所以最大后验估计可以看作是规则化（regularization）的最大似然估计。
-In statistics, the maximum a posteriori (English as a Maximum a posteriori, abbreviated as MAP) estimation method according to empirical data is difficult to obtain right amount of observation point estimate. It is with the maximum likelihood estimation of the Fisher method is closely related to, but it uses a larger optimization goals, this approach would be the estimated amount of integration of prior distribution to it. Therefore, maximum a posteriori estimates can be regarded as regularization (regularization) of the maximum likelihood estimate. Platform: |
Size: 1024 |
Author:youxia |
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Description: 最小二乘，极大似然定位算法，其中包括二维和三维的最小均方误差定位算法以及连续定位算法(Least squares, maximum likelihood localization algorithm, which includes two-dimensional and three-dimensional minimum mean square error localization algorithm and continuous positioning algorithm) Platform: |
Size: 3072 |
Author:青骑士zf
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Search - maximum likelihood