Description: 提供实现了（2，1，7）卷积码的维特比译码的源程序，采用了最大似然算法，介绍了软判决维特比译码算法过程的三个步骤：初始化、度量更新和回溯译码。-for achieving a (2,1,7) Convolutional Codes Viterbi decoding of the source, using the maximum - likelihood algorithm, introduced a soft-decision Viterbi decoding algorithm of the three steps : initialization, Metric update and backtracking decoding. Platform: |
Size: 1261 |
Author:王雪松 |
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Description: ICA算法The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.-ICA algorithm:The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction. Platform: |
Size: 563200 |
Author:陈互 |
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Description: 用递推的极大似然法对系统辨识(递推的极大似然法辨识程序)希望通过站长审核-recursive use of the maximum likelihood method of system identification (recursive maximum likelihood method identification procedures) through head of audit Platform: |
Size: 1024 |
Author: |
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Description: Tdscdma系统中的载频估计程序，利用导频段，极大似然的估计算法，在MATLAB中的实现程序-Tdscdma system of carrier frequency estimation procedures, the use of derivative band, the maximum likelihood estimation algorithm, MATLAB in the realization process Platform: |
Size: 2048 |
Author:青青 |
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Description: The EM algorithm is short for Expectation-Maximization algorithm. It is based on an iterative optimization of the centers and widths of the kernels. The aim is to optimize the likelihood that the given data points are generated by a mixture of Gaussians. The numbers next to the Gaussians give the relative importance (amplitude) of each component.-The EM algorithm is short for Expectation- Maximization algorithm. It is based on an ITERA tive optimization of the centers and widths of t he kernels. The aim is to optimize the likelihoo d that the given data points are generated by a mi xture of Gaussians. The numbers next to the Gaus sians give the relative importance (amplitude ) of each component. Platform: |
Size: 15360 |
Author:陈伟 |
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Description: 用对数似然估计法求解时间序列分析中的ARIMA模型的matlab源代码-with several likelihood estimation method Time Series Analysis of the ARIMA model Matlab source code Platform: |
Size: 1024 |
Author:温泉 |
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Description: Turbo码的仿真程序，用matlab编写，是一个很新的程序-Turbo Codes simulation program used to prepare Matlab is a very new procedure Platform: |
Size: 35840 |
Author:Wei jiang |
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Description: 提供实现了（2，1，7）卷积码的维特比译码的源程序，采用了最大似然算法，介绍了软判决维特比译码算法过程的三个步骤：初始化、度量更新和回溯译码。-for achieving a (2,1,7) Convolutional Codes Viterbi decoding of the source, using the maximum- likelihood algorithm, introduced a soft-decision Viterbi decoding algorithm of the three steps : initialization, Metric update and backtracking decoding. Platform: |
Size: 1024 |
Author:王雪松 |
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Description: 基于matlab的彩色图像皮肤区域分割算法与实现，包括原理介绍和算法实验-Matlab based on skin color image region segmentation algorithm and realize, including the principle of the experimental introduction and algorithms Platform: |
Size: 646144 |
Author:无名 |
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Description: 此算法为基于最大似然方法的DOA估计 是区别于子空间类的DOA算法 但需要多维搜索 计算量较大-This algorithm is based on the maximum likelihood method of DOA estimation is different from the sub-space kind of DOA algorithm but calculating the volume of the larger multi-dimensional search Platform: |
Size: 1024 |
Author:金江 |
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Description: In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
-In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar-xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
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Size: 197632 |
Author:晨间 |
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Description: 信号在信道进行传输时，经常会出现串扰，采用基于最大似然序列估计（MLSE）的电子色散均衡器的方法，克服光纤通信中的由各种色散引起的码间干扰。
研究基于最大似然序列估计（MLSE）的均衡器，采用维特比算法实现，用matlab仿真出采用MLSE后的性能指标（眼图和误码率）的提升。
-Signal transmission channel often occur crosstalk, based on the maximum likelihood sequence estimation (MLSE) electronic dispersion equalizer of the ways to overcome optical fiber communications in a variety of dispersion caused by the inter-symbol interference. Research based on the maximum likelihood sequence estimation (MLSE) of the equalizer, the Viterbi algorithm, a simulation using matlab after using MLSE performance indicators (eye diagram and bit error rate) of the upgrade. Platform: |
Size: 9216 |
Author:Lee |
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Description: ％ EM algorithm for k multidimensional Gaussian mixture estimation
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％ 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)
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％ 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: 相干源对最大似然算法测向的影响 设置了两个相干的信号，以便研究相干源对测向的影响-Coherent Sources on the maximum likelihood algorithm for measuring the impact of the establishment of two coherent signals, in order to study the coherent source of measurement to the effects of Platform: |
Size: 1024 |
Author:txl |
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Description: 实现了（4，1，6）型卷积码的维特比译码算法，采用了极大似然算法。介绍了软判决维特比译码算法过程的三个步骤：初始化，度量更新和回溯译码。-Realize the (4,1,6)-type convolutional codes Viterbi decoding algorithm using the maximum likelihood algorithm. Introduce a soft-decision Viterbi decoding algorithm the process of three steps: initialization, update and backward decoding metric. Platform: |
Size: 3072 |
Author:raymond |
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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: 球形检测算法论文，性能接近最大似然算法，但是复杂度较低-Spherical detection algorithm paper, the performance near the maximum likelihood algorithm, but the complexity is low Platform: |
Size: 4191232 |
Author:王超 |
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Search - Likelihood algorithm