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: |
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Author:青青 |
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Description: 功率谱估计的应用范围很广，在各学科和应用领域中受到了极大的重视。在《现代信号处理》课程中讲述了经典谱估计和现代谱估计这两大类谱估计方法；经典谱估计是基于傅立叶变换的，虽然具有运算效率高的优点，但是频谱分辨率低同时旁瓣泄漏严重，对长序列有着良好的估计。为了克服经典谱估计的缺点，人们开展了对现代谱估计方法的研究。现代谱估计是以随机过程的参数模型为基础的，有最大似然估计法、最大熵法、AR模型法、预测滤波器法。现代谱估计对短序列的估计精度高，同经典谱估计互为补充。在认真学习了现 代谱估计方法后，我选择了现代谱估计中的AR模型法的仿真作为题目。下面给出AR模型的相关理论和仿真实现。-Power Spectral Estimation of very extensive, in all disciplines and fields of application of a great deal of attention. The "modern signal processing" on the curriculum of classical and modern spectral estimation spectrum is estimated that the two types of spectrum estimation method; Classical spectrum estimation is based on Fourier transform, although high computing efficiency advantages, but also low-resolution spectrum Sidelobe serious leakage of long sequences have good estimates. In order to overcome the classic shortcomings of the spectrum estimation, there have been a pair of modern spectral estimation methods. Modern spectral estimation is the random process model parameters based on the maximum likelihood estimation, maximum entropy method, AR model, forecast filter. Spe Platform: |
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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: 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 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: |
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Author:Lee |
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Description: 附件中的m代码包括了一系列的拟合函数，这些函数通常的输入是概率分布的样本。还有最大似然估计仿真器、最小平方仿真器、混合高斯分布估计的EM算法、-M in the annex to the code, including a series of fitting function, which function normally is the probability distribution of input samples. There are maximum likelihood estimation simulator, emulator least squares, mixed-Gaussian distribution is estimated that the EM algorithm, Platform: |
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Author:liyuedsg |
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Description: 本算法包括最大似然估计，最小二乘估计，基于EM算法的多种混合高斯分布估计，EM算法测试实例，绘制每种分布的plot函数。非常有参考价值！-This algorithm, including maximum likelihood estimation, least squares estimation, based on the EM algorithm estimate a mixture Gaussian distribution, EM algorithm for the test examples, each mapping the distribution of the plot function. Very useful! Platform: |
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Author:liyuedsg |
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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: |
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Author:黄飞鸿 |
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Description: 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 is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks. Platform: |
Size: 102400 |
Author:Lee |
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Description: OFDM系统同步中的定时估计算法，主要使用了极大似然估计法。此程序实现极大似然估计法定时的程序。-OFDM system, synchronization of timing estimation algorithm, the main use of maximum likelihood estimation method. Realize this procedure maximum likelihood estimation when the statutory procedures. Platform: |
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Author:张彩 |
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Description: ：极值分布在计量经济学、金融工程、计算生物学、工程测量中都有用途，一般常用最小二乘法估计
其参数，但最小二乘法的误差较高．极大似然估计具有比最4 -乘法更好的性质，但由于它的计算往往比较麻
烦．通过极大似然法估计了极值分布的参数，同时给出了求参数的数值解的算法，并通过Matlab程序实现了
这一算法．
-: Extreme value distribution in econometrics, financial engineering, computational biology, engineering measurement purposes are generally used to estimate the parameters of least squares, but a higher least squares error. Maximum likelihood estimation than the 4'-multiplication better nature, but because it is often too much trouble to the calculation. Through the maximum likelihood method estimates the parameters of the extreme value distribution, while the parameters are given for the numerical solution of the algorithm, Matlab program by the algorithm. Platform: |
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Author:pine051025 |
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Description: 当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。- This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio Platform: |
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Author:sun |
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Description: 1）最大似然方法联合实现符号定时同步和载波同步仿真
2）泊松分布
3）贝叶斯估计
4）RANSAC方法-1) The maximum likelihood method of the joint realization of Symbol Timing and Carrier Synchronization in simulation 2) Poisson distribution 3) Bayesian estimation 4) RANSAC method Platform: |
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Author:平凡 |
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Description: 强壮的人脸识别系统，发表于cvpr2011年，程序是应用matlab实现-Recently the sparse representation (or coding) based classifi cation (SRC) has been successfully used in face recognition. In SRC, the testing image is represented as
a sparse linear combination of the training samples, and
the representation fi delity is measured by the � 2-norm or
� 1-norm of coding residual. Such a sparse coding model
actually assumes that the coding residual follows Gaus-
sian or Laplacian distribution, which may not be accurate
enough to describe the coding errors in practice. In this
paper, we propose a new scheme, namely the robust sparse
coding (RSC), by modeling the sparse coding as a sparsity-
constrained robust regression problem. The RSC seeks for
the MLE (maximum likelihood estimation) solution of the
sparse coding problem, and it is much more robust to out-
liers (e.g., occlusions, corruptions, etc.) than SRC. An
effi cient iteratively reweighted sparse coding algorithm is
proposed to solve the RSC model. Extensive Platform: |
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Author:刘大明 |
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Description: matlab中最大似然估计的程序说明，里面包含程序，拷到matlab中可直接使用-matlab maximum likelihood estimation program description, which contains the program, copying matlab can be used directly in Platform: |
Size: 3072 |
Author:李翠琳 |
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Description: GSM系统信道估计和均衡方法MATLAB程序，效果好，这是基于最大似然估计的均衡器，整个GSM系统的程序，有益于大家的学习资料-GSM system channel estimation and equalization in MATLAB program, good effect, this is the equalizer based on maximum likelihood estimation, the whole GSM system procedures, useful in our study. Platform: |
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Author:黄佳吉 |
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Description: 随机数发生器
此功能会产生连续的值（功法的文章中讨论的五个分布随机分布，指数，对数正态分布，拉伸指数，截止功法）。使用信息包含在文件类型的帮助randht在MATLAB提示符更多信息。
幂律分布拟合
这项功能同时实现的离散和连续的最大似然估计拟合幂律分布的数据，以及善良的合适的方法来估计缩放区域较低的截止。使用信息包含在文件类型的帮助plfit在MATLAB提示符更多信息。-This function is a random number generator will produce discrete values (power law discussed in five articles distributed random distribution, exponential, lognormal, stretching index cutoff power law). The use of information contained in the file type of help randht in MATLAB prompt for more information. Power-law distribution fitting This function implements both discrete and continuous maximum likelihood estimation fitting power-law distribution of data, and kind suitable method to estimate the scaling region lower cutoff. The use of information contained in the file type of help plfit in MATLAB prompt for more information. Platform: |
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Author:ligan |
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Description: 用MATLAB编写代码,在经济和金融中法对连续时间过程实现了封闭的最大似然估计方法-The code, written in MATLAB, implements the closed-form maximum-likelihood estimation method for continuous-time processes in economics and finance. First, the code maximizes the log-likelihood function and displays the MLE estimates, the standard error estimates (constructed from the inverse of Hessian) and the misspecification-robust standard error (i.e., the sandwich estimate). Second, it reports whether the maximization procedure converges under the default tolerance. Finally, it plots the marginal log-likelihood for each parameter in a neighborhood of the estimates. The blue curve is the likelihood function, while each red star corresponds to the estimate for the corresponding parameter. For more information about the models, please read the user s guide (link "more"). Platform: |
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Author:雪之恋 |
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Description: 改进DV-Hop定位算法
首先设置初始量，布置了一个范围为100×100m2的区域，其上随机分布100个传感器节点，其中有10个信标节点，节点的通信半径为30m。
第二步在正方形区域内产生均匀分布的随机拓扑，随机产生节点坐标并将其中十个选定为信标节点，其余九十个设为未知节点，然后画出节点分布图。
第三步通过最短路径法计算未知节点与每个信标节点的最小跳数。
第四步根据前面记录的其他信标节点的位置信息和相距跳数估算平均每跳的实际距离，用跳数估计距离的方法得出未知节点到信标节点的距离。
第五步用极大似然估计法求未知节点坐标
(Improved DV-Hop localization algorithm first set the initial amount, layout 100100m2 the area of a range of 100 sensor nodes randomly distributed on the 10 beacon node, the node communication radius of 30m. The second step in the square area to generate uniformly distributed random topology, random coordinates of the nodes and ten of the selected beacon node, the remaining 90 is set to unknown node, and then draw the node distribution diagram. The third step is to calculate the minimum number of hops of the unknown node and each beacon node through the shortest path method. The fourth step according to the location information of the other beacon nodes in the previous record and away from hops to estimate the average hop distance and hop count to estimate the distance to come to the distance of the unknown node to beacon nodes. The fifth step maximum likelihood estimation method and the unknown coordinates of the nodes) Platform: |
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Author:robinkk4 |
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Search - maximum likelihood estimation in matlab