Description: 2X2 MIMO系统使用ML（最大似然）接受。（验证可用）-2X2 MIMO system using the ML (maximum likelihood) to accept. (Verification can be used) Platform: |
Size: 1024 |
Author:lynn |
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Description: 关于最大似然重建方法的实现，可用于tomography reconstruction-This is the code for maximum likelihood expectation maximum reconstruction method which is frequently applied in tomography reconstruction, such as CT and PET Platform: |
Size: 1024 |
Author:Xiubin Dai |
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Description: ML的方法在ofdm中的应用，是最大似然在ofdm中的仿真-ML method ofdm application is the maximum likelihood in the simulation ofdm Platform: |
Size: 1024 |
Author:frank |
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Description: ML的方法在ofdm中的应用，是最大似然在ofdm中的仿真-ML method ofdm application is the maximum likelihood in the simulation ofdm Platform: |
Size: 1024 |
Author:frank |
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Description: 该算法是经典的信噪比估计算法——最大似然估计算法，利用接收信道的先验概率密度函数，ML法能够很好的估计信号的信噪比-The algorithm is a classic signal to noise ratio estimation algorithm- maximum likelihood estimation algorithm, using the a priori receiver channel probability density function, ML method can be a very good signal to noise ratio is estimated Platform: |
Size: 1024 |
Author:贾小勇 |
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Description: 《通信信道处理》课程设计，内容为MIMO系统的性能仿真分析，内含MIMO系统的构建、Rayleigh信道、AWGN干扰、QPSK调制解调等，按照IEEE格式全英书写，请大家多多指教-Performance Analysis of Maximum Likelihood Detection in a MIMO Antenna System.pdf Platform: |
Size: 304128 |
Author:Hongyuan Li |
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Description: ：为了使应力变异在顽健语音识别系统中能够达到较好的识别效果，研究了基于隐马
尔可夫模型(HMM)的自适应技术，提出了将最大后验概率(MAP)和最大似然回归方法(MLLR)用
于应力变异语音的自适应中。实验结果表明，与基本系统相比，两种方法均有效地提高系统识别
率。以SD为初始模型的最大后验概率方法在150个训练样本时识别效果最好，可以达到90．4％ 。-: In order to stress variation in the robustness of speech recognition system can achieve better recognition results, based on Hidden Markov Model (HMM) of adaptive technology, put forward a maximum a posteriori probability (MAP) and Maximum Likelihood regression (MLLR) for the stress of the adaptive variation in voice. The experimental results show that compared with the basic system, both methods are effective to improve the system recognition rate. SD as the initial model to the maximum a posteriori probability method in 150 training samples to identify the best, can reach 90.4 . Platform: |
Size: 234496 |
Author:尹江波 |
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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: |
Size: 432128 |
Author:sun |
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Description: 经典的最大似然法分类法的C语言实现，有助于深入了解遥感分类原理。-This program implements the maximum likelihood classification procedure. ouput:1.classified image, and 2. probability file.
Note: For constructong variance-covariance matrix must be generic binary file.
Platform: |
Size: 4096 |
Author:李会利 |
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Description: 3 books about distance function and Maximum Likelihood Estimation: Earth s Mover Distance, Kullback-Leibler, MLE Platform: |
Size: 1897472 |
Author:ChipChipKnight |
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Description: echniques for multi-user detection in OFDM / MC-CDMA can be classified as linear or non-linear techniques. A number of these techniques have evolved from previous research for CDMA–based systems. The overlaying of OFDM with CDMA permits grouping of the received signals based on received power, and this fact is exploited by the techniques discussed below. This project is going to focus on some of the more recent advances in some of the non-linear multi-user detection (MUD) techniques. A brief summary of the various techniques are given below. (Maximum Likelihood detection is not discussed here because of the computation complexity involved.)-echniques for multi-user detection in OFDM/MC-CDMA can be classified as linear or non-linear techniques. A number of these techniques have evolved from previous research for CDMA–based systems. The overlaying of OFDM with CDMA permits grouping of the received signals based on received power, and this fact is exploited by the techniques discussed below. This project is going to focus on some of the more recent advances in some of the non-linear multi-user detection (MUD) techniques. A brief summary of the various techniques are given below. (Maximum Likelihood detection is not discussed here because of the computation complexity involved.) Platform: |
Size: 63488 |
Author:Todd |
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Description: The results for 2×2 MIMO with Maximum Likelihood (ML) equalization helped us to achieve a performance closely matching the 1 transmit 2 receive antenna Maximal Ratio Combining (MRC) case. Platform: |
Size: 1024 |
Author:Umashankar Dewangan |
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Description: 最大似然译码的程序，用MATLAB编写的，很实用的例子-Maximum likelihood decoding process, using MATLAB written a very practical example of Platform: |
Size: 3072 |
Author:liqiang |
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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: |
Size: 4096 |
Author:平凡 |
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Description: HELP: coherent_ML_receiver
function [separated_data]=coherent_ML_receiver(received_signal,H,code_name,rate,num_code,modulator)
Perform Maximum Likelihood Space Time Decoding. The function can be
computionnaly expensive if the modulation order is too large.
Input: - received signal
- channel matrix: H
- code_name: The code name ( Alamouti , OSTBC3 ,...)
- code_rate: The code rate ( 1 , 1/2 ,...)
- num_code: The code number (1,2,...)
- modulator object
Ouput: - separated data
Note: This function requires the Matlab Communication Toolbox
Reference:
[1]E.G. Larsson,P.Stoica. "Space-time block coding for wireless
communications", Cambridge Press,2003
- HELP: coherent_ML_receiver
function [separated_data]=coherent_ML_receiver(received_signal,H,code_name,rate,num_code,modulator)
Perform Maximum Likelihood Space Time Decoding. The function can be
computionnaly expensive if the modulation order is too large.
Input: - received signal
- channel matrix: H
- code_name: The code name ( Alamouti , OSTBC3 ,...)
- code_rate: The code rate ( 1 , 1/2 ,...)
- num_code: The code number (1,2,...)
- modulator object
Ouput: - separated data
Note: This function requires the Matlab Communication Toolbox
Reference:
[1]E.G. Larsson,P.Stoica. "Space-time block coding for wireless
communications", Cambridge Press,2003
Platform: |
Size: 1024 |
Author:dasu |
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Description: 多天线系统的各种信号检测算法包括迫零，最小均方误差，最大似然，改进的最大似然等-A variety of multi-antenna systems signal detection algorithm, including zero-forcing, minimum mean square error, maximum likelihood, the improved maximum likelihood, etc. Platform: |
Size: 243712 |
Author:Ray |
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Description: This program calibrates the Ornstein–Uhlenbeck process, a mean reverting AR(1) stochastic process. The parameters are estimated using (1)Least Squares fitting and (2)Maximum Likelihood estimation.-This program calibrates the Ornstein–Uhlenbeck process, a mean reverting AR(1) stochastic process. The parameters are estimated using (1)Least Squares fitting and (2)Maximum Likelihood estimation. Platform: |
Size: 1024 |
Author:panda |
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Search - maximum likelihood