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[Other resource] estimator DL : 0: Introduction to channel estimation by using LS and MMSE.
Update : 2008-10-13 Size : 9.92kb Publisher : 楊忠倫
[matlab] estimator DL : 0: Introduction to channel estimation by using LS and MMSE.
Update : 2025-04-04 Size : 10kb Publisher : 楊忠倫
[matlab] shuzhuangchengxu2 DL : 0: 梳状导频方式下OFDM系统的LS、LMMSE算法比较-Comb Pilot OFDM system under LS, LMMSE algorithm
Update : 2025-04-04 Size : 1kb Publisher : 袁园
[matlab] LS-MMSE DL : 0: LS vs MMSE estimator for SISO OFDM system
Update : 2025-04-04 Size : 1kb Publisher : Asterixsm
[Communication-Mobile] mimommse DL : 0: Channel Estimation of MIMO OFDM with MMSE Estimator.
Update : 2025-04-04 Size : 2kb Publisher : kalapraveen
[Other] LTE_channel_estimator DL : 0: LTE规范信道估计 MMSE zf -channel estimator lte
Update : 2025-04-04 Size : 5kb Publisher : 丽娜
[Other] LTE_channel_estimat2 DL : 0: LTE规范信道估计 MMSE zf -channel estimator lte
Update : 2025-04-04 Size : 4kb Publisher : 丽娜
[matlab] MMSE DL : 1: The Best Blind MMSE Estimator
Update : 2025-04-04 Size : 354kb Publisher : Alireza
[matlab] Channel_Estimation_Module DL : 0: 信道估计仿真，采用了多种方法：线性插值，MMSE，1惟MMSE,2维MMSE等-Channel Estimation 1 for non-block-wise linear interpolation, 2 for block-wise 1-D MMSE, 3 for non-block-wise 1-D MMSE, 4 for block-wise 2-D MMSE, 5 for non-block-wise 2-D MMSE, 6 for ideal channel estimator, 7 for random pilots map case using 2-D MMSE.
Update : 2025-04-04 Size : 4kb Publisher : todd
[Speech/Voice recognition/combine] MMSE DL : 0: 本程序为经典MMSE方法，引自Y. Ephraim and D.Malah “Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator-Ephraim and D.Malah “Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator
Update : 2025-04-04 Size : 2kb Publisher : 张丽
[Other] compare_siso DL : 0: mmse estimator implemented in a function for ofdm you can simulate using your parameters.
Update : 2025-04-04 Size : 1kb Publisher : billu
[Communication] 2modulesPppt DL : 0: A dynamic estimation of channel is necessary before the transmission of the signals since the wireless channel is time–varying..we use MMSE method for channel estimation. The MMSE method calculates the following, MMSE channel estimator is designed to minimize the estimation MSE. The MMSE estimate the channel responses.-A dynamic estimation of channel is necessary before the transmission of the signals since the wireless channel is time–varying..we use MMSE method for channel estimation. The MMSE method calculates the following, MMSE channel estimator is designed to minimize the estimation MSE. The MMSE estimate the channel responses.
Update : 2025-04-04 Size : 261kb Publisher : yuva
[Documents] CHAOGAOSI DL : 0: 研究表明超高斯分布更加贴近语音信号的实际分布，然而语音信号很难用单一的概率密度函数准确描述，针对这一情况，提出了一种用超高斯混合模型对语音信号幅度谱建模的新方法，并推导了基于此模型的幅度谱最小均方误差估的估计式。仿真结果表明：与传统的短时谱估计算法相比，该算法不仅能够进一步提高增强语音的信噪比，而且可以有效减小增强语音的失真度，提高增强语音的主观感知质量。 -Recent research indicates that the speech spectral amplitude distributions could be fairly described with super-Gaussian probability density function. However, the complexity of speech signal determines that the distribution statistics ofspeech signal could not be well described by single simple function. Thus a super-Gaussian mixture model for speech spectral amplitude is proposed, and with this model, a minimum mean-square error (MMSE) estimator for speech signals spectral amplitude is derived. The simulation results show that this algorithm based on Gaussian and super-Gaussian speech model could achieve better noise suppression and lower speech distortion as compared with the conventional short-time spectral amplitude estimation algorithm.
Update : 2025-04-04 Size : 935kb Publisher : 立枣酒
[Speech/Voice recognition/combine] Laplace DL : 0: 传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT) 系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优于传统的语音增强方法。-The spectral components of speech are usually assumed to be independent in traditional short-time spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform (DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show that the developed method has better noise suppression performance and lower speech distortion compared to the traditional speech enhancement method.
Update : 2025-04-04 Size : 1.01mb Publisher : 立枣酒
[matlab] MMSE_MSE_calc DL : 0: This function generates mean squared error for the the MMSE estimator
Update : 2025-04-04 Size : 1kb Publisher : Shirisha
[Program doc] MASSIVE-MIMO DL : 0: 本论文根据最小均方根误差准则（MMSE）,提出一种非正交设计导频的方法，这种方法在MASSIVE MIMO中非常有效。-In this letter, the error variance of the Minimal Mean-Square Error (MMSE) channel estimator is analyzed, and its analytic formula is given. Based on the analytic formula, a designing criterion on the pilot signals is proposed. When training time slots can be large enough, our criterion confirms the well-known fact that orthogonal pilot signals are optimal. But if training time slots are not enough to support this orthogonality, our results show that the error variance is lower-bounded away zero, no matter what kind of pilot signals are used. In this case, the design of pilot signals should be implemented by using the line packing on a complex Grassmannian manifold
Update : 2025-04-04 Size : 122kb Publisher : wangyanyan
[matlab] mss_mmse_spzc DL : 0: In statistics and signal processing, a minimum mean square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE) of the fitted values of a dependent variable, which is a common measure of estimator quality. In the Bayesian setting, the term MMSE more specifically refers to estimation in a Bayesian setting with quadratic cost function. In such case, the MMSE estimator is given by the posterior mean of the parameter to be estimated. Since the posterior mean is cumbersome to calculate, the form of the MMSE estimator is usually constrained to be within a certain class of functions. Linear MMSE estimators are a popular choice since they are easy to use, calculate, and very versatile. It has given rise to many popular estimators such as the Wiener-Kolmogorov filter and Kalman filter
Update : 2025-04-04 Size : 1kb Publisher : nagendra
[matlab] LMMSE DL : 0: In statistics and signal processing, a minimum mean square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE) of the fitted values of a dependent variable, which is a common measure of estimator quality. In the Bayesian setting, the term MMSE more specifically refers to estimation in a Bayesian setting with quadratic cost function. In such case, the MMSE estimator is given by the posterior mean of the parameter to be estimated. Since the posterior mean is cumbersome to calculate, the form of the MMSE estimator is usually constrained to be within a certain class of functions. Linear MMSE estimators are a popular choice since they are easy to use, calculate, and very versatile. It has given rise to many popular estimators such as the Wiener-Kolmogorov filter and Kalman filter.
Update : 2025-04-04 Size : 1kb Publisher : Said
[Other] pncaofdm--estimation DL : 0: ofdm-pnc 系统信道估计算。包括LS，LMMSE，SVD等算法-ofdm-plc system channel estimator. Including the LS, MMSE, SVD algorithms
Update : 2025-04-04 Size : 29kb Publisher : zhaodl
[Program doc] MMSE Channel Estimator for OFDM Receiver DL : 0: 我们基于Jake模型重新推导了新的自相关函数，并基于新的自相关函数提出了一种通用最小均方误差（MMSE）信道估计器。因此，由于其固有的鲁棒性，所提出的MMSE信道估计器可以被用于各种信道场景。 MMSE信道估计器的性能是通过实践DVB-T标准进行研究的，该标准表明MMSE信道估计器能以低复杂度实现非凡的最小平方误差性能(Based on the Jake model, we derive the new autocorrelation function and propose a universal minimum mean square error (MMSE) channel estimator based on the new autocorrelation function. Therefore, due to its inherent robustness, the proposed MMSE channel estimator can be used for various channel scenarios. The performance of MMSE channel estimator is studied through the practice of DVB-T standard, which indicates that MMSE channel estimator can achieve the least squared error performance with low complexity.)
Update : 2025-04-04 Size : 724kb Publisher : tsxywy365

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