A modified MMSE algorithm for speech enhancement based on speech periodic property is presented.
基于语音周期性的特点，提出了一种预加重的MMSE语音增强的改进算法。
By eliminating the possible influence produced by low quality data, the presented algorithm can improve localization precision effectively in comparison with the MMSE algorithm.
通过和最小均方误差估计算法(MMSE)相比较，变门限聚类定位算法可有效消除低质量数据对定位结果的影响，从而提高了目标的定位精度。
About denoising algorithm this paper researches focused on Spectral Subtraction algorithm and improved form, STSA-MMSE algorithm, using MATLAB tool to simulate these algorithms.
在去噪算法上本文重点研究了谱减法及其改进形式、STSA - MMSE去噪算法，用MATLAB工具仿真了这些算法。
MMSE algorithm is the most commonly technique which is used for MIMO detection. MMSE algorithm based on the principle of this view is valid to a co-channel interference of suppression.
MMSE算法是最常用的MIMO检测技术之一，本文根据MMSE算法的原理，提出了一种可抑制同频干扰的MMSE算法。
This algorithm utilizes time-average channel correlation matrix in place of exact channel correlation matrix and approximates the MMSE estimator by a low-rank structure.
该算法利用信道的时间平均相关取代统计相关，结合了基于特征值分解的低秩建模，从而近似地实现MMSE估计。
This paper mainly discusses the speech enhancement algorithm based on the Minimum Mean Square Error (MMSE) estimation of speech short time spectrum.
本文主要讨论基于语音短时谱估计的语音增强算法。
Analyze and compare the performance of LS, MMSE, LMMSE and their modified algorithm.
对LS、MMSE和LMMSE及其改进算法的性能进行了分析比较。
This technique is based on the suboptimal subspace blind minimum mean square error (MMSE) algorithm of multiuser detection.
该技术基于次优化子空间盲最小均方误差（MMSE）多用户检测算法。
Introduce the Wiener filter algorithm base on MMSE, and time domain channel estimation algorithms.
介绍了基于MMSE维纳滤波算法，变换域信道估计算法，以及判决反馈信道估计算法。
The comparison of threes methods, spectral subtraction, LOGSTSA-MMSE and subspace approach, is the major work in researching the noise reduction algorithm.
在去噪算法上本文重点比较了谱相减法、LOGSTSA-MMSE与子空间方法。
This technique is based on the suboptimal subspace blind minimum mean square error (MMSE) algorithm of multiuser detection.
针对快跳频多址系统，提出了基于最小均方误差（MMSE）准则的多用户检测算法。
This technique is based on the suboptimal subspace blind minimum mean square error (MMSE) algorithm of multiuser detection.
该技术基于次优化子空间盲最小均方误差(MMSE)多用户检测算法。
A modified MMSE-ML algorithm is proposed, by finding the second probable constellation symbol position after MMSE-ML search, and then applying the ML search on these two positions.
提出了一种改进的MMSE -ML算法，在一阶MMSE - ML搜索的中间结果中找出次最可能的星座符号位置，进而在这两个位置上做ML搜索。
SISO MMSE TURBO equalization algorithm is applied to equalizing section, and the characteristics of OFDM's cyclic prefix reduce the complexity of equalization further.
均衡器采用SISOMMSETURBO均衡算法，并利用OFDM系统的循环前缀特性进一步降低算法复杂度。
In Chapter Four, the common OFDM channel Estimation algorithm, including LS and MMSE method is studied and its corresponding performance is simulated and analyzed in UWB channel.
第四章主要研究了OFDM系统常见的信道估计方法，包括LS、MMSE等算法，并且在UWB信道条件下进行了相应的性能仿真和分析。
In Chapter Four, the common OFDM channel Estimation algorithm, including LS and MMSE method is studied and its corresponding performance is simulated and analyzed in UWB channel.
第四章主要研究了OFDM系统常见的信道估计方法，包括LS、MMSE等算法，并且在UWB信道条件下进行了相应的性能仿真和分析。
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