无线通信中应用最大似然序列估计，其时延和计算复杂度是必须解决的两个问题。
Delay and computational complexity are two problems to be solved when Maximum Likelihood Sequence Estimation (MLSE) is used in wireless communication system.
在研究自适应均衡的原理、结构和算法的基础上，本文深入研究了最大似然序列估计(MLSE)。
This paper focuses on Maximum Likelihood Sequence Estimate (MLSE), based on the widely study of basic principle, structure and algorithms of adaptive equalization.
常用的最大似然序列估计(MLSE)均衡器采用维特比算法(VA)，它只能用于具有较小时延扩展的信道。
The Maximum Likelihood Sequence Estimation (MLSE) using the Viterbi Algorithm (VA) is commonly recommended for the equalization, which can only accommodate the channels with limited time delay spread.
最大似然序列检测技术被广泛应用于数字通信系统中来估计通过有噪声的符号间干扰（ISI）信道传输的数字数据序列。
Maximum likelihood sequence detection (MLSE) is broadly use in the digital communication system to estimate the transferred data through the ISI channel with noise.
通过简化最大似然估计目标函数，提出了用自适应迭代法并结合宽窗口法来实现序列同步和序列估计。
By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and wide window.
应用最大似然估计，得到了判决反馈这种基于发送序列以知的载波估计方法。
Using Maximum-likelihood estimation, we choose the decision feed back carrier estimate method based sent list known.
应用最大似然估计，得到了判决反馈这种基于发送序列以知的载波估计方法。
Using Maximum-likelihood estimation, we choose the decision feed back carrier estimate method based sent list known.
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