Delay and computational complexity are two problems to be solved when Maximum Likelihood Sequence Estimation (MLSE) is used in wireless communication system.
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。
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.
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。
By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and wide window.
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。
In this paper, a method of process quality diagnosis using hypothesis testing for residual sequence of ARMA innovation model estimation error by recursive maximum likelihood method was studied.
本文基于辨识 ARMA新息模型生成估计残差序列 ，再对残差序列的平均值和无偏方差进行假设检验 ，可实现工序质量的异常诊断。
In this paper, a method of process quality diagnosis using hypothesis testing for residual sequence of ARMA innovation model estimation error by recursive maximum likelihood method was studied.
本文基于辨识 ARMA新息模型生成估计残差序列 ，再对残差序列的平均值和无偏方差进行假设检验 ，可实现工序质量的异常诊断。
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