The method constructs a receiving noise model,whose parameters are determined by the weighted overlapped segment averaging method. The frequency parameters are estimated by a technique based on the Expectation-Maximization algorithm which,iteratively,produces good approximations to the maximum likelihood estimate.
首先构造目标辐射噪声的数理模型,然后根据加权交叠平均(WOSA)谱估计方法不产生伪峰的特点,判断可能存在的线谱数量和线谱频率,确定数理模型参数,然后采用EM迭代算法得到线谱频率的极大似然估计。
参考来源 - 基于WOSAThe condition moment estimate and the convergence maximum likelihood estimate are discussed. The simulation indicates that the condition moment estimation is more accurate than the convergence maximum likelihood estimation.3.
数值模拟表明条件矩估计优于渐进极大似然估计。
参考来源 - 随机波动率模型的统计推断及其衍生证券的定价·2,447,543篇论文数据，部分数据来源于NoteExpress
The parameters in model are estimated by maximum likelihood estimate method.
利用最大似然估计法对模型中的参数进行了估计。
The parameters in model were estimated by maximum likelihood estimate method.
利用最大似然估计法对模型中的参数进行了估计。
They are consistent with the Sum Maximum Likelihood Estimate and have consistence and minimum bias.
当误差为正态分布时，与和极大似然估计完全一致，具有一致性和最小估值偏差。
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