分布式估计算法 Estimation of Distribution Algorithms ; EDAS
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仿真结果表明基于协作的分布式估计算法的估计精度比Kalman估计算法更高，估计误差小于0。
Simulations indicate that distributed estimation based cooperation has higher estimation accuracy than the Kalman estimation algorithm with an estimation accuracy of less than 0.05.
论述了带反馈分布式信息融合系统中传感器观测维数不同时的状态估计方法。
The method of state estimation is discussed, when radars have different observation dimension in one distributed data fusion system with feedback.
在模型基础上系统地介绍了已有分布式目标参数估计方法，包括最大似然与最小二乘算法，DSPE和DISPARE算法等。
Systematically introduced parameter estimation of distributed sources on the base of models, including the maximum likelihood estimate, least squares estimator, DSPE, DISPARE, etc.
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