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.
在这类特殊的多传感器系统中，本文通过矩阵运算消除相关估计方差，得到了最优分布式融合估计算法。
For this special multisensor system, distributed optimal fusion algorithm is received by avoiding computing correlated estimation covariance based on the matrix operation.
比较了目前分布式视频系统的各种码率估计算法性能，并提出了改进的码率估计算法。
With a comparison on a few of rate estimation algorithms, an improved methods resided in the decoder is proposed in this paper.
分布式算法通过其边界协调方程来修正边界节点估计值，从而保证了计算的精度。
The DSE method modified the results of the boundary buses by the coordinate function, thus it ensures the calculating precision generally.
基于多传感器单模型动态系统的多尺度估计理论，研究了不同尺度上拥有不同统计特性的多尺度融合算法及多尺度分布式融合估计算法。
Basing multiscale estimation theory of multi-sensors and single-model of dynamic system, the multiscale fuse algorithm and multiscale distribute fuse algorithm were studied respectively.
数字仿真表明，分布式联合、估计算法在各种性能指标上都优于单站跟踪算法。
The Monto Carlo simulation shows that the distributed fusion algorithm performs much better than the local estimation algorithm in every function index and achieves the expected effec…
数字仿真表明，分布式联合、估计算法在各种性能指标上都优于单站跟踪算法。
The Monto Carlo simulation shows that the distributed fusion algorithm performs much better than the local estimation algorithm in every function index and achieves the expected…
数字仿真表明，分布式联合、估计算法在各种性能指标上都优于单站跟踪算法。
The Monto Carlo simulation shows that the distributed fusion algorithm performs much better than the local estimation algorithm in every function index and achieves the expected…
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