| 1. | In that case , the data are compressed in the fusion center to improve the computational efficiency
当这一条件不满足，文献上一直未见观测数据如何压缩的结果。 |
| 2. | In recent years , multisensor kalman filter fusion have received significant attention for both military and non - military applications . but in fusion center the data size may be too large to be processed immediately
多传感器的kalman滤波融合是在许多军事和民用高科技部门中有重要应用的问题，在融合中心常常会因观测数据过大而不能实时处理。 |
| 3. | A suboptimal decision fusion scheme that minimize the probability of error at the fusion center is presented , it consists of a minimum - error - probability ( mep ) test at the fusion center and likelihood ration tests at the sensors
提出了一种能将聚变中心误差概率降至最低的次优化聚变解决方案，它由聚变中心的最少误差概率（ mep ）试验和传感器的可能定量试验组成。 |
| 4. | The sampling period of the fusion center is defined as the lease common multiple of multi - sensors measurement period , so the same number of the local state estimation is transmitted to the fusion center every sampling period and the computation burden of the tracking filter is alleviated
该算法将融合中心的采样周期设定为感测器测量周期的最小公倍数，使得传输到融合中心的局部状态估计在每个周期内具有相同的数目，减少了跟踪滤波的计算量。 |
| 5. | The research emphasis is laid on the design and implementation of the fusion center software . a kind of multi - layer blackboard fusion center software structure is presented , and we propose a new object - oriented system data structure design method . the thread structure based on posix and the database process method base
论文主要研究了融合中心软件的设计与实现，提出了一种基于层次黑板结构的融合中心软件结构，研究了面向对象的融合中心数据结构设计与组织方法及基于posix多线程的软件线程结构与基于oracle的数据库处理。 |
| 6. | The second is a fuzzy neuron network based hybrid filter , which comprises four basic components : plus - shaped center weighted median filter , cross - shaped center weighted median filter , nine pixels median filter , and a fusion center with fuzzy - neuron network . the proposed filter is able to effectively inherit the merits of the used three filters . the third is a fuzzy reasoning filter based on neural network
第二种是基于模糊神经网络的混合滤波器，主要滤波器模块有十字型中心加权中值滤波器、交叉型中心加权中值滤波器和9点中值滤波器，信号经过三种滤波器处理后送入一个训练好的模糊神经网络进行融合处理，得到最终的滤波结果。 |
| 7. | This paper studies a design method of decentralized signal detection system which consists of adaptive fuzzied local - detectors and a data fusion rule of on - line self - learning weights . the local - detectors for inaccurate signal parameters are modeled by means of fuzzy sets which can be adapted to change of the inaccurate signal parameteres . the data fusion center where the optimal declsion rules are used as objective function can learn the local decision weights on - line . the robustness of the fuzzied local - detectors and the adaptability of the self - learned fusion rule make it true that the detection performance of the decentralized detection system is improved under uncertainty and this system can also process the decentralized signal detection with a unknown parameter of unknown distribution or non - random unknown parameter
本文研究了一种由局部自适应模糊检测器和在线自学习融合算法所构成的分布式信号检测系统的设计方法.由模糊集对不精确信号参数的局部检测器进行建模，该模糊模型可自适应不精确信号参数的变化.融合中心以最佳融合规则作为目标函数在线自学习局部判决的权重.局部模糊检测器的鲁棒性和自学习融合算法的自适应性使该分布式检测系统在不确定环境下的检测性能得到提高.也使该系统能够处理未知分布的未知参数以及非随机未知参数的分布式信号检测 |
