摘要
针对具有多个特征指标的目标识别问题,提出了一种新的模糊传感器数据融合方法。该方法由最大最小隶属度函数得到相对距离矩阵,通过求解总偏差最小的数学规划问题,确定各特征的权重,从而给出目标识别算法,提高了目标识别结果的客观性。应用实例验证了算法的有效性。
Aimed at the object recognition problem with multiple characteristic indices, a new fusion method for the fuzzy sensor data is proposed. The method introduces the max-min membership degree function to define the relative distance matrix. By solving the mathematical programming of minimizing total deviations, the weights of characteristic indices are determined. Hence, the algorithm of object recognition is given. The method improves the objectivity of recognition result. The applied example proves that the method is effective.
出处
《传感器与微系统》
CSCD
北大核心
2009年第1期22-23,26,共3页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(10626029)
江西省教育厅科技计划资助项目(GJJ08350)
关键词
模糊多传感器
数据融合
目标识别
偏差
fuzzy multi-sensor
data fusion
object recognition
deviation
