Novel magnetic field computation model in pattern classification  

作　　者：Feng Pan Xiaoting Li Ting Long Xiaohui Hu Tingting Ren Junping Du 

机构地区：[1]School of Automation,Beijing Institute of Technology [2]GE Intelligent Platforms 325 Foxboro Blvd Foxboro [3]School of Computer Science, Beijing University of Posts and Telecommunications

出　　处：《Journal of Systems Engineering and Electronics》2013年第5期862-869,共8页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(60903005);the National Basic Research Program of China(973 Program)(2012CB821206)

摘　　要：Field computation, an emerging computation technique, has inspired passion of intelligence science research. A novel field computation model based on the magnetic field theory is constructed. The proposed magnetic field computation （MFC） model consists of a field simulator, a non-derivative optimization algo- rithm and an auxiliary data processing unit. The mathematical model is deduced and proved that the MFC model is equivalent to a quadratic discriminant function. Furthermore, the finite element prototype is derived, and the simulator is developed, combining with particle swarm optimizer for the field configuration. Two benchmark classification experiments are studied in the numerical experiment, and one notable advantage is demonstrated that less training samples are required and a better generalization can be achieved.Field computation, an emerging computation technique, has inspired passion of intelligence science research. A novel field computation model based on the magnetic field theory is constructed. The proposed magnetic field computation （MFC） model consists of a field simulator, a non-derivative optimization algo- rithm and an auxiliary data processing unit. The mathematical model is deduced and proved that the MFC model is equivalent to a quadratic discriminant function. Furthermore, the finite element prototype is derived, and the simulator is developed, combining with particle swarm optimizer for the field configuration. Two benchmark classification experiments are studied in the numerical experiment, and one notable advantage is demonstrated that less training samples are required and a better generalization can be achieved.

关 键 词：magnetic field computation （MFC） field computation particle swarm optimization （PSO） finite element analysis ma- chine learning and pattern classification. 

分 类 号：TM15[电气工程—电工理论与新技术]