Parameter Optimization Method for Gaussian Mixture Model with Data Evolution

• 作 者: 於跃成 生佳根 邹晓华
• 机 构: CollegeofComputerScienceandEngineering,InformationTechnologyResearchBaseofCivilAviationAdministratio
• 出 处: 南京航空航天大学学报：英文版
• 发表日期: 2014年4期
• 基金项目: Supported by the National Natural Science Foundation of China（61202137）, the Open Project Foundation of Information Technology Research Base of Civil Aviation Administration of China（CAAC-ITRB-201302）

To learn from evolutionary experimental data points effectively,an evolutionary Gaussian mixture model based on constraint consistency(EGMM)is proposed and the corresponding method of parameter optimization is presented.Here,the Gaussian mixture model(GMM