Nonlinear Multifunctional Sensor Signal Reconstruction Based on Local Least Squares Support Vector Machines

摘要：

Least squares support vector machines (LSSVM),as a recently reported least squares version support vector machines (SVM),involves equality constraints instead of inequality constraints and adopts least squares cost function,therefore it expresses the training by solving a set of linear equations instead of the quadratic programming problem which greatly reduces computational cost.In this paper,we combine LSSVM with a local approach in order to obtain accurate estimations of multifunctional sensor signals.For the simulation model of multifunctional sensor,the reconstruction accuracies of input signals are 1.07％ and 1.27％,respectively.The experimental results demonstrate the higher reliability and accuracy of proposed method for multifunctional sensor signal reconstruction than original LSSVM algorithm,and verify the feasibility of proposed method.

关键词： LSSVM multifunctional sensor signal reconstruction

作者: Xin Liu Jinwei Sun Guo Wei Dan Liu

作者单位: Dept.of Automatic Measurement and Control,Harbin Institute of Technology,Harbin 150001,China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）