In this paper,a new method for extracting the parameters of buried object is proposed.The center position and dielectric properties of 2-D buried object are estimated by means of a regression technique based on suppor...In this paper,a new method for extracting the parameters of buried object is proposed.The center position and dielectric properties of 2-D buried object are estimated by means of a regression technique based on support vector machine（SVM）.The proposed method,after a proper training procedure,is able to reconstruct the center position and dielectric properties of a buried object inside a given investigation domain.Numerical simulation results indicate that SVM-based approach shows higher accuracy than the back-propagation neural networks（BPNN） algorithm.展开更多
基金Supported by the National Natural Science Foundation of China (50679037,60671040)
文摘In this paper,a new method for extracting the parameters of buried object is proposed.The center position and dielectric properties of 2-D buried object are estimated by means of a regression technique based on support vector machine（SVM）.The proposed method,after a proper training procedure,is able to reconstruct the center position and dielectric properties of a buried object inside a given investigation domain.Numerical simulation results indicate that SVM-based approach shows higher accuracy than the back-propagation neural networks（BPNN） algorithm.
