volume | PIER Journals

Abstract

This study proposes a real-time method to solve the electromagnetic inverse scattering problem. This technique converts this problem into a regression problem using a support vector machine (SVM). The SVM-based solution successfully deals with the nonlinearity and ill-posedness inherent in thisproblem. Simulation results show the feasibility and effectiveness of the proposed method. The method can effectively locate the tumor target of the stomach regardless of the presence of noise. The positioning effect of the method improves as SNR increases. When the SNR is higher than 50 dB, noise minimally affects the results. Finally, the SVM prediction model is utilized to study the effect of the number of sampling locations on the prediction results. The results show that the more sampling locations, the better the prediction results.

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Dr. Gong Chen

Dr. Ye-Rong Zhang

Dr. Bi-Yun Chen