Download Microwave Tomography: Global Optimization, Parallelization by Sima Noghanian, Abas Sabouni, Travis Desell, Ali Ashtari PDF

By Sima Noghanian, Abas Sabouni, Travis Desell, Ali Ashtari (auth.)

This booklet presents an in depth evaluation at the use of world optimization and parallel computing in microwave tomography thoughts. The ebook makes a speciality of strategies which are in line with worldwide optimization and electromagnetic numerical equipment. The authors offer parallelization recommendations on homogeneous and heterogeneous computing architectures on excessive functionality and common goal futuristic desktops. The booklet additionally discusses the multi-level optimization strategy, hybrid genetic set of rules and its program in breast melanoma imaging.

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Extra info for Microwave Tomography: Global Optimization, Parallelization and Performance Evaluation

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In Scattering and Inverse Scattering in Pure and Applied Sciences, vol. 1, ed. R. C. Sabatier (Academic, London, 2001), pp. 121–141 64. M. E. Kleinman, A contrast source inversion method. Inverse Probl. 13(6), 1607–1620 (1997) 65. A. Abubakar, P. van den Berg, J. Mallorqui, Imaging of biomedical data using a multiplicative regularized contrast source inversion method. IEEE Trans. Microw. Theor. Tech. 50(7), 1761–1771 (2002) 66. M. L. van Broekhoven, A. Abubakar, Extended contrast source inversion.

This term is needed because of the ill-posedness of the inverse problem, and in this book, a priori information is used as regularization term. 3 Time Domain Algorithm The majority of the proposed inverse scattering algorithms have used monochromatic (single-frequency) excitation [6–16]. Although using monochromatic incidences has been applied successfully to different applications of MWI, it has a significant shortcoming. It has been proven that due to the ill-posedness and nonlinearity of the problem the inverse algorithms fail if they only use monochromatic incidences [17].

Rocca, M. Benedetti, M. Donelli, D. Franceschini, A. Massa, Evolutionary optimization as applied to inverse scattering problems. Inverse Probl. 25(12), 1–41 (2009) 133. S. Noghanian, A. Sabouni, S. Pistorius, A numerical approach to microwave imaging based on genetic algorithm optimization. In Smart Structure and Materials and NDE for Health Monitoring and Diagnostics, San Diego, 2006 134. A. Yadollahi, A. B. h2 C l 2 / method for second-order hyperbolic equations with time-dependent boundary conditions.

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