论文信息 - Evolutionary Algorithms in Image Reconstruction from Limited Data

Evolutionary Algorithms in Image Reconstruction from Limited Data

We consider in this paper two classes of evolutionary methods for improving the ART Kaczmarz procedure: genetic and, respectively particle swarm optimization algorithms. They are combined in various ways with the classical Kaczmarz projection method, in two classes of hybrid algorithms. Experiments ilustrating the efficiency of these new methods are presented for consistent least-squares formulation of some simulated reconstruction problems in borehole electromagnetic geotomography. AMS Subject Classifications: 65F10, 65F20, 68T20

Elena Bautu | Constantin Popa | A. Bautu

[1] Zbigniew Michalewicz,et al. Genetic algorithms + data structures = evolution programs (3rd ed.) , 1996 .

[2] Åke Björck,et al. Numerical methods for least square problems , 1996 .

[3] Rafal Zdunek,et al. Kaczmarz extended algorithm for tomographic image reconstruction from limited-data , 2004, Math. Comput. Simul..

[4] F. Natterer. The Mathematics of Computerized Tomography , 1986 .

[5] Andrzej Stachurski,et al. Parallel Optimization: Theory, Algorithms and Applications , 2000, Parallel Distributed Comput. Pract..

[6] James Kennedy,et al. Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[7] Y. Censor,et al. Parallel Optimization: Theory, Algorithms, and Applications , 1997 .

[8] Åke Björck. 7. Iterative Methods for Least Squares Problems , 1996 .