Table of Contents
X-Ray Optics and Instrumentation
Volume 2008 (2008), Article ID 168237, 7 pages
http://dx.doi.org/10.1155/2008/168237
Research Article

Custom Hardware Processor to Compute a Figure of Merit for the Fit of X-Ray Diffraction Peaks

1Department of Technologies of Computers and Communications, Polytechnic Institute, University of Extremadura, Campus Universitario s/n, 10071 Caceres, Spain
2Department of Applied Physics, School of Industrial Engineering, University of Extremadura, Avenida de Elvas s/n, 06071 Badajoz, Spain
3Department of Computer Science, Polytechnic Institute of Leiria, Alto do Vieiro, 2401-951 Leiria, Portugal

Received 24 October 2007; Revised 5 February 2008; Accepted 24 March 2008

Academic Editor: Scott Misture

Copyright © 2008 Juan A. Gomez-Pulido et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. P. Thompson, D. E. Cox, and J. B. Hastings, “Rietveld refinement of Debye-Scherrer synchrotron X-ray data from Al2O3,” Journal of Applied Crystallography, vol. 20, part 2, 79 pages, 1987. View at Publisher · View at Google Scholar
  2. Th. de Keijser, E. J. Mittemeijer, and H. C. F. Rozendaal, “The determination of crystallite-size and lattice-strain parameters in conjunction with the profile-refinement method for the determination of crystal structures,” Journal of Applied Crystallography, vol. 16, part 3, 309 pages, 1983. View at Publisher · View at Google Scholar
  3. S. Enzo, G. Fagherazzi, A. Benedetti, and S. Polizzi, “A profile-fitting procedure for analysis of broadened X-ray diffraction peaks. I. Methodology,” Journal of Applied Crystallography, vol. 21, part 5, 536 pages, 1988. View at Publisher · View at Google Scholar
  4. F. Sánchez-Bajo and F. L. Cumbrera, “The use of the Pseudo-Voigt function in the variance method of X-ray line-broadening analysis,” Journal of Applied Crystallography, vol. 30, part 4, 427 pages, 1997. View at Publisher · View at Google Scholar
  5. D. B. Fogel, Evolutionary Computation. Toward a New Philosophy of Machine Intelligence, IEEE Press, Piscataway, NJ, USA, 1995.
  6. Th. Bäck and H.-P. Schwefel, “An overview of evolutionary algorithms for parameter optimization,” Evolutionary Computation, vol. 1, no. 1, 1 pages, 1993. View at Publisher · View at Google Scholar
  7. E. Alba and M. Tomassini, “Parallelism and evolutionary algorithms,” IEEE Transactions on Evolutionary Computation, vol. 6, no. 5, 443 pages, 2002. View at Publisher · View at Google Scholar
  8. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Boston, Mass, USA, 1989.
  9. J. R. Koza, Genetic Programming: On the Programming of Computers by means of Natural Evolution, MIT Press, Cambridge, Mass, USA, 1992.
  10. K. Price and R. Storn, “Differential evolution: numerical optimization made easy,” Doctor Dobb's Journal, vol. 22, no. 4, 18 pages, 1997. View at Google Scholar
  11. H. A. Abbasse and R. Sarker, “The pareto differential evolution algorithm,” International Journal on Artificial Intelligence Tools, vol. 11, no. 4, 531 pages, 2002. View at Publisher · View at Google Scholar
  12. B. Zeidman, Designing with FPGAs and CPLDs, CMP Books, Gilroy, Calif, USA, 2002.
  13. M. A. Vega-Rodriguez, J. M. Sánchez-Perez, and J. A. Gómez-Pulido, “Guest editors' introduction—special issue on FPGAs: applications and designs,” Microprocessors and Microsystems, vol. 28, no. 5-6, 193 pages, 1994. View at Publisher · View at Google Scholar
  14. Xilinx ISE 9.2i software manuals, http://www.xilinx.com/.
  15. K. Ramamritham, K. Arya, and G. Fohler, “System software for embedded applications,” in Proceedings of the 17th International Conference on VLSI Design (VLSID '04), p. 12, IEEE Computer Society, Mumbai, India, January 2004. View at Publisher · View at Google Scholar
  16. Spartan-3 FPGA family: complete data sheet, http://www.xilinx.com/.
  17. Y. Sawaragi, H. Nakayama, and T. Tanino, Theory of Multiobjective Optimization, Academic Press, Orlando, Fla, USA, 1985.