606
R. Frühwirth et al.
5. T. Alexopoulos, M. Bachtis, E. Gazis, and G. Tsipolitis, “Implementation of the Legendre
Transform for track segment reconstruction in drift tube chambers,” Nucl. Instrum. Meth.,
vol. A592, pp. 456–462, 2008.
6. J. Hopfield, “Neural networks and physical systems with emergent collective computational
abilities,” Proc. Nat. Acad. Sci., vol. 79, p. 2554, 1982.
7. C. Peterson, “Track Finding With Neural Networks,” Nucl. Instrum. Meth., vol. A279, p. 537,
1989.
8. B. Denby, “Neural Networks and Cellular Automata in Experimental High-energy Physics,”
Comput. Phys. Commun., vol. 49, p. 429, 1988.
9. C. Peterson and J. Anderson, “A Mean Field Theory Learning Algorithm for Neural
Networks,” Complex Systems, vol. 2, p. 995, 1987.
10. M. Diehl, M. Junger, R. Frühwirth, and J. Scherzer, “Global optimization for track finding,”
Nucl. Instrum. Meth., vol. A389, p. 180, 1997.
11. G. Stimpfl-Abele and L. Garrido, “Fast track finding with neural nets,” Comput. Phys.
Commun., vol. 64, p. 46, 1991.
12. S. Baginian, A. Glazov, I. Kisel, E. Konotopskaya, V. Neskoromnyi, and G. Ososkov,
“Tracking by a modified rotor model of neural network,” Comput. Phys. Commun., vol. 79,
p. 165, 1994.
13. A. Badalà, R. Barbera, G. Lo Re, A. Palmeri, G. S. Pappalardo, A. Pulvirenti, and F. Riggi,
“Neural tracking in ALICE,” Nucl. Instrum. Meth., vol. A502, pp. 503–506, 2003.
14. A. Pulvirenti, A. Badala, R. Barbera, G. Lo Re, A. Palmeri, G. S. Pappalardo, and F. Riggi,
“Neural tracking in the ALICE Inner Tracking System,” Nucl. Instrum. Meth., vol. A533,
pp. 543–559, 2004.
15. A. Badalà, R. Barbera, G. Lo Re, A. Palmeri, G. S. Pappalardo, A. Pulvirenti, and F. Riggi,
“Combined tracking in the ALICE detector,” Nucl. Instrum. Meth., vol. A534, p. 211, 2004.
16. M. Gyulassy and M. Harlander, “Elastic tracking and neural network algorithms for complex
pattern recognition,” Comput. Phys. Commun., vol. 66, p. 31, 1991.
17. M. Gyulassy and M. Harlander, “High resolution multiparticle tracking without preprocessing
via elastic tracking,” Nucl. Instrum. Meth., vol. A316, p. 238, 1992.
18. M. Ohlsson, C. Peterson, and A. Yuille, “Track finding with deformable templates: The Elastic
arms approach,” Comput. Phys. Commun., vol. 71, p. 77, 1992.
19. M. Ohlsson, “Extensions and explorations of the elastic arms algorithm,” Comput. Phys.
Commun., vol. 77, p. 19, 1993.
20. R. Durbin and D. Willshaw, “An analogue approach to the travelling salesman,” Nature,
vol. 326, no. 16, p. 689, 1987.
21. D. Bui, T. Greenshaw, and G. Schmidt, “A combination of an elastic net and a Hopfield net to
solve the segment linking problem in the forward tracker of the H1 detector at HERA,” Nucl.
Instrum. Meth., vol. A389, p. 184, 1997.
22. I. Kisel and V. Kovalenko, “Elastic net for broken multiple scattered tracks,” Comput. Phys.
Commun., vol. 98, p. 45, 1996.
23. I. Kisel et al., “Cellular automaton and elastic net for event reconstruction in the NEMO-2
experiment,” Nucl. Instrum. Meth., vol. A387, p. 433, 1997.
24. R. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Journal of Basic
Engineering, vol. 82, no. 1, p. 35, 1960.
25. D. Catlin, Estimation, Control, and the Discrete Kalman Filter. NewYork: Springer, 1989.
26. R. Frühwirth, “Application of Kalman filtering to track and vertex fitting,” Nucl. Instrum.
Meth., vol. A262, p. 444, 1987.
27. P. Billoir, “Progressive track recognition with a Kalman like fitting procedure,” Comput.
Phys. Commun., vol. 57, p. 390, 1989.
28. R. Mankel, “A Concurrent track evolution algorithm for pattern recognition in the HERA-B
main tracking system,” Nucl. Instrum. Meth., vol. A395, p. 169, 1997.
29. A. Glazov, I. Kisel, E. Konotopskaya, and G. Ososkov, “Filtering tracks in discrete detectors
using a cellular automaton,” Nucl. Instrum. Meth., vol. A329, p. 262, 1993.
R. Frühwirth et al.
5. T. Alexopoulos, M. Bachtis, E. Gazis, and G. Tsipolitis, “Implementation of the Legendre
Transform for track segment reconstruction in drift tube chambers,” Nucl. Instrum. Meth.,
vol. A592, pp. 456–462, 2008.
6. J. Hopfield, “Neural networks and physical systems with emergent collective computational
abilities,” Proc. Nat. Acad. Sci., vol. 79, p. 2554, 1982.
7. C. Peterson, “Track Finding With Neural Networks,” Nucl. Instrum. Meth., vol. A279, p. 537,
1989.
8. B. Denby, “Neural Networks and Cellular Automata in Experimental High-energy Physics,”
Comput. Phys. Commun., vol. 49, p. 429, 1988.
9. C. Peterson and J. Anderson, “A Mean Field Theory Learning Algorithm for Neural
Networks,” Complex Systems, vol. 2, p. 995, 1987.
10. M. Diehl, M. Junger, R. Frühwirth, and J. Scherzer, “Global optimization for track finding,”
Nucl. Instrum. Meth., vol. A389, p. 180, 1997.
11. G. Stimpfl-Abele and L. Garrido, “Fast track finding with neural nets,” Comput. Phys.
Commun., vol. 64, p. 46, 1991.
12. S. Baginian, A. Glazov, I. Kisel, E. Konotopskaya, V. Neskoromnyi, and G. Ososkov,
“Tracking by a modified rotor model of neural network,” Comput. Phys. Commun., vol. 79,
p. 165, 1994.
13. A. Badalà, R. Barbera, G. Lo Re, A. Palmeri, G. S. Pappalardo, A. Pulvirenti, and F. Riggi,
“Neural tracking in ALICE,” Nucl. Instrum. Meth., vol. A502, pp. 503–506, 2003.
14. A. Pulvirenti, A. Badala, R. Barbera, G. Lo Re, A. Palmeri, G. S. Pappalardo, and F. Riggi,
“Neural tracking in the ALICE Inner Tracking System,” Nucl. Instrum. Meth., vol. A533,
pp. 543–559, 2004.
15. A. Badalà, R. Barbera, G. Lo Re, A. Palmeri, G. S. Pappalardo, A. Pulvirenti, and F. Riggi,
“Combined tracking in the ALICE detector,” Nucl. Instrum. Meth., vol. A534, p. 211, 2004.
16. M. Gyulassy and M. Harlander, “Elastic tracking and neural network algorithms for complex
pattern recognition,” Comput. Phys. Commun., vol. 66, p. 31, 1991.
17. M. Gyulassy and M. Harlander, “High resolution multiparticle tracking without preprocessing
via elastic tracking,” Nucl. Instrum. Meth., vol. A316, p. 238, 1992.
18. M. Ohlsson, C. Peterson, and A. Yuille, “Track finding with deformable templates: The Elastic
arms approach,” Comput. Phys. Commun., vol. 71, p. 77, 1992.
19. M. Ohlsson, “Extensions and explorations of the elastic arms algorithm,” Comput. Phys.
Commun., vol. 77, p. 19, 1993.
20. R. Durbin and D. Willshaw, “An analogue approach to the travelling salesman,” Nature,
vol. 326, no. 16, p. 689, 1987.
21. D. Bui, T. Greenshaw, and G. Schmidt, “A combination of an elastic net and a Hopfield net to
solve the segment linking problem in the forward tracker of the H1 detector at HERA,” Nucl.
Instrum. Meth., vol. A389, p. 184, 1997.
22. I. Kisel and V. Kovalenko, “Elastic net for broken multiple scattered tracks,” Comput. Phys.
Commun., vol. 98, p. 45, 1996.
23. I. Kisel et al., “Cellular automaton and elastic net for event reconstruction in the NEMO-2
experiment,” Nucl. Instrum. Meth., vol. A387, p. 433, 1997.
24. R. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Journal of Basic
Engineering, vol. 82, no. 1, p. 35, 1960.
25. D. Catlin, Estimation, Control, and the Discrete Kalman Filter. NewYork: Springer, 1989.
26. R. Frühwirth, “Application of Kalman filtering to track and vertex fitting,” Nucl. Instrum.
Meth., vol. A262, p. 444, 1987.
27. P. Billoir, “Progressive track recognition with a Kalman like fitting procedure,” Comput.
Phys. Commun., vol. 57, p. 390, 1989.
28. R. Mankel, “A Concurrent track evolution algorithm for pattern recognition in the HERA-B
main tracking system,” Nucl. Instrum. Meth., vol. A395, p. 169, 1997.
29. A. Glazov, I. Kisel, E. Konotopskaya, and G. Ososkov, “Filtering tracks in discrete detectors
using a cellular automaton,” Nucl. Instrum. Meth., vol. A329, p. 262, 1993.