[1] Mankel R., Pattern recognition and event reconstruction in particle physics experiments. Reports on Progress in Physics, 2004, 67, pp. 553–622.
[2] Billoir P., Track Fitting With Multiple Scattering: A New Method. Nucl. Instrum. Meth., 1984, A225, pp. 352–366.
[3] Billoir P., Fruhwirth R., Regler M., Track Element Merging Strategy and Vertex Fitting in Complex Modular Detectors. Nucl. Instrum. Meth., 1985, A241, pp. 115–131.
[4] Billoir P., Progressive track recognition with a Kalman like fitting procedure. Comput. Phys. Commun., 1989, 57, pp. 390–394.
[5] Fruhwirth R., Application of Kalman filtering to track and vertex fitting. Nucl. Instrum. Meth., 1987, A262, pp. 444–450.
[6] Kalman R.E., A new approach to linear filtering and prediction problems. Transactions of the ASME–Journal of Basic Engineering, 1960, 82(Series D), pp. 35–45.
[7] Myers S., The large hadron collider 2008-2013. International Journal of Modern Physics A, 2013, 28(25), pp. 1330035.
[8] Cornelissen T., Elsing M., Fleischmann S., Liebig W., Moyse E., Salzburger A., Concepts, Design and Implementation of the ATLAS New Tracking (NEWT). Technical Report ATL-SOFT-PUB-2007-007. ATL-COM-SOFT-2007002, CERN, 2007.
[9] Collaboration A., Airapetian A., Cindro V., Filipˇciˇc A., Kramberger G., Mandi´c I., Mikuˇz M., Tadel M., ˇZontar D., ATLAS detector and physics performance. Technical design report. ATLAS, 1999.
[10] Palmonari F., CMS tracker performance. Nucl.Instrum.Meth., 2013, A699, pp. 144–148.
[11] Merkel P., CMS tracker performance. Nucl.Instrum.Meth., 2013, A718, pp. 339– 341.
[12] CMS collaboration and others, Description and performance of track and primary-vertex reconstruction with the cms tracker. Journal of Instrumentation, 2014, 9(10), pp. P10009.
[13] Abelev B., et al., Upgrade of the ALICE Experiment: Letter Of Intent. J. Phys., 2014, G41, pp. 087001.
[14] Aamodt K., et al., The ALICE experiment at the CERN LHC. JINST, 2008, 3, pp. S08002.
[15] Amoraal J., Collaboration L., et al., Alignment of the LHCb detector with kalman filter fitted tracks. In: Journal of Physics: Conference Series. vol. 219., IOP Publishing, 2010, pp. 032028.
[16] Rodrigues E., The LHCb track kalman fit. Note LHCb-2007-014, 2007, 164.
[17] Hernando J., Rodrigues E., Tracking event model, LHCb internal note, LHCb2007-007. CERN-LHCb-2007-007.
[18] Schiller M., Standalone track reconstruction for the Outer Tracker of the LHCb experiment using a cellular automaton. PhD thesis, Uni Heidelberg 2007.
[19] Passaleva G., A recurrent neural network for track reconstruction in the LHCb muon system. In: Nuclear Science Symposium Conference Record, 2008. NSS’08. IEEE, IEEE, 2008, pp. 867–872.
[20] Pulvirenti A., Badala A., Barbera R., Lo Re G., Palmeri A., et al., Neural tracking in the ALICE Inner Tracking System. Nucl. Instrum. Meth., 2004, A533, pp. 543–559.
[21] Badala A., Barbera R., Lo Re G., Palmeri A., Pappalardo G., et al., Combined tracking in the ALICE decetctor. Nucl. Instrum. Meth., 2004, A534, pp. 211–216.
[22] Badala A., Barbera R., Re G.L., Palmeri A., Pappalardo G., Pulvirenti A., Riggi F., Neural tracking in alice. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2003, 502(2), pp. 503–506.
[23] Strandlie A., Fru¨hwirth R., Track and vertex reconstruction: From classical to adaptive methods. Reviews of Modern Physics, 2010, 82(2), pp. 1419.
[24] Abgrall N., et al., Na61/shine facility at the cern sps: beams and detector system. Journal of Instrumentation, 2014, 9(06), pp. P06005.
[25] Nygren D.R., Proposal to investigate the feasibility of a novel concept in particle detection. LBL Internal Report, 1974.
[26] Wyszynski O., Trigger system of the NA61/SHINE experiment at the CERN SPS, 2014.
[27] Laszlo A., Denes E., Fodor Z., Kiss T., Kleinfelder S., Soos C., Tefelski D., Tolyhi T., Vesztergombi G., Wyszynski O., Design and performance of the data acquisition system for the na61/shine experiment at cern. arXiv preprint arXiv:1505.01004, 2015.
[28] Gorbunov S., Kisel I., Analytic formula for track extrapolation in nonhomogeneous magnetic field. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2006, 559(1), pp. 148–152.
[29] Jordan A., On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes. Advances in neural information processing systems, 2002, 14, pp. 841.
[30] Hand D.J., Yu K., Idiot’s bayesnot so stupid after all? International statistical review, 2001, 69(3), pp. 385–398.
[31] Domingos P., Pazzani M., Beyond independence: Conditions for the optimality of the simple bayesian classifier. In: Machine Learning, Morgan Kaufmann, 1996, pp. 105–112.
[32] Hansen N., Ostermeier A., Adapting arbitrary normal mutation distributions in evolution strategies: The covariance matrix adaptation. In: Proceedings of the 1996 IEEE International Conference on Evolutionary Computation. IEEE 1996 pp. 312–317.
[33] Hansen N., Ostermeier A., Completely derandomized self-adaptation in evolution strategies. Evolutionary Computation, 2001, 9(2), pp. 159–195.
[34] Hansen N., The CMA evolution strategy: a comparing review. In Lozano J., Larranaga P., Inza I., Bengoetxea E., eds.: Towards a new evolutionary computation. Advances on estimation of distribution algorithms. Springer 2006 pp. 75–102.
[35] Jastrebski G.A., Arnold D.V., Improving evolution strategies through active covariance matrix adaptation. In: Evolutionary Computation, 2006. CEC 2006. IEEE Congress on. IEEE 2006 pp. 2814–2821.
[36] Agostinelli S.e.a., GEANT4: A simulation toolkit. Nuclear Instruments and Methods in Physics Research, 2003, A506, pp. 250–303.
[37] Sipos R., Laszlo A., Marcinek A., Paul T., Szuba M., Unger M., Veberic D., Wyszynski O., The offline software framework of the na61/shine experiment. In: Journal of Physics: Conference Series. vol. 396., IOP Publishing, 2012, pp. 022045.
[38] Irmscher D., Philosophy and parts of the global tracking chain. NA49 Note number 131 (1997).