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Heidelberg, pp. 107–125 (1990).
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485
105. P. E. Kloeden and E. Platen. A survey of numerical methods for stochastic
differential equations. Stochastic Hydrology and Hydraulics, vol. 3, no. 5, pp.
155-178 (1989).
106. E. Platen and K. Kubilius. Rate of weak convergence of the Euler approximation for diffusion processes with jumps. School of Finance and Economics,
University of Technology, Sydney (2001).
107. A. Kolmogorov. On Analytical Methods in the Theory of Probability, pp.
448–451, (1931),
108. H. J. Kushner, G. G. Yin. Stochastic approximation and recursive algorithms
and applications, vol. 35, Applications of Mathematics. Springer- Verlag, New
York (2003)
109. H. J. Kushner, D. S. Clark. Stochastic approximation methods for constrained and unconstrained systems, vol. 26 of Applied Mathematical Sciences.
Springer- Verlag, New York (1978).
110. L. D. Landau, E. M. Lifshitz. Course of theoretical physics. Physical kinetics, E. M. Lifshitz and L. P. Pitaevskii eds. vol. 10, Oxford, Pergamon (1981).
111. F. Le Gland, V. Monbet, and V. D. Tran. Large sample asymptotics for
the ensemble Kalman filter. In Handbook on Nonlinear Filtering, D. Crisan and
B. Rozovskii, Eds. Oxford University Press, Oxford, pp. 598–631 (2011).
112. V. Tran, V. Monbet and F. Le Gland. Filtre de Kalman d’ensemble et
filtres particulaires pour le mod` ele de Lorenz. Actes de la Manifestation des
Jeunes Chercheurs STIC (MajecSTIC’06), Lorient, November 22-24 (2006).
113. K. Macek, R. Philippsen, and R.Siegwart. Path Following for Autonomous Vehicle Navigation based on Kinodynamic Control. Journal of Computing
and Information Technology (2008).
114. H. P. McKean. A class of Markov processes associated with nonlinear parabolic equations. Proc. Nat. Acad. Sci. USA. vol. 56, pp. 1907–1911 (1966)
115. G. Marsaglia, A. Zaman. A new class of random number generators. Ann.
Appl. Prob., 1, pp. 462-480 (1991).
116. S. Maskell, M. Rollason, N.J. Gordon, and D. Salmond.. Efficient particle filtering for multiple target tracking with application to tracking in structured images. Image and Vision Computing. Vol. 21, no. 10, pp. 931–939 (2003).
117. S. M´ el´ eard. Some stochastic models of interacting diffusion processes and the
associated propagation of chaos. Proceedings, Stochastic Modelling in Biology,
Heidelberg, pp. 107–125 (1990).
118. S. P. Meyn and R.L. Tweedie. Markov Chains and Stochastic Stability.
Springer-Verlag, London. Available at : probability.ca/MT (1993).
119. S. P. Meyn. Control Techniques for Complex Networks. Cambridge University
Press (2007).
120. J. P. Mills. Table of the ratio : area to bounding ordinate, for any portion of
the normal curve. Biometrika, vol. 18, pp. 395–400 (1926).
121. Musso, C. and Oudjane, N. Recent particle filter applied to terrain navigation. In Proceedings of the 3rd International Conference on Information Fusion,
Paris (2000).
122. B. Mandelbrot. The fractal geometry of nature. W.H. Freeman & Co. (1982).