Free Access
Volume 14, 2010
Page(s) 93 - 116
Published online 10 May 2010
  1. A. Benveniste, P. Priouret and M. Métivier, Adaptive algorithms and stochastic approximations. Springer-Verlag, New York, Inc. (1990). [Google Scholar]
  2. P. Cohort, Limit theorems for random normalized distortion. Ann. Appl. Probab. 14 (2004) 118–143. [CrossRef] [MathSciNet] [Google Scholar]
  3. S. Dereich, High resolution coding of stochastic processes and small ball probabilities. Ph.D. thesis, TU Berlin (2003). [Google Scholar]
  4. A. Gersho and R.M. Gray, Vector Quantization and Signal Compression. Kluwer, Boston (1992). [Google Scholar]
  5. S. Graf and H. Luschgy, Foundations of Quantization for Probability Distributions. Lect. Notes Math. 1730. Springer, Berlin (2000). [Google Scholar]
  6. S. Graf and H. Luschgy, The point density measure in the quantization of self-similar probabilities. Math. Proc. Cambridge Phil. Soc. 138 (2005) 513–531. [CrossRef] [Google Scholar]
  7. R.M. Gray and D.L. Neuhoff, Quantization. IEEE Trans. Inform. 44 (1998) 2325–2383. [CrossRef] [MathSciNet] [Google Scholar]
  8. H.J. Kushner and G.G. Yin, Stochastic approximation algorithms and applications. First edition, volume 35 of Applications of Mathematics. Springer-Verlag, New York (1997), p. xxii+417. [Google Scholar]
  9. B. Lapeyre, G. Pagès and K. Sab, Sequences with low discrepancy. Generalization and application to robbins-monro algorithm. Statistics 21 (1990) 251–272. [CrossRef] [MathSciNet] [Google Scholar]
  10. H. Luschgy and G. Pagès, Functional quantization of stochastic processes. J. Funct. Anal. 196 (2002) 486–531. [CrossRef] [MathSciNet] [Google Scholar]
  11. H. Luschgy and G. Pagès, Sharp asymptotics of the functional quantization problem for Gaussian processes. Ann. Probab. 32 (2004) 1574–1599. [CrossRef] [MathSciNet] [Google Scholar]
  12. H. Luschgy and G. Pagès, Sharp asymptotics of the kolmorogov entropy for Gaussian measures. J. Funct. Anal. 212 (2004) 89–120. [CrossRef] [MathSciNet] [Google Scholar]
  13. M. Mrad and S. Ben Hamida, Optimal quantization: Evolutionary algorithm vs. stochastic gradient, in JCIS (2006). [Google Scholar]
  14. G. Pagès, A space vector quantization method for numerical integration. J. Appl. Comput. Math. 89 (1997) 1–38. [Google Scholar]
  15. G. Pagès, H. Pham and J. Printems, Optimal quantization methods and applications to numerical methods and applications in finance, in Handbook of Computational and Numerical Methods in Finance, S. Rachev (Ed.), Birkhäuser (2004), pp. 253–298. [Google Scholar]
  16. G. Pagès and J. Printems, Optimal quadratic quantization for numerics: the Gaussian case. Monte Carlo Meth. Appl. 9 (2003) 135–166. [CrossRef] [Google Scholar]
  17. G. Pagès and J. Printems, Functional quantization for numerics with an application to option pricing. Monte Carlo Meth. Appl. 11 (2005) 407–446. [CrossRef] [Google Scholar]
  18. G. Pagès and J. Printems, Website devoted to quantization (2005). [Google Scholar]
  19. K.T. Vu and R. Gorenflo, Asymptotics of singular values of volterra integral operators. Numer. Funct. Anal. Optimiz. 17 (1996) 453–461. [CrossRef] [Google Scholar]

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