MDL denoising

IEEE Transactions on Information Theory

Volumn 46, Issue 7, 2000, Pages 2537-2543

  Rissanen, Jorma ^a  

^a IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ASYMPTOTIC STABILITY; CODES (SYMBOLS); MAXIMUM LIKELIHOOD ESTIMATION; NORMAL DISTRIBUTION; PROBABILITY DENSITY FUNCTION; RANDOM PROCESSES; REGRESSION ANALYSIS; WAVELET TRANSFORMS;

KOLMOGOROV SUFFICIENT STATISTICS; LINEAR REGRESSION; MINIMUM DESCRIPTION LENGTH DENOISING; NORMALIZED MAXIMUM LIKELIHOOD TECHNIQUE; ORTHONORMAL REGRESSION MATRIX;

SIGNAL FILTERING AND PREDICTION;

EID: 0034316026     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/18.887861     Document Type: Article

References (13)

1. A. R. Barren, J. Rissanen, and B. Yu, The MDL principle in modeling and coding, Special Issue of IEEE Trans. Information Theory to Commemorate 50 Years of Information Theory, vol. 44, pp. 2743-2760, Oct. 1998.
2. T. M. Cover and J. A. Thomas, Elements of Information Theory. New York: Wiley, 1991.
3. B. Dom, MDL estimation for small sample sizes and its application to linear regression," IBM Corp., Res. Rep. RJ 10030, June 13, 1996.
4. D. L. Donoho and I. M. Johnstone, Ideal spatial adaptation by wavelet shrinkage, Biometrika, vol. 81, pp. 425155, 1994.
5. D. P. Foster and E. I. George, The risk inflation criterion for multiple regression," A. Statist., vol. 22, no. 4, pp. 1947-75, 1994.
6. M. H. Hansen and B. Yu. (1998) Model selection and the principle of minimum description length [Online]. Available : http://cm.bell-labs. com/stat/doc/mdl.ps.Z
7. H. Krim and I. C. Schick, Minimax description length for signal denoising and optimized representation, IEEE Trans. Inform. Theory, vol. 45, pp. 898-908, Apr. 1999.
8. G. P. Nason, Wavelet shrinkage using cross-validation, J. Roy. Statist. Soc. B, vol. 58, no. 2, pp. 46379, 1996.
9. J. Rissanen, Fisher information and stochastic complexity, IEEE Trans. Inform. Theory, vol. 42, pp. 40-47, Jan. 1996.
10. Stochastic Complexity in Statistical Inquiry, 2nd ed. Singapore: World Scientific, 1998, 177pp.
11. Hypothesis selection and testing by the MDL principle (Invited Paper)" Comput. J., vol. 42, no. 4, pp. 260-269, 1998.
12. A generalized MinMax bound for universal coding, P roc. IEEE Int. Symp. Information Theory (ISIT2000), Sorrento, Italy, June 25-30, 2000.
13. Yu. M. Shtarkov, Universal sequential coding of single messages, Probt. Inform. Transm., vol. 23, no. 3, pp. 3-17, July-Sept. 1987.