Universal Prediction - Information Theory, IEEE Transactions on

Universal Prediction

This paper consists of an overview on universal prediction from an information-theoretic perspective. Special attention is given to the notion of probability assignment under the self-information loss function, which is directly related to the theory of universal data compression. Both the probabilistic setting and the deterministic setting of the universal prediction problem are described with...

Efficient Lossless Coding of Medical Image Volumes Using Reversible Integer Wavelet Transforms

of 1996 Data Compression Conference, 1996, p. 436. [22] C. S. Barreto and G. V. Mendonca, “Enhanced zerotree wavelet transform image coding exploiting similarities inside subbands,” in Proc. of International Conference on Image Processing, 1996, vol. 2, pp. 549–551. [23] X. Wu and J.-H. Chen, “Context modeling and entropy coding of wavelet coefficients for image compression,” in Proc. of 1997 I...

Universal coding, information, prediction, and estimation

A connection between universal codes and the problems of prediction and statistical estimation is established. A‘known lower bound for the mean length of universal codes is sharpened and generalized, and optimum universal codes constructed. The bound is defined to give the information in strings relative to the considered class of processes. The earlier derived minimum description length criter...

On optimal sequential prediction for general processes

This paper considers several aspects of the sequential prediction problem for unbounded, non-stationary processes under p-th power loss lp(u, v) = |u−v|, 1 < p < ∞. In the first part of the paper it is shown that Bayes prediction schemes are Cesaro optimal under general conditions, that Cesaro optimal prediction schemes are unique in a natural sense, and that Cesaro optimality is equivalent to ...

An efficient universal prediction algorithm for unknown sources with limited training data