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Abstruct-The problem of predicting the next outcome of an individual binary sequence using finite memory, is considered. The finite-state predictability of an infinite sequence is defined as the minimum fraction of prediction errors that can be made by any finite-state (FS) predictor. It is proved that this FS predictability can be attained by universal(More)
Achievable rates are characterized for successive refinement (SR) in the Wyner-Ziv scenario, namely, in the presence of correlated side information (SI) at the receivers. In this setting, the encoder is assumed to operate in two stages, where the first corresponds to relatively low rate and high distortion, and the second, comprising a refinement code on(More)
Reliable transmission over a discrete-time memory-less channel with a decoding metric that is not necessarily matched to the channel (mismatched decoding) is considered. It is assumed that the encoder knows both the true channel and the decoding metric. The lower bound on the highest achievable rate found by Csiszar and Komer and by Hui for DMC's, hereafter(More)
We consider the problem of estimating, in the presence of model uncertainties, a random vector x that is observed through a linear transformation H and corrupted by additive noise. We first assume that both the covariance matrix of x and the transformation H are not completely specified and develop the linear estimator that minimizes the worst-case(More)
The problem of optimal sequential decision for individual sequences, relative to a class of competing oo-line reference strategies, is studied for general loss functions with memory. This problem is motivated by applications in which actions may h a ve \long term" eects, or there is a cost for switching from one action to another. As a rst step, we consider(More)