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While the standard approach to quantum systems studies length preserving linear transformations of wave functions, the Markov picture focuses on trace preserving operators on the space of Hermitian (self-adjoint) matrices. The Markov approach extends the standard one and provides a refined analysis of measurements and quantum Markov chains. In particular, Bells inequality becomes structurally clear. It turns out that hidden state models are natural in the Markov context. In particular, a violation of Bells inequality is seen to be compatible with the existence of hidden states. The Markov model moreover clarifies the role of the negative probabilities in Feynmans analysis of the EPR paradox.
Joint radar and communication (JRC) technology has become important for civil and military applications for decades. This paper introduces the concepts, characteristics and advantages of JRC technology, presenting the typical applications that have b
Tight bounds for several symmetric divergence measures are introduced, given in terms of the total variation distance. Each of these bounds is attained by a pair of 2 or 3-element probability distributions. An application of these bounds for lossless
There is no closed form analytical equation or quick method to calculate probabilities based only on the entropy of a signal or process. Except in the cases where there are constraints on the state probabilities, one must typically derive the underly
We derive a lower bound on the smallest output entropy that can be achieved via vector quantization of a $d$-dimensional source with given expected $r$th-power distortion. Specialized to the one-dimensional case, and in the limit of vanishing distort
In this paper, we study a support set reconstruction problem in which the signals of interest are jointly sparse with a common support set, and sampled by joint sparsity model-2 (JSM-2) in the presence of noise. Using mathematical tools, we develop u