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—Research on fingerprint classification has primarily focused on finding improved classifiers, image and feature enhancement, and less on the development of novel fingerprint representations. Using an AM–FM representation for each fingerprint, we obtain significant gains in classification performance as compared to the commonly used National Institute of(More)
In an earlier paper, the authors introduced the notion of safety control of stochastic discrete event systems (DESs), modeled as controlled Markov chains. Safety was specified as an upper bound on the components of the state probability distribution, and the class of irreducible and aperiodic Markov chains were analyzed relative to this safety criterion.(More)
— We study the control of completely observed Markov chains with safety bounds as introduced in [3], but with more general safety constraints and the added requirement of optimality. In [3], the safety bounds were specified as unit-interval valued vector pairs (lower and upper bounds for each component of the state probability distribution). In this paper(More)
We study the control of completely observed Markov chains subject to generalized safety bounds and optimality requirement. Originally, the safety bounds were specified as unit-interval valued vector pairs (lower and upper bounds for each component of the state probability distribution). In this paper, we generalize the constraint to be any linear convex set(More)
A new method based on the YCbCr channel information is proposed for image demosaicing. The method includes three steps. The first step follows the convenient approach to calculate the candidates of estimators for the missing pixels. The second step employs a novel soft-decision method to determine the proper estimators. The final step finalizes the(More)