Dualization of a monotone Boolean function represented by a conjunctive normal form (CNF) is a problem which, in different disguise, is ubiquitous in many areas including Computer Science, Artificial Intelligence, and Game Theory to mention some of them. It is also one of the few problems whose precise tractability status (in terms of polynomial-time solvability) is still unknown, and now open ...

A new method for tissue classification of brain magnetic resonance images (MRI) of the brain is proposed. The method is based on local image models where each models the image content in a subset of the image domain. With this local modeling approach, the assumption that tissue types have the same characteristics over the brain needs not to be evoked. This is important because tissue type chara...

increasing water distribution uniformity in micro irrigation systems has been an important subject in applied researches. despite considerable progress in emitters’ construction, some research reports refer to their incapability in water distribution uniformity. in order to achieve greater uniformity in micro irrigation, it is necessary to manufacture emitters with low variation in manufacturin...

introduction: non-uniformity test is essentially the only required daily qc procedure in nuclear medicine practice. noise creates statistical variation or random error in a flood image. non-uniformity on the other hand does not have statistical nature and may be regarded as systemic error. the present methods of non-uniformity calculation do not distinguish between these two types of error. the...

We define sequential completeness for ⊤-quasi-uniform spaces using Cauchy pair ⊤-sequences. show that implies and ⊤-uniform with countable bases, are equivalent. As an illustration of the applicability concept, we give a fixed point theorem certain contractive self-mappings in space. This result yields, as special case, probabilistic metric spaces.

Probability distributions are central tools for probabilistic modeling in data mining. In functional data analysis (FDA) they are weakly studied in the general case. In this paper we discuss a probability distribution law for functional data considered as stochastic process. We define first a new kind of stationarity linked t o the Archimedean copulas, and then we build a probability distributi...

We derive an asymptotic Newton algorithm for Quasi Maximum Likelihood estimation of the ICA mixture model, using the ordinary gradient and Hessian. The probabilistic mixture framework can accommodate non-stationary environments and arbitrary source densities. We prove asymptotic stability when the source models match the true sources. An application to EEG segmentation is given. Index Terms Ind...

The relativistic Klein-Gordon system is studied as an illustration of Quantum Mechanics using non-Hermitian operators as observables. A version of the model is considered containing a generic coordinateand energy-dependent phenomenological mass-term m(E, x). We show how similar systems may be assigned a pair of the linear, energy-independent leftand right-acting Hamiltonians with quasi-Hermitic...