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The logarithmic triplet theory with boundary
, 2006
"... The boundary theory for the c = −2 triplet model is investigated in detail. In particular, we show that there are four different boundary conditions that preserve the triplet algebra, and check the consistency of the corresponding boundary operators by constructing their OPE coefficients explicitly. ..."
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Cited by 35 (4 self)
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The boundary theory for the c = −2 triplet model is investigated in detail. In particular, we show that there are four different boundary conditions that preserve the triplet algebra, and check the consistency of the corresponding boundary operators by constructing their OPE coefficients explicitly
An algebraic approach to logarithmic Conformal Field Theory
 LECTURES GIVEN AT THE SCHOOL ON LOGARITHMIC CONFORMAL FIELD THEORY AND ITS APPLICATIONS, IPM
, 2001
"... A comprehensive introduction to logarithmic conformal field theory, using an algebraic point of view, is given. A number of examples are explained in detail, including the c = −2 triplet theory and the k = −4/3 affine su(2) theory. We also give some brief introduction to the work of Zhu. ..."
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Cited by 107 (3 self)
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A comprehensive introduction to logarithmic conformal field theory, using an algebraic point of view, is given. A number of examples are explained in detail, including the c = −2 triplet theory and the k = −4/3 affine su(2) theory. We also give some brief introduction to the work of Zhu.
Triplet Markov
"... chains and image segmentation AnumberofMarkovmodelshavebeenshowntoberemarkablyeffective for a variety of modelization problems and treatment of a wide range of phenomena. The use of these models is very much on the increase in economics, finance, genomics, ecology, communications, signal and image p ..."
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chains and image segmentation AnumberofMarkovmodelshavebeenshowntoberemarkablyeffective for a variety of modelization problems and treatment of a wide range of phenomena. The use of these models is very much on the increase in economics, finance, genomics, ecology, communications, signal and image processing, etc. In particular, hidden Markov models (HMM) are well known for their effectiveness for treating the problem of segmentation, which is among the most prominent and difficult problemsinimage processing. In such a model, the hidden data, which model the desired segmented image, are considered as the realization of a Markov process, which may be a field, a tree or a chain. More generally, HMMs are used to treat other inverse problems in imagery such as noise removal or contour detection – see Chapter 1. The distributionp(x) of the hidden process X, referredtoastheaprioridistribution, can generally be interpreted as a regularization tool for the unobservable image which is being determined. The distribution of Y,conditionalonX,isknownasthedatadrivendistribution.Thus the various extensions to HMM presented in this chapter are even more general tools,
Fusion Rules of the Wp,q Triplet Models
, 2009
"... In this paper we determine the fusion rules of the logarithmic Wp,q triplet theory and construct the Grothendieck group with subgroups for which consistent product structures can be defined. The fusion rules are then used to determine projective covers. This allows us also to write down a candidate ..."
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In this paper we determine the fusion rules of the logarithmic Wp,q triplet theory and construct the Grothendieck group with subgroups for which consistent product structures can be defined. The fusion rules are then used to determine projective covers. This allows us also to write down a candidate
Multisensor triplet Markov chains and theory of evidence
 International Journal of Approximate Reasoning
, 2006
"... Hidden Markov chains (HMC) are widely applied in various problems occurring in different areas like Biosciences, Climatology, Communications, Ecology, Econometrics and Finances, Image or Signal processing. In such models, the hidden process of interest X is a Markov chain, which must be estimated fr ..."
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Cited by 30 (13 self)
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restoration. HMC have been recently generalized to ‘‘Pairwise’ ’ Markov chains (PMC) and ‘‘Triplet’ ’ Markov chains (TMC), which offer similar processing advantages and superior modeling capabilities. In PMC, one directly assumes the Markovianity of the pair (X, Y) and in TMC, the distribution of the pair (X
Cancer Supplement THE TRIPLETS OF
"... Email article A conference considers a theory that blames tumorigenesis on chromosomal gains and losses  By Douglas Steinberg ..."
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Email article A conference considers a theory that blames tumorigenesis on chromosomal gains and losses  By Douglas Steinberg
and doublettriplet splitting
, 2008
"... We propose an attractive scenario of grand unified theories in which doublettriplet splitting is beautifully realized in SO(10) unification using DimopoulosWilczek mechanism. The anomalous U(1)A gauge symmetry plays essential roles in the doublettriplet splitting mechanism. It is interesting that ..."
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We propose an attractive scenario of grand unified theories in which doublettriplet splitting is beautifully realized in SO(10) unification using DimopoulosWilczek mechanism. The anomalous U(1)A gauge symmetry plays essential roles in the doublettriplet splitting mechanism. It is interesting
The N = 1 triplet vertex . . .
, 2008
"... We introduce a new family of C2cofinite N = 1 vertex operator superalgebras SW(m), m ≥ 1, which are natural super analogs of the triplet vertex algebras W(p), p ≥ 2, important in logarithmic conformal field theory. We classify irreducible SW(m)modules and discuss logarithmic modules. We also compu ..."
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We introduce a new family of C2cofinite N = 1 vertex operator superalgebras SW(m), m ≥ 1, which are natural super analogs of the triplet vertex algebras W(p), p ≥ 2, important in logarithmic conformal field theory. We classify irreducible SW(m)modules and discuss logarithmic modules. We also
Results 1  10
of
62,276