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The Concept of a Linguistic Variable and its Application to Approximate Reasoning
 Journal of Information Science
, 1975
"... By a linguistic variable we mean a variable whose values are words or sentences in a natural or artificial language. I:or example, Age is a linguistic variable if its values are linguistic rather than numerical, i.e., young, not young, very young, quite young, old, not very oldand not very young, et ..."
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Cited by 1430 (9 self)
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, etc., rather than 20, 21, 22, 23, In more specific terms, a linguistic variable is characterized by a quintuple (&?, T(z), U, G,M) in which &? is the name of the variable; T(s) is the termset of2, that is, the collection of its linguistic values; U is a universe of discourse; G is a syntactic
A Neural Probabilistic Language Model
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2003
"... A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dimensionality: a word sequence on which the model will be tested is likely to be different from all the word sequences seen ..."
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Cited by 447 (19 self)
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training sentence to inform the model about an exponential number of semantically neighboring sentences. The model learns simultaneously (1) a distributed representation for each word along with (2) the probability function for word sequences, expressed in terms of these representations. Generalization
The Determinants of Credit Spread Changes.
 Journal of Finance
, 2001
"... ABSTRACT Using dealer's quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are ..."
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Cited by 422 (2 self)
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rates, r 10 t . To capture potential nonlinear effects due to convexity, we also include the squared level of the term structure, (r 10 t ) 2 . Slope of Yield Curve We define the slope of the yield curve as the difference between Datastream's 10year and 2year Benchmark Treasury yields, slope
Vertex component analysis: A fast algorithm to unmix hyperspectral data
 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
, 2005
"... Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for ..."
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Cited by 193 (16 self)
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for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: 1) the endmembers are the vertices of a simplex and 2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA
Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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of the object. Formally this is done simply by removing the corresponding column in the sensitivity matrix and setting the excluded pixel to zero in the final image. Knowledge of which voxels may safely be excluded is obtained as a byproduct of sensitivity assessment. In Eq. [2] receiver noise levels
Fredholm Determinants, Differential Equations and Matrix Models
 COMMUNICATIONS IN MATHEMATICAL PHYSICS
, 1994
"... Orthogonal polynomial random matrix models of N x N hermitian matrices lead to Fredholm determinants of integral operators with kernel of the form (φ(x)φ(y) — ψ(x)φ(y))/x — y. This paper is concerned with the Fredholm determinants of integral operators having kernel of this form and where the und ..."
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Cited by 142 (20 self)
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the underlying set is the union of intervals J = [J ™ =1 (βiju Λ 2J) The emphasis is on the determinants thought of as functions of the endpoints a k. We show that these Fredholm determinants with kernels of the general form described above are expressible in terms of solutions of systems of PDE's as long
Whom You Know Matters: Venture Capital Networks and Investment Performance,
 Journal of Finance
, 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm'slength, spotmarket transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
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Cited by 138 (8 self)
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on portfolio company performance. In the absence of companylevel rates of return data, we measure company performance indirectly. In terms of The models shown in The dependent variable in A. The Determinants of Portfolio Company Survival The pseudo R 2 s in We find a significant increasing and at times
Incidence of depression in longterm care settings
 Journal of Gerontology: Medical Sciences
, 1992
"... A oneyear longitudinal study examined incidence and persistence of depression among nursing home and congregate apartment residents. Of 868 persons interviewed at Time 1,15.7 % displayed researchdiagnosed possible major depression, and 16.5 % displayed minor depressive symptoms. A followup interv ..."
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Cited by 6 (0 self)
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, 6.3%. More than 40 % ofTl possible major depressives showed no remission of symptoms a year later. In contrast, more than half of Tl minor depressives showed no depression at T2; however, another 16.2 % appeared at followup to suffer possible major depression. Change in depression was associated
Anonymous Hierarchical IdentityBased Encryption (Without Random Oracles). In: Dwork
 CRYPTO 2006. LNCS,
, 2006
"... Abstract We present an identitybased cryptosystem that features fully anonymous ciphertexts and hierarchical key delegation. We give a proof of security in the standard model, based on the mild Decision Linear complexity assumption in bilinear groups. The system is efficient and practical, with sm ..."
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Cited by 119 (10 self)
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. The game proceeds as follows: Init: The adversary announces the identity Id * it wants to be challenged upon. Setup: The simulator chooses random exponents t 1 , t 2 , t 3 , t 4 , y ∈ Z p . It retains the generator g, and sets g 0 = (g z 1 ) −Id g y and g 1 = g z 1 . The public parameters are published as
Shape Recovery Algorithms Using Level Sets in 2D/3D Medical Imagery: A StateoftheArt Review
, 2001
"... The class of geometric deformable models, socalled level sets, has brought tremendous impact to medical imagery due to its capability to preserve topology and fast shape recovery. In an effort to facilitate a clear and full understanding of these powerful stateoftheart applied mathematical tools ..."
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Cited by 55 (2 self)
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The class of geometric deformable models, socalled level sets, has brought tremendous impact to medical imagery due to its capability to preserve topology and fast shape recovery. In an effort to facilitate a clear and full understanding of these powerful stateoftheart applied mathematical
Results 1  10
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1,567