Results 241 to 250 of about 5,568,459 (279)
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Vector Associative Memory Models
Automation and Remote Control, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kryzhanovskij, B. V., Litinskij, L. B.
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IFAC Proceedings Volumes, 2001
Abstract This paper introduces a class of nonlinear discrete-time dynamic models that generalize familiar linear model structures; our motivation is to explore the degree to which known results for the linear case do or do not extend to this nonlinear class.
R.K. Pearson, Ü. Kotta
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Abstract This paper introduces a class of nonlinear discrete-time dynamic models that generalize familiar linear model structures; our motivation is to explore the degree to which known results for the linear case do or do not extend to this nonlinear class.
R.K. Pearson, Ü. Kotta
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Surfaces Associated with Sigma Models
Studies in Applied Mathematics, 2006We present a unified method of construction of surfaces associated with Grassmannian sigma models, expressed in terms of an orthogonal projector. This description leads to compact formulae for structural equations of two‐dimensional surfaces immersed in thesu(N) algebra.
Grundland, A. M., Šnobl, L.
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Computational models of association cortex
Current Opinion in Neurobiology, 2000Recent computational models, or mathematical realizations of neurobiological theories, are providing insights into the organization and workings of the association cortex. Such models concern the construction of cortical maps, the neural basis of cognitive functions such as visual perception, reward-motivated learning and some aspects of consciousness.
T, Gisiger, S, Dehaene, J P, Changeux
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Association Models for Web Mining
Data Mining and Knowledge Discovery, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
GIUDICI, PAOLO STEFANO, CASTELO R.
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Multidimensional Association Models
Sociological Methods & Research, 2001This article develops several multidimensional multilinear association models for sociologists and other social science researchers to analyze the relationship between categorical variables in multiway cross-classification tables. The proposed multilinear approach not only provides satisfactory fit by conventional standards in the illustrative ...
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Log-Multiplicative Association Models as Item Response Models
Psychometrika, 2007Log-multiplicative association (LMA) models, which are special cases of log-linear models, have interpretations in terms of latent continuous variables. Two theoretical derivations of LMA models based on item response theory (IRT) arguments are presented.
Anderson, Carolyn J., Yu, Hsiu-Ting
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2017
In this work, the authors develop signaling models based on ideas from homology and discuss how to design a model of signal space which decomposes the incoming signals into classes of progressively higher levels of associative meaning. The tools needed are illustrated with a simple approach using standard linear algebra processing but this is just a ...
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In this work, the authors develop signaling models based on ideas from homology and discuss how to design a model of signal space which decomposes the incoming signals into classes of progressively higher levels of associative meaning. The tools needed are illustrated with a simple approach using standard linear algebra processing but this is just a ...
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HIV-Associated Nephropathy: Experimental Models
2011Since 1984 reports of renal involvement in AIDS patients have been presented in the literature. Different forms of renal disease were noted in the AIDS population including those related to systemic and local renal infections, tubulointerstitial disease, renal involvement by neoplasm and glomerular disease including collapsing glomerulopathy (CG).
Carmen, Avila-Casado +2 more
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Quantile Association Regression Models
Journal of the American Statistical Association, 2014It is often important to study the association between two continuous variables. In this work, we propose a novel regression framework for assessing conditional associations on quantiles. We develop general methodology which permits covariate effects on both the marginal quantile models for the two variables and their quantile associations.
Ruosha Li, Yu Cheng, Jason P. Fine
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