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» Reconstructing Boolean Models of Signaling
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CDC
2010
IEEE
144views Control Systems» more  CDC 2010»
14 years 4 months ago
Semiparametric identification of Hammerstein systems using input reconstruction and a single harmonic input
We present a two-step method for identifying SISO Hammerstein systems. First, using a persistent input with retrospective cost optimization, we estimate a parametric model of the l...
Anthony M. D'Amato, Kenny S. Mitchell, Bruno Ot&aa...
ICASSP
2009
IEEE
15 years 4 months ago
Bounded conditional mean imputation with Gaussian mixture models: A reconstruction approach to partly occluded features
In this work we show how conditional mean imputation can be bounded through the use of box-truncated Gaussian distributions. That is of interest when signals or features are partl...
Friedrich Faubel, John W. McDonough, Dietrich Klak...
CGF
2010
132views more  CGF 2010»
14 years 9 months ago
Hybrid Booleans
In this paper we present a novel method to compute Boolean operations on polygonal meshes. Given a Boolean expression over an arbitrary number of input meshes we reliably and effi...
Darko Pavic, Marcel Campen, Leif Kobbelt
ICASSP
2011
IEEE
14 years 1 months ago
Parameter estimation using sparse reconstruction with dynamic dictionaries
We consider the problem of parameter estimation for signals characterized by sums of parameterized functions. We present a dynamic dictionary subset selection approach to paramete...
Christian D. Austin, Joshua N. Ash, Randolph L. Mo...
GECCO
2006
Springer
172views Optimization» more  GECCO 2006»
15 years 1 months ago
Evolving boolean networks to find intervention points in dengue pathogenesis
We use probabilistic boolean networks to simulate the pathogenesis of Dengue Hemorraghic Fever (DHF). Based on Chaturvedi's work, the strength of cytokine influences are mode...
Philip Tan, Joc Cing Tay