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» Parametrization of Linear Systems Using Diffusion Kernels
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ICML
2006
IEEE
14 years 11 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
IPPS
1998
IEEE
14 years 3 months ago
Processor Lower Bound Formulas for Array Computations and Parametric Diophantine Systems
Using a directed acyclic graph (dag) model of algorithms, we solve a problem related to precedenceconstrained multiprocessor schedules for array computations: Given a sequence of ...
Peter R. Cappello, Ömer Egecioglu
ICIP
2005
IEEE
15 years 15 days ago
The impulse responses of block shift-invariant systems and their use for demosaicing algorithms
Shift-invariant linear algorithms can be described completely by the algorithm's response to an impulse input. The so called impulse response can be used as filter kernels wh...
Yacov Hel-Or
MICCAI
2010
Springer
13 years 8 months ago
Biomarkers for Identifying First-Episode Schizophrenia Patients Using Diffusion Weighted Imaging
Recent advances in diffusion weighted MR imaging (dMRI) has made it a tool of choice for investigating white matter abnormalities of the brain and central nervous system. In this w...
Yogesh Rathi, James G. Malcolm, Oleg V. Michailovi...
NPAR
2010
ACM
14 years 3 months ago
Diffusion constraints for vector graphics
The formulation of Diffusion Curves [Orzan et al. 2008] allows for the flexible creation of vector graphics images from a set of curves and colors: a diffusion process fills out...
Hedlena Bezerra, Elmar Eisemann, Doug DeCarlo, Jo&...