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AMC
2008
99views more  AMC 2008»
13 years 10 months ago
Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
Roderick V. N. Melnik
CDC
2008
IEEE
111views Control Systems» more  CDC 2008»
13 years 11 months ago
A Hamiltonian approximation method for the reduction of controlled systems
Abstract-- This paper considers the problem of model reduction for controlled systems. The paper considers a dual/adjoint formulation of the general optimization problem to minimiz...
Siep Weiland
ICCV
1999
IEEE
14 years 11 months ago
A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and synthesizing figure motion has employed eit...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Ke...
ISBI
2004
IEEE
14 years 10 months ago
Covariance of Kinetic Parameter Estimators Based on Time Activity Curve Reconstructions: Preliminary Study on 1D Dynamic Imaging
We provide approximate expressions for the covariance matrix of kinetic parameter estimators based on time activity curve (TAC) reconstructions when TACs are modeled as a linear c...
Sangtae Ahn, Jeffrey A. Fessler, Thomas E. Nichols...
TIP
2008
134views more  TIP 2008»
13 years 9 months ago
Higher Order SVD Analysis for Dynamic Texture Synthesis
Videos representing flames, water, smoke, etc. are often defined as dynamic textures: "textures" because they are characterized by redundant repetition of a pattern and &...
Roberto Costantini, Luciano Sbaiz, Sabine Süs...