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» Combining Simple Models to Approximate Complex Dynamics
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CVPR
2000
IEEE
14 years 9 months ago
Impact of Dynamic Model Learning on Classification of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and analysis of figure motion has employed eith...
Vladimir Pavlovic, James M. Rehg
JUCS
2007
107views more  JUCS 2007»
13 years 7 months ago
Genetic Algorithm Based Recurrent Fuzzy Neural Network Modeling of Chemical Processes
: A genetic algorithm (GA) based recurrent fuzzy neural network modeling method for dynamic nonlinear chemical process is presented. The dynamic recurrent fuzzy neural network (RFN...
Jili Tao, Ning Wang, Xuejun Wang
CVPR
2006
IEEE
14 years 9 months ago
Dynamics Based Robust Motion Segmentation
In this paper we consider the problem of segmenting multiple rigid motions using multi?frame point correspondence data. The main idea of the method is to group points according to...
Roberto Lublinerman, Mario Sznaier, Octavia I. Cam...
BMCBI
2006
138views more  BMCBI 2006»
13 years 7 months ago
Approximation properties of haplotype tagging
Background: Single nucleotide polymorphisms (SNPs) are locations at which the genomic sequences of population members differ. Since these differences are known to follow patterns,...
Staal A. Vinterbo, Stephan Dreiseitl, Lucila Ohno-...
WSC
2004
13 years 9 months ago
Stochastic Approximation with Simulated Annealing as an Approach to Global Discrete-Event Simulation Optimization
This paper explores an approach to global, stochastic, simulation optimization which combines stochastic approximation (SA) with simulated annealing (SAN). SA directs a search of ...
Matthew H. Jones, K. Preston White