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» Numerical Approximations for Stochastic Differential Games
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ICTAI
2008
IEEE
13 years 11 months ago
The Performance of Approximating Ordinary Differential Equations by Neural Nets
—The dynamics of many systems are described by ordinary differential equations (ODE). Solving ODEs with standard methods (i.e. numerical integration) needs a high amount of compu...
Josef Fojdl, Rüdiger W. Brause
JCNS
1998
134views more  JCNS 1998»
13 years 5 months ago
Analytical and Simulation Results for Stochastic Fitzhugh-Nagumo Neurons and Neural Networks
An analytical approach is presented for determining the response of a neuron or of the activity in a network of connected neurons, represented by systems of nonlinear ordinary stoc...
Henry C. Tuckwell, Roger Rodriguez
HYBRID
2005
Springer
13 years 11 months ago
A Toolbox of Hamilton-Jacobi Solvers for Analysis of Nondeterministic Continuous and Hybrid Systems
Abstract. Hamilton-Jacobi partial differential equations have many applications in the analysis of nondeterministic continuous and hybrid systems. Unfortunately, analytic solution...
Ian M. Mitchell, Jeremy A. Templeton
ICC
2007
IEEE
217views Communications» more  ICC 2007»
13 years 11 months ago
Decentralized Activation in a ZigBee-enabled Unattended Ground Sensor Network: A Correlated Equilibrium Game Theoretic Analysis
Abstract— We describe a decentralized learning-based activation algorithm for a ZigBee-enabled unattended ground sensor network. Sensor nodes learn to monitor their environment i...
Michael Maskery, Vikram Krishnamurthy
CDC
2010
IEEE
105views Control Systems» more  CDC 2010»
13 years 12 days ago
Learning in mean-field oscillator games
This research concerns a noncooperative dynamic game with large number of oscillators. The states are interpreted as the phase angles for a collection of non-homogeneous oscillator...
Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday...