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ISTCS
1993
Springer
14 years 24 days ago
Analog Computation Via Neural Networks
We pursue a particular approach to analog computation, based on dynamical systems of the type used in neural networks research. Our systems have a xed structure, invariant in time...
Hava T. Siegelmann, Eduardo D. Sontag
ESANN
2004
13 years 10 months ago
Computational model of amygdala network supported by neurobiological data
Abstract. The amygdala has repeatedly been involved in the processing of emotional reactions and conditioning. This paper presents a neurobiologically inspired computational model ...
Mélanie Falgairolle, Agnès Gorge, Je...
JCPHY
2011
133views more  JCPHY 2011»
12 years 11 months ago
A Riemann solver for single-phase and two-phase shallow flow models based on relaxation. Relations with Roe and VFRoe solvers
We present a Riemann solver derived by a relaxation technique for classical single-phase shallow flow equations and for a two-phase shallow flow model describing a mixture of so...
Marica Pelanti, François Bouchut, Anne Mang...
ROMAN
2007
IEEE
134views Robotics» more  ROMAN 2007»
14 years 3 months ago
Learning Reward Modalities for Human-Robot-Interaction in a Cooperative Training Task
—This paper proposes a novel method of learning a users preferred reward modalities for human-robot interaction through solving a cooperative training task. A learning algorithm ...
Anja Austermann, Seiji Yamada
FS
2011
168views more  FS 2011»
13 years 5 days ago
Gamma expansion of the Heston stochastic volatility model
Abstract We derive an explicit representation of the transitions of the Heston stochastic volatility model and use it for fast and accurate simulation of the model. Of particular i...
Paul Glasserman, Kyoung-Kuk Kim