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» Dependence Modeling for Stochastic Simulation
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IJCNN
2007
IEEE
15 years 11 months ago
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks
— A single biological neuron is able to perform complex computations that are highly nonlinear in nature, adaptive, and superior to the perceptron model. A neuron is essentially ...
Manish Saggar, Tekin Meriçli, Sari Andoni, ...
WSC
2007
15 years 7 months ago
Ant-based approach for determining the change of measure in importance sampling
Importance Sampling is a potentially powerful variance reduction technique to speed up simulations where the objective depends on the occurrence of rare events. However, it is cru...
Poul E. Heegaard, Werner Sandmann
ICCD
2005
IEEE
108views Hardware» more  ICCD 2005»
16 years 1 months ago
Methods for Modeling Resource Contention on Simultaneous Multithreading Processors
Simultaneous multithreading (SMT) seeks to improve the computation throughput of a processor core by sharing primary resources such as functional units, issue bandwidth, and cache...
Tipp Moseley, Dirk Grunwald, Joshua L. Kihm, Danie...
PRESENCE
2007
167views more  PRESENCE 2007»
15 years 4 months ago
TimbreFields: 3D Interactive Sound Models for Real-Time Audio
We describe a methodology for Virtual Reality designers to capture and resynthesize the variations in sound made by objects when we interact with them through contact such as touc...
Richard Corbett, Kees van den Doel, John E. Lloyd,...
ICIP
2009
IEEE
15 years 2 months ago
Modeling of image shutters and motion blur in analog and digital camera systems
For motion imaging the perceived smoothness of a sequence highly depends on motion blur. The exposure for each frame is started and ended with a shutter mechanism. There are diffe...
Michael Schöberl, Siegfried Fößel,...