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» Modelling Complex Events with Event-Driven Process Chains
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APVIS
2009
15 years 26 days ago
Visualization of signal transduction processes in the crowded environment of the cell
In this paper, we propose a stochastic simulation to model and analyze cellular signal transduction. The high number of objects in a simulation requires advanced visualization tec...
Martin Falk, Michael Klann, Matthias Reuss, Thomas...
CPE
2003
Springer
149views Hardware» more  CPE 2003»
15 years 5 months ago
Logical and Stochastic Modeling with SMART
We describe the main features of SmArT, a software package providing a seamless environment for the logic and probabilistic analysis of complex systems. SmArT can combine differen...
Gianfranco Ciardo, R. L. Jones III, Andrew S. Mine...
ICARCV
2008
IEEE
170views Robotics» more  ICARCV 2008»
15 years 6 months ago
Mixed state estimation for a linear Gaussian Markov model
— We consider a discrete-time dynamical system with Boolean and continuous states, with the continuous state propagating linearly in the continuous and Boolean state variables, a...
Argyris Zymnis, Stephen P. Boyd, Dimitry M. Gorine...
VALUETOOLS
2006
ACM
164views Hardware» more  VALUETOOLS 2006»
15 years 5 months ago
Analysis of Markov reward models using zero-suppressed multi-terminal BDDs
High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
Kai Lampka, Markus Siegle
IPSN
2004
Springer
15 years 5 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal