Add to ORKGNumerical simulation is used more and more frequently in the analysis of physical phenomena. A simulation requires several phases. The first phase consists of constructing a physical model based on the results of experimenting with the phenomena. Next, the physical model is approximated by a mathematical model. Generally, th
A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also ...
[[abstract]]An algorithm for numerical simulation, based on stochastic quantization, is presented. R...
The stochastic simulation algorithm (SSA) was introduced by Gillespie and in a different form by Kur...
International audienceStochastic arithmetic enables one to estimate round-off error propagation usin...
International audienceStochastic arithmetic has been developed as amodel for exact computing with im...
Sampling-based computational methods have become a fundamental part of the numerical toolset of prac...
With the development of ever more powerful computers a new branch of physics and engineering evolved...
Digitally generated solutions of nonlinear stochastic systems are not unique, but depend critically ...
Ross's Simulation, Fourth Edition introduces aspiring and practicing actuaries, engineers, computer ...
In these lecture notes we will work through three different computational problems from different ap...
Mathematical Modeling describes a process and an object by use of the mathematical language. A proce...
The sequential use of random numbers, to sample the values of probability variables, allows obtainin...
Much research in control systems is purely mathematical, but advances in stochastic control problem ...
Mathematical and Computational Models developed are innovative outcomes of interdisciplinary researc...
International audienceStochastic computational modelsare used to simulate complex physical or biolog...
A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also ...
[[abstract]]An algorithm for numerical simulation, based on stochastic quantization, is presented. R...
The stochastic simulation algorithm (SSA) was introduced by Gillespie and in a different form by Kur...
International audienceStochastic arithmetic enables one to estimate round-off error propagation usin...
International audienceStochastic arithmetic has been developed as amodel for exact computing with im...
Sampling-based computational methods have become a fundamental part of the numerical toolset of prac...
With the development of ever more powerful computers a new branch of physics and engineering evolved...
Digitally generated solutions of nonlinear stochastic systems are not unique, but depend critically ...
Ross's Simulation, Fourth Edition introduces aspiring and practicing actuaries, engineers, computer ...
In these lecture notes we will work through three different computational problems from different ap...
Mathematical Modeling describes a process and an object by use of the mathematical language. A proce...
The sequential use of random numbers, to sample the values of probability variables, allows obtainin...
Much research in control systems is purely mathematical, but advances in stochastic control problem ...
Mathematical and Computational Models developed are innovative outcomes of interdisciplinary researc...
International audienceStochastic computational modelsare used to simulate complex physical or biolog...
A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also ...
[[abstract]]An algorithm for numerical simulation, based on stochastic quantization, is presented. R...
The stochastic simulation algorithm (SSA) was introduced by Gillespie and in a different form by Kur...