Publications associées à Modeling Compositions of Impedance-based Primitives via Dynamical Systems.

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Singularly perturbed piecewise deterministic games

Alain Haurie

In this paper we consider a class of hybrid stochastic games with the piecewise open-loop information structure. These games are indexed over a parameter

\varepsilon

which represents the time scale ratio between the stochastic (jump process) and the dete ...

Society for Industrial and Applied Mathematics2008

Modeling Compositions of Impedance-based Primitives via Dynamical Systems.

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Dynamical system for learning the waveform and frequency of periodic signals - application to drumming

Singularly perturbed piecewise deterministic games

Adaptive Fine-Tuning for Large-Scale Complex Nonlinear Systems

Dynamic simulation of regulatory networks using SQUAD

Uncovering the topology of configuration space networks

Engineering limit cycle systems

Generalization of the RIN Result to Heterogeneous Networks of Aggregate Schedulers and Leaky Bucket Constrained Flows

Generalization of the RIN result to heterogeneous networks of aggregate schedulers and leaky bucket constrained flows

Linking Policy Research and Practice in 'STIG Systems': Many Obstacles, but Some Ways Forward

Finding the distance to instability of a large sparse matrix

Engineering limit cycle systems

Adaptive Fine-Tuning for Large-Scale Complex Nonlinear Systems

Dynamical system for learning the waveform and frequency of periodic signals - application to drumming

Singularly perturbed piecewise deterministic games

Generalization of the RIN result to heterogeneous networks of aggregate schedulers and leaky bucket constrained flows

Uncovering the topology of configuration space networks

Dynamic simulation of regulatory networks using SQUAD

Generalization of the RIN Result to Heterogeneous Networks of Aggregate Schedulers and Leaky Bucket Constrained Flows

Linking Policy Research and Practice in 'STIG Systems': Many Obstacles, but Some Ways Forward

Finding the distance to instability of a large sparse matrix