Bounds on the state vector growth rate in stochastic dynamical systems
arXiv:1212.6030h-index: 17
Originality Synthesis-oriented
AI Analysis
Provides theoretical bounds for stochastic dynamical systems, but the contribution is incremental and lacks concrete performance numbers or broad applicability.
The paper proposes simple bounds on the mean growth rate of the state vector in stochastic dynamical systems modeled with idempotent algebra, and analyzes the absolute error of a bound, with numerical results for a test system.
A stochastic dynamical system represented through a linear vector equation in idempotent algebra is considered. We propose simple bounds on the mean growth rate of the system state vector, and give an analysis of absolute error of a bound. As an illustration, numerical results of evaluation of the bounds for a test system are also presented.