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A Class of Lyapunov Functionals for Analyzing Hybrid Dynamical Systems
Lyapunov Functionals Analyzing Hybrid Dynamical Systems
2015/7/10
In this paper, we introduce a new class of Lyapunov functionals for analyzing hybrid dynamical systems. This class can be thought of as a generalization of the Lyapunov functional introduced by Yakubo...
Control of Asynchronous Dynamical Systems with Rate Constraints on Events
Asynchronous dynamical systems Lyapunov theory linear matrix inequality (LMI) bilinear matrix inequality (BMI)
2015/7/10
In this paper we consider dynamical systems which are driven by events that occur asynchronously. It is assumed that the event rates are fixed, or at least they can be bounded on any time period of le...
Shannon Meets Lyapunov: Connections between Information Theory and Dynamical Systems
Shannon Meets Lyapunov Connections between Information Theory Dynamical Systems
2015/7/6
This paper explores connections between Information Theory, Lyapunov exponents for products of random matrices, and hidden Markov models. Specifically, we will show that entropies associated with fini...
Entropic fluctuations in statistical mechanics: I. Classical dynamical systems
Dynamic system theory the steady state the theorem of equilibrium statistical mechanics mathematical structure fluctuation quantum statistical mechanics
2014/12/24
Within the abstract framework of dynamical system theory we describe a general approach to the transient (or Evans–Searles) and steady state (or Gallavotti–Cohen) fluctuation theorems of non-equilibri...
Inverse Modeling of Dynamical Systems: Multi-Dimensional Extensions of a Stochastic Switching Problem
Inverse Modeling of Dynamical Systems Multi-Dimensional Extensions Stochastic Switching Problem
2012/9/18
The Buridan's ass paradox is characterized by perpetual indecision between two states, which are never attained. When this problem is formulated as a dynamical
system, indecision is modeled by a disc...
Expectation Propagation in Gaussian Process Dynamical Systems
Expectation Propagation Gaussian Process Dynamical Systems
2012/9/19
Rich and complex time-series data, such as those generated from engineer-ing systems, financial markets, videos or neural recordings, are now a common feature of modern data analysis. Explaining the p...
Identifying and understanding modular organizations is centrally important in the study of complex systems. Several approaches to this problem have been advanced, many framed in information-theoretic ...
Scalable Bayesian reduced-order models for high-dimensional multiscale dynamical systems
AMS subject classifications
2010/3/9
While existing mathematical descriptions can accurately account for phenomena at
microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and their
applicability ov...
Goodness-of-Fit Tests for Perturbed Dynamical Systems
Cramer-von Mises Kolmogorov-Smirnov and Chi-Square tests diffusion process goodness of fit hypotheses testing
2010/3/19
We consider the goodness of fit testing problem for stochastic differential
equation with small diffusion coefficient. The basic hypothesis
is always simple and it is described by the known trend co...
Estimation for Dynamical Systems with Small Noise from Discrete Observations
discrete time observation dynamical systems with small noise M-estimator parametric inference quadratic martingale estimating function
2009/3/10
We consider an efficient estimation of an unknown parameter appearing in both the drift and the diffusion coefficient for a d-dimensional dynamical system with small noise. Asymptotic properties of an...
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
Approximate Bayesian computation scheme parameter inference model selection dynamical systems
2010/3/17
Approximate Bayesian computation methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper we discuss and apply an approximate Bayesian computation...