Add to ORKGThe normal approach to digital control is to sample periodically in time. Using an analog of integration theory we can call this Riemann sampling. Lebesgue sampling or event based sampling, is an alternative to Riemann sampling. It means that signals are sam pled only when measurements pass certain limits. In this paper it is shown that Lebesgue sampling gives better performance for some simple systems. 1
The usual justification for talking about signal-to-noise ratio is in terms of a Gaussian model. Thi...
In this paper, we consider nonlinear stochastic systems and intersect ideas from nonlinear control t...
The reduction of the number of samples is a key issue in signal process-ing for mobile applications....
The normal approach to digital control is to sample periodically in time. Using an analog of integra...
The normal approach to digital control is to sample periodically in time. Using an analog of integra...
Sampling is normally done periodically in time. For linear time invariant systems this leads to clos...
International audienceIn this paper, the stabilization of a chain of integrators in the Lebesgue sam...
In this technical note, several issues of periodic and event-based impulse control for a class of se...
In a standard setup of conventional state estimation problems, the output signal of a dynamical syst...
The problem of optimal control for first order stochastic systems with a quadratic performance index...
For systems with limited capacity for storage, processing and transmission of data, the choice of sa...
A rapid progress in intelligent sensing technology creates new interest in a development of analysis...
Physical systems typically evolve continuously whereas modern controllers and signal processing devi...
Sampled-data Models for Linear and Nonlinear Systems provides a fresh new look at a subject with whi...
We consider the problem of finding an event-based sampling scheme that optimizes the trade-off betwe...
The usual justification for talking about signal-to-noise ratio is in terms of a Gaussian model. Thi...
In this paper, we consider nonlinear stochastic systems and intersect ideas from nonlinear control t...
The reduction of the number of samples is a key issue in signal process-ing for mobile applications....
The normal approach to digital control is to sample periodically in time. Using an analog of integra...
The normal approach to digital control is to sample periodically in time. Using an analog of integra...
Sampling is normally done periodically in time. For linear time invariant systems this leads to clos...
International audienceIn this paper, the stabilization of a chain of integrators in the Lebesgue sam...
In this technical note, several issues of periodic and event-based impulse control for a class of se...
In a standard setup of conventional state estimation problems, the output signal of a dynamical syst...
The problem of optimal control for first order stochastic systems with a quadratic performance index...
For systems with limited capacity for storage, processing and transmission of data, the choice of sa...
A rapid progress in intelligent sensing technology creates new interest in a development of analysis...
Physical systems typically evolve continuously whereas modern controllers and signal processing devi...
Sampled-data Models for Linear and Nonlinear Systems provides a fresh new look at a subject with whi...
We consider the problem of finding an event-based sampling scheme that optimizes the trade-off betwe...
The usual justification for talking about signal-to-noise ratio is in terms of a Gaussian model. Thi...
In this paper, we consider nonlinear stochastic systems and intersect ideas from nonlinear control t...
The reduction of the number of samples is a key issue in signal process-ing for mobile applications....