Observers to the aid of "strictification" of Lyapunov functions (Long version)

Toute utili- sation commerciale ou impression systématique est constitutive d’une infraction pénale.. Toute copie ou impression de ce fichier doit conte- nir la présente mention

The resulting estimator is shown to be adaptive and minimax optimal: we establish nonasymptotic risk bounds and compute rates of convergence under various assumptions on the decay

Our main tool for estimating the discrepancy of a sequence is the inequality of Erdos-Turan-Koksma ([6], cf. - The left-hand side is equal to sin 2irt.. the first lines of the proof

We construct a canonical projection (which turns out to be continuous) from the shift space of an IIFS on its attractor and provide sufficient conditions for this function to be

Since the design of (memoryless) homogeneous continu- ous or discontinuous feedback controllers using the Implicit Lyapunov Function (ILF) method [6] greatly simplifies the gain

Exponential stability, based on Lyapunov functions with discontinuity at the impulses, is proposed by [9] for nonlinear time-varying impulsive systems but the stability conditions

We show that under suitable conditions, consisting of strict dissipativity, the turnpike property and appropriate continuity properties, a practical Lyapunov function exists for the

For ES levels close to one (between 0.5 and 1.5), the specification (29) in level gives a pretty good approximation of the exact CES function (24) with no visual difference (see