Comportement asymptotique dans l'algorithme de transformée en ondelettes. Lien avec la régularité de l'ondelette
Let be a Markov kernel on a measurable space with countably generated -algebra, let :→[1, +∞[ such that ≤ with ≥0, and let be the space of measurable functions on satisfying ‖‖=sup{()|()|, ∈}<+∞. We prove that is quasi-compact on if and only if, for all , contains a subsequence converging in to=∑ () , where the ’s are non-negative bounded measurable functions on and the ’s are probability...
Soit une probabilité de transition sur un espace mesurable , admettant une probabilité invariante, soit ( ) une chaîne de Markov associée à , et soit une fonction réelle mesurable sur , et =∑ ( ). Sous des hypothèses fonctionnelles sur l’action de et des noyaux de Fourier (), nous étudions la vitesse de convergence dans le théorème limite central pour la suite . Selon les hypothèses nous obtenons une vitesse en ...
We study the asymptotic performance for a Wavelets Transform, in particular as a function of the regularity order of the wavelet.
We consider quadrature mirror filters, and the associated wavelet packet transform. Let X = {X} be a stationary signal which has a continuous spectral density . We prove that the 2 signals obtained from X by n iterations of the transform converge to white noises when n → +∞. If is holderian, the convergence rate is exponential.
The Nagaev-Guivarc’h method, via the perturbation operator theorem of Keller and Liverani, has been exploited in recent papers to establish limit theorems for unbounded functionals of strongly ergodic Markov chains. The main difficulty of this approach is to prove Taylor expansions for the dominating eigenvalue of the Fourier kernels. The paper outlines this method and extends it by stating a multidimensional local limit theorem, a one-dimensional Berry-Esseen theorem, a first-order Edgeworth expansion,...
Let be a discrete or continuous-time Markov process with state space where is an arbitrary measurable set. Its transition semigroup is assumed to be additive with respect to the second component, i.e. is assumed to be a Markov additive process. In particular, this implies that the first component is also a Markov process. Markov random walks or additive functionals of a Markov process are special instances of Markov additive processes. In this paper, the process is shown to satisfy the...
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