Approximating integrals with respect to stationary probability measures of iterated function systems
نویسندگان
چکیده
منابع مشابه
Rigorous Approximation of Stationary Measures for Iterated Function Systems
We study the problem of the rigorous computation of the stationary measure of an IFS described by a stochastic mixture of two or more dynamical systems which are either all uniformly expanding on the interval, either all contractive. In the expanding case, the associated transfer operators satisfy a LasotaYorke inequality, and we compute rigorously the approximations in the L1 norm. The rigorou...
متن کاملApproximating distribution functions by iterated function systems
In this small note an iterated function system on the space of distribution functions is built. The inverse problem is introduced and studied by convex optimization problems. Applications of this method to approximation of distribution functions and estimation are presented. Résumé. Dans cette petite note un système de fonction itéré sur l’espace de fonctions de repartition est construit. Le pr...
متن کاملa comparison of teachers and supervisors, with respect to teacher efficacy and reflection
supervisors play an undeniable role in training teachers, before starting their professional experience by preparing them, at the initial years of their teaching by checking their work within the proper framework, and later on during their teaching by assessing their progress. but surprisingly, exploring their attributes, professional demands, and qualifications has remained a neglected theme i...
15 صفحه اولA family of measures associated with iterated function systems
Let (X, d) be a compact metric space, and let an iterated function system (IFS) be given on X, i.e., a finite set of continuous maps σi: X → X, i = 0, 1, · · · , N − 1. The maps σi transform the measures μ on X into new measures μ i . If the diameter of σi1 ◦ · · · ◦ σik (X) tends to zero as k → ∞, and if pi > 0 satisfies ∑ i pi = 1, then it is known that there is a unique Borel probability mea...
متن کاملLearning Probability Measures with respect to Optimal Transport Metrics
We study the problem of estimating, in the sense of optimal transport metrics, a measure which is assumed supported on a manifold embedded in a Hilbert space. By establishing a precise connection between optimal transport metrics, optimal quantization, and learning theory, we derive new probabilistic bounds for the performance of a classic algorithm in unsupervised learning (k-means), when used...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Ergodic Theory and Dynamical Systems
سال: 2020
ISSN: 0143-3857,1469-4417
DOI: 10.1017/etds.2020.49