2020
DOI: 10.1088/1361-6544/ab8fb8
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A probabilistic Takens theorem

Abstract: Let X ⊂ R N be a Borel set, μ a Borel probability measure on X and T : X → X a locally Lipschitz and injective map. Fix … Show more

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Cited by 13 publications
(12 citation statements)
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“…The proof is based on the embedding theorem for dim B with Hölder inverse [13,Thm. 4.3] (see [16] for an almost sure embedding theorem for Hausdorff dimension). See [1] for the proof and examples showing that one cannot change the constant 2 1−α to t 1−α for t < 2 and inf L>0 cannot be omitted.…”
Section: Resultsmentioning
confidence: 99%
“…The proof is based on the embedding theorem for dim B with Hölder inverse [13,Thm. 4.3] (see [16] for an almost sure embedding theorem for Hausdorff dimension). See [1] for the proof and examples showing that one cannot change the constant 2 1−α to t 1−α for t < 2 and inf L>0 cannot be omitted.…”
Section: Resultsmentioning
confidence: 99%
“…To prove Theorem 1.7, we will use our previous result from [BGŚ20], which we recall below, using the notion of prevalence described in Subsection 2.2. This is a probabilistic version of the Takens delay embedding theorem, asserting that under suitable conditions on k, there is a prevalent set of Lipschitz observables, which give rise to an almost surely injective k-delay coordinate map.…”
Section: Probabilistic Takens Delay Embedding Theoremmentioning
confidence: 99%
“…Extensions of Takens' work were obtained in several categories, e.g. in [SYC91, Sta99, Cab00, Rob05, Gut16, GQS18, SBDH97, SBDH03, NV20] (see also [Rob11,BGŚ20] for a more detailed overview). A common feature of these results is that the minimal number of measurements sufficient for the exact reconstruction of the system is k ≈ 2 dim X, where dim X is the dimension of the phase space X.…”
mentioning
confidence: 99%
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