2017
DOI: 10.1016/j.jmaa.2017.02.012
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Topological invariants and Lipschitz equivalence of fractal squares

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Cited by 33 publications
(25 citation statements)
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“…4. By a result of Whyburn [23], they are homeomorphic, and [21] conjectures these two fractal squares are not Lipschitz equivalent (see also [17]). To show two sets are not Lipschitz equivalent, the main method is to construct a certain Lipschitz invariant to distinct them.…”
Section: E Fmentioning
confidence: 99%
See 1 more Smart Citation
“…4. By a result of Whyburn [23], they are homeomorphic, and [21] conjectures these two fractal squares are not Lipschitz equivalent (see also [17]). To show two sets are not Lipschitz equivalent, the main method is to construct a certain Lipschitz invariant to distinct them.…”
Section: E Fmentioning
confidence: 99%
“…A non-empty compact set satisfying the set equation F = ∪ d∈D F+d n is called a fractal square if n ≥ 2 and D ⊂ {0, 1, • • • , n − 1} 2 . Ruan and Wang [21] studied fractal squares of ratio 1/3 and with 7 or 8 branches, which are all connected fractals. Their method is to find various connectivity properties, which depend on very careful observations.…”
Section: Introductionmentioning
confidence: 99%
“…There are several works devoted to the Lipschitz classification of non-totally disconnected fractal squares with contraction ratio 1/3, that is, a kind of Sierpinski carpets ( [10,13,17,23]), but the problem is unsolved in case of the fractal squares with 5 branches. Using neighbor automaton, Rao-Zhu [16] proved that F 1 F 2 in Figure 1, but it is not known whether F j , j = 2, 3, 4, 5 are Lipschitz equivalent or homeomorphic.…”
Section: Introductionmentioning
confidence: 99%
“…Rao, Ruan and Xi [22] gave an affirmative answer to this question by introducing the graph‐directed technique to prove certain self‐similar sets being Lipschitz equivalence. Although considerable efforts [5, 10, 15–18, 20–25, 27–38] have been made in the study of this issue, it is still a long way to understand the Lipschitz equivalence of self‐similar sets.…”
Section: Introductionmentioning
confidence: 99%