2010
DOI: 10.1007/s11202-010-0025-4
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Interpolation of nonlinear operators in weighted L p -spaces

Abstract: We show that Peetre's classical interpolation theorem in weighted L p -spaces is carried over to some classes of nonlinear operators containing in particular the Lipschitz operators and operators close to them in the properties satisfying less restrictive conditions than Lipschitz in each of the spaces of a Banach pair.

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Cited by 2 publications
(3 citation statements)
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“…It is shown in [4] that if x is a finitary vector, then the obtained estimate for K-functionals implies the required interpolation inequality for the operator T . Hence, as was done above, we pass to an estimate on the cone that approximates Q ∩ E + and consists of finitary vectors.…”
Section: Then the Family Of Triples Of Conesmentioning
confidence: 91%
See 1 more Smart Citation
“…It is shown in [4] that if x is a finitary vector, then the obtained estimate for K-functionals implies the required interpolation inequality for the operator T . Hence, as was done above, we pass to an estimate on the cone that approximates Q ∩ E + and consists of finitary vectors.…”
Section: Then the Family Of Triples Of Conesmentioning
confidence: 91%
“…It is shown in [4] that the above estimate for K-functionals implies the following interpolation inequality:…”
Section: Then the Family Of Triples Of Conesmentioning
confidence: 95%
“…Differently from interpolation methods in spaces of finite dimension (e.g., d-dimensional Euclidean spaces), interpolation here is in a space of functions, i.e., the interpolation nodes θ k (x) are functions in a Hilbert or a Banach space. Over the years, the problem of constructing a functional interpolant through suitable nodes in Hilbert or Banach spaces has been studied by several authors and convergence results were established in rather general cases [134,103,183,178,99,4,106,104,179,216]. Before discussing functional interpolation in detail, let us provide some geometric intuition on what functional interpolation is and what kind of representations we should expect.…”
Section: Functional Interpolation Methodsmentioning
confidence: 99%