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Truncated Hilbert transform and principal value
Definition
Fix and a function , with the conventions of Complex Lp classes and Euclidean test-function conventions. For and define the truncated Hilbert transform
Each truncation is an ordinary Lebesgue integral over the complement of an interval of length around , and it is absolutely convergent. For this follows from the pointwise bound on the domain of integration; for it follows from Hölder's inequality applied to the two half-lines and , where has finite norm, with conjugate to (Complex Holder, Minkowski, and the quotient norm). Changing on a null set changes no integral, so is a well-defined number attached to the class of ; and is itself a measurable function of .
The Hilbert transform in the principal-value sense is defined only where the truncations converge:
whenever this limit exists in . No almost-everywhere existence of this limit, and no bound of in any norm, is asserted by this definition. The definition also does not extend to : for the tail the bound is finite but the integral over an unbounded domain is not controlled, so the truncation of a merely bounded need not converge absolutely at any .
Three distinctions are recorded here for later use. First, is an integral of a truncated singular kernel, while the pairing of a test function with the principal-value distribution of is a separate object; the two agree only under the convergence just defined. Second, the limit is taken symmetrically in about the singularity , and unsymmetric truncations are a different object. Third, is a pointwise partial function, whereas the extension constructed later on this page is a single bounded operator agreeing with where the latter exists on a dense class.
Depends on
Used by
Dependency tree · two levels
26 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Loukas Grafakos, Classical Fourier Analysis, third edition (standard reference, not scraped)