6 research outputs found

    A general wavelet-based profile decomposition in the critical embedding of function spaces

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    We characterize the lack of compactness in the critical embedding of functions spaces X⊂YX\subset Y having similar scaling properties in the following terms : a sequence (un)n≄0(u_n)_{n\geq 0} bounded in XX has a subsequence that can be expressed as a finite sum of translations and dilations of functions (ϕl)l>0(\phi_l)_{l>0} such that the remainder converges to zero in YY as the number of functions in the sum and nn tend to +∞+\infty. Such a decomposition was established by G\'erard for the embedding of the homogeneous Sobolev space X=H˙sX=\dot H^s into the Y=LpY=L^p in dd dimensions with 0<s=d/2−d/p0<s=d/2-d/p, and then generalized by Jaffard to the case where XX is a Riesz potential space, using wavelet expansions. In this paper, we revisit the wavelet-based profile decomposition, in order to treat a larger range of examples of critical embedding in a hopefully simplified way. In particular we identify two generic properties on the spaces XX and YY that are of key use in building the profile decomposition. These properties may then easily be checked for typical choices of XX and YY satisfying critical embedding properties. These includes Sobolev, Besov, Triebel-Lizorkin, Lorentz, H\"older and BMO spaces.Comment: 24 page
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