7 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

    Concentration analysis and cocompactness

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    Loss of compactness that occurs in may significant PDE settings can be expressed in a well-structured form of profile decomposition for sequences. Profile decompositions are formulated in relation to a triplet (X,Y,D)(X,Y,D), where XX and YY are Banach spaces, X↪YX\hookrightarrow Y, and DD is, typically, a set of surjective isometries on both XX and YY. A profile decomposition is a representation of a bounded sequence in XX as a sum of elementary concentrations of the form gkwg_kw, gk∈Dg_k\in D, w∈Xw\in X, and a remainder that vanishes in YY. A necessary requirement for YY is, therefore, that any sequence in XX that develops no DD-concentrations has a subsequence convergent in the norm of YY. An imbedding X↪YX\hookrightarrow Y with this property is called DD-cocompact, a property weaker than, but related to, compactness. We survey known cocompact imbeddings and their role in profile decompositions

    Compactly supported frames for spaces of distributions associated with nonnegative self-adjoint operators

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