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The following is a short introduction to Besov spaces and their characterization by means of approximationprocedures as well as wavelet decompositions.

A natural idea for approximating a function f by wavelets is to retain in [link] the N largest contributions in the norm in which we plan to measure the error. In the case wherethis norm is L p , this is given by

A N f : = λ E N , p ( f ) d λ ψ λ ,

where E N , p ( f ) is the set of indices of the N largest d λ ψ λ L p . This set depends on the function f , making this approximation process nonlinear . Other instances of nonlinear approximation are discussed in [link] .

An important result established in [link] states that f - A N f L p N - r / d is achieved for functions f B q , q r where 1 / q = 1 / p + r / d . Note that this relation between p and q corresponds to a critical case of the Sobolev embedding of B q , q r into L p . In particular, B q , q r is not contained in B p , p ε for any ε > 0 , so that no decay rate can be achieved by a linearapproximation process for all the functions f in the space B q , q r . (For some functions in B q , q r , which happen to also lie in spaces for which an independent linear approximation theorem can be written, it isof course possible to get a linear approximation rate; the point here is that this ispossible only via such additional information.)

Note also that for large values of r , the parameter q given by 1 / q = 1 / p + r / d is smaller than 1. In such a situation the space B q , q s is not a Banach space any more and is only a quasi-norm (it fails to satisfythe triangle inequality x + y x + y ). However, this space is still contained in L 1 (by a Sobolev-type embedding) and its characterization by means of wavelets coefficients according tostill holds. Letting q go to zero as r goes to infinity allows the presence of singularities in the functions of B q , q r even when r is large: for example, a function which is piecewise C n on an interval except at a finite number of isolated points of discontinuities belongsto all B q , q r for q < 1 / s and r < n . This is a particular instance where a non-linear approximation process will performsubstantially better than a linear projection.

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Source:  OpenStax, A primer on besov spaces. OpenStax CNX. Sep 09, 2009 Download for free at http://cnx.org/content/col10679/1.2
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