Use the Fourier transform convention . An orthonormal multiresolution analysis is a family of closed vector subspaces , indexed by integers, with , , and . Its dilation condition is if and only if . The space is invariant under integer function translations and admits a scaling function whose integer function translations form an orthonormal basis. Consequently form an orthonormal basis of .
Since , expansion in that orthonormal basis gives the scaling refinement equationThe series converges in the L2 norm. The associated low-pass filter of a multiresolution analysis is the periodic Fourier series symbolInitially the symbol is defined almost everywhere. Orthonormal integer function translations give the quadrature mirror filter identity almost everywhere. For a Lebesgue integrable scaling function, its Fourier transform is continuous and ; choosing a constant phase makes and the continuous representative near zero has . Different conventions absorb into the refinement coefficients; the displayed convention fixes that ambiguity.
Let denote the orthogonal complement of inside . The Meyer-Mallat theorem constructs a wavelet whose integer function translations form an orthonormal basis of . Dilation then gives the orthogonal decomposition into orthogonal complements , so its translates and dilates form an orthonormal wavelet basis.
Using the MRA low-pass filter, choose the high-pass symbol . The quadrature mirror filter identity makes the two analysis channels orthonormal. The resulting Fourier transform formula isEquivalently, with the refinement coefficients from the scaling refinement equation, put and . This index choice gives precisely the displayed high-pass symbol. Changing all by one constant unit phase gives the same orthonormal wavelet construction. In particular the often-used convention differs only by a global minus sign. The basis is for .
A wavelet with vanishing moments satisfies and for . The moment differentiation of the Fourier transform theorem states that these weighted integrability hypotheses make , with . Hence . The MRA projection Fourier identity, together with density of the approximation spaces and continuity of at zero, gives . These are the two analytic theorems needed in addition to the quadrature mirror filter construction.
For the ordinary derivative conclusion, assume also that the MRA low-pass filter is near and is near zero. These hypotheses hold, for example, for a compactly supported scaling function with a finite refinement filter. The wavelet identity givesThe denominator is nonzero near zero. Its reciprocal and the exponential are , so the product rule and the zero Taylor polynomial of give the smooth-mask vanishing-moment criterion
The printed integrability hypothesis alone does not guarantee ordinary higher derivatives. It gives only a continuous . Without added smoothness, Taylor theorem for still gives for the representative defined by the quotient: a Peano zero. This establishes the value at , and for the first derivative there, but it does not automatically establish iterated derivatives.
Here is a lacunary scaling-phase regularity counterexample for . Start with a compactly supported Daubechies wavelet having vanishing moments, with scaling function and finite MRA low-pass filter . Define the periodic phaseThe Fourier coefficients of are absolutely summable. The Wiener algebra is closed under multiplication and the exponential series, so and have absolutely summable Fourier coefficients. Thus is an absolutely summable combination of integer function translations of , belongs to , and generates the same . Unimodularity preserves orthogonality and unit norm of its integer function translations; the inverse phase preserves their complete span. The same approximation spaces therefore give a multiresolution analysis.
The identity gives , so the periodic phase change of a scaling function produces . In the high-pass formula the phases cancel:The associated wavelet is therefore exactly the original one, with unchanged vanishing moments.
At any dyadic point , the difference quotient of the terms with is per term. The sum of these errors and the remaining tail divided by are bounded; the finitely many earlier terms have finite limits. Hence , which has no finite limit. The exponential has the same failure of differentiability. Dyadic points are dense, and is nonzero for sufficiently small . Thus is not differentiable on any neighborhood of , so an ordinary second derivative at , understood as the derivative of a locally defined first derivative, need not exist. The Peano zero remains valid. This separates the intended smooth-mask theorem from what the literal assumptions establish.
Under the smoothness hypotheses in the smooth-mask vanishing-moment criterion, write any nonzero integer as , where and is odd, possibly negative. Iterating the scaling refinement equation exactly times givesThe last MRA low-pass filter factor is . Its derivatives of all orders less than vanish at , because is odd and the MRA low-pass filter is -periodic. If the remaining factors are at the displayed arguments, the product rule forces every derivative of order less than of the product to vanish. In particular compact support and a finite MRA low-pass filter supply all these hypotheses. Therefore the integer-frequency zeros of a scaling function are
Under only the printed assumptions, the exact same finite refinement argument gives the Peano zero . Indeed, the last MRA low-pass filter factor has that estimate, the other MRA low-pass filter factors are bounded by one almost everywhere by the quadrature mirror filter identity, and the last Fourier transform factor is bounded because . The estimate initially holds almost everywhere and extends to every by continuity of . It does not imply arbitrary ordinary higher derivatives. In the lacunary scaling-phase regularity counterexample, is nondifferentiable at dense dyadic points next to the isolated integer-frequency zeros of the smooth base transform. Thus the same regularity qualification is necessary here.
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