Past exam of the mathematics course of the University of Cambridge 2018 iii Paper 340 2 a ii Solution Created 2026-10-03 Updated 2026-10-05
The density axiom and continuity of the Fourier transform at zero imply . Here is a proof that avoids assuming a normalization of the integral. Choose a nonzero whose Fourier transform has bounded support. The MRA projection Fourier identity, with no aliasing once is sufficiently large, isSince , its Fourier transform is continuous and bounded, so this tends to . Density and nesting give in . Thus , in particular it is nonzero. Evaluating the scaling refinement equation in frequency at zero now giveswhich is stronger than the requested absolute-value equality. Multiplying the scaling function by a constant of modulus one normalizes its integral to one without changing .
Past exam of the mathematics course of the University of Cambridge 2018 iii Paper 340 2 b Solution Created 2026-10-03 Updated 2026-10-05
At zero, the partial products are . Their assumed convergence and force and . Uniform convergence on compact sets makes continuous. The identity with gives with squared norm . Define by the inverse Fourier transform in . The Plancherel theorem and the other given integral identities giveDefine as the closed span of . These functions form an orthonormal basis of , and dyadic dilation gives the scale axiom. Shifting the infinite product givesso the finite Fourier series of gives a scaling refinement equation and . The coarse-scale projection argument of part 1(b) proves the trivial-intersection axiom.
For density, take a function with bounded Fourier support. The MRA projection Fourier identity gives, for large ,Uniform convergence of to one on that support proves the limit. Since is an orthogonal projection, . Such functions are dense in , givingThus all the multiresolution analysis axioms hold. Under the strong convergence and orthogonality assumptions supplied here, the additional nonvanishing condition is not needed in this last verification; it is useful when establishing those assumptions from a filter.
Scaling function 2026-10-05
A scaling function generates the approximation space of a multiresolution analysis by its integer translates. In an orthonormal construction those translates form an orthonormal basis, and generate . Integrable orthonormal scaling functions have , as follows from density and the MRA projection Fourier identity.