Math 414-501 — Final Exam Review

General Information

The final exam will be given in our usual classroom on Monday, 5/11/09. Please bring an 8½×11 bluebook. I will have extra office hours this week; I'll announce the times later. Points on the test will be approximately distributed this way: chapter 1, 10%; chapters 2 and 3, 20% and, chapters 4-6, 70%. Questions from chapters 1-3 will be involve calculations, but no theory. See sections calculations in the review sheets for Test 1 and Test 2.

Calculators. You may use calculators to do arithmetic, although you will not need them. You may not use any calculator that has the capability of doing linear algebra or storing programs or other material.

Other devices. You may not use cell phones, computers, or any other device capable of storing, sending, or receiving information.

Structure. There will be 6 to 8 questions, some with multiple parts. The problems will be similar to ones done for homework, and as examples in class and in the text.

Topics Covered

Haar wavelets. Know the Haar scaling function, wavelet, approximation spaces (V's), and wavelet spaces (W's). Using the Haar wavelet and scaling function, be able to carry out simple decomposition and reconstruction algorithms. Know what the various high pass and low pass filters associated with these algorithms are, what downsampling and upsampling are, and finally be able to use filter diagrams to describe the decomposition and reconstruction algorithms.

Multiresolution analysis (MRA). You will be asked to define Mallat's multiresolution analysis, including the approximation spaces (V's), the scaling relation, the wavelet spaces (W's), and the wavelet itself. Know the decomposition and reconstruction formulas, high-pass and low-pass decomposition and reconstruction filters, downsampling and upsampling. Be able to discuss the details of the multiresolution analysis in the Haar case or for the Shannon MRA (exercise 8 in § 5.4). Know how to implement both decomposition and reconstruction algorithms. In particular, be able to show that the top level coefficients, which are used in the initialization step, have the approximate form ajk ≈ m f( 2 -jk), where m = ∫-∞ &phi(x)dx (Theorem 5.12).

Fourier transform criteria for an MRA. Be able to find the Fourier transformed (i.e., frequency space) form of the scaling relation (Theorem 5.19). Be able to outline how the scaling function and the wavelet are derived from the function P(z) that satisfies the conditions in Theorem 5.23. Know these conditions.

Daubechies' wavelets. Know how the Daubechies wavelets are classified using N, the largest power of z+1 that divides P(z), and also know how N relates to the number of vanishing moments of a wavelet and the support of the Daubechies scaling. For N=2, be able to show that the bjk is a multiple of the 2nd derivative 2 -(5/2)j f ″( 2 -jk), as we did in class. Be able to explain how the approximate form of the wavelet coefficients (equation (6.13)) can be used in singularity detection and data compression. Be able to explain various ways of handling the problem of overspill; see section 6.3.

Updated 5/5/2009.