Applied & Computational Harmonic Analysis:
Comments, Handouts, and References Page (Winter 2014)
Course: MAT 271
CRN: 84077
Title: Applied & Computational Harmonic Analysis
Class: TR 1:40pm3:00pm, Physics 140
Instructor: Naoki Saito
Office: 2142 MSB
Phone: 7542121
Email:saito@math.ucdavis.edu
Office Hours: TR 3:10pm4:00pm, or by appointment
The following references are useful and contains much more
details of the topics covered or referred to in my lectures.
I strongly encourage you to take a look at some of them.
Lecture 1: Overture and Motivation;
What is a Signal?
For quantization, which will not be discussed in this course due to the
time constraint, see:  R. M. Gray and D. L. Neuhoff: "Quantization," IEEE Trans. Inform.
Theory, vol.44, no.6, pp.23252383, 1998.
 K. Sayood: Introduction to Data Compression, 3rd Ed., Morgan
Kaufmann Publ., 2006. In particular, Chapters 8 and 9.
If you are interested in vision science, I would strongly recommend the following books:

D. H. Hubel: Eye, Brain, and Vision, Scientific American Library, 1995.

B. A. Wandell: Foundation of Vision, Sinauer Associates, Inc., 1995.
Lecture 2: Basics of the Fourier Transforms
The following engineeringoriented book has been popular for a long time
and contains quite useful information:
 R. N. Bracewell: The Fourier Transform and Its Applications,
3rd Ed., McGraw Hill, 1999.
Details of the L^{2} theory:
 Dym and McKean: Sec. 2.32.5.
 Pinsky: Sec. 2.4.
 G. B. Folland: Real Analysis, 2nd Ed., Wiley
Interscience, 1999. Sec. 8.3.
 E. M. Stein and G. L. Weiss: Introduction to Fourier
Analysis on Euclidean Spaces, Princeton Univ. Press, 1970. Sec. 1.2.
Lecture 3: Uncertainty Principles
Basic references on the Heisenberg inequality/uncertainty principle in
L^{2}:
 Dym and McKean: Sec. 2.8.
 Folland: Fourier Analysis, Sec. 7.3.
 Pinsky: Sec. 2.4.3.
Basic references on more general uncertainty principles such as those in L^{1}, which played as seeds for the popular Compressed Sensing:
 D. L. Donoho and P. B. Stark: "Uncertainty principles and signal recovery," SIAM J. Appl. Math., vol.49, no.3, pp.906931, 1989.
 D. L. Donoho and X. Huo: "Uncertainty principles and ideal atomic decomposition," IEEE Trans. Inform. Theory, vol.47, no.7, pp.28452862, 2001.
Lecture 4: Bandlimited Functions and Sampling Theorems; Periodization vs Sampling
Sampling Theorems:  R. N. Bracewell: The Fourier
Transform and Its Applications, 2nd Ed., Revised, McGrawHill,
1987. Chap. 10.
 W. L. Briggs and V. E. Henson: The DFT: An Owner's Manual
for the Discrete Fourier Transform, SIAM, 1995. Sec. 3.4, Chap. 6.
 Pinsky: Chap.4.
 See also a nice interactive java demonstration by Matt Herman on sampling and aliasing.
For more details on Sampling Theorems and NonUniform Sampling Schemes,
see:  H. J. Landau: "Sampling, data transmission, and the Nyquist rate," Proc. IEEE, vol.55, no.10, pp.17011706, 1967.
 A. Aldroubi and K. Gröchenig, "Nonuniform sampling and reconstruction in shiftinvariant spaces," SIAM Review, vol.43, no.4, pp.585620, 2001.
For the historical articles on the sampling theorems, see:  E. T.
Whittaker: "On the functions which are represented by the expansions of
the interpolationtheory," Proc. Royal Soc. Edinburgh, Sec. A,
vol.35, pp.181194, 1915.
 C. E. Shannon: "Communication in the presence of noise," Proc. IRE, vol.37, pp.1021, 1949.
 M. Unser: "Sampling50 years after Shannon," Proc. IEEE, vol.88, no.4, pp.569587, 2000.
 E. Meijering: "A chronology of interpolation: From ancient astronomy to modern signal and image processing," Proc. IEEE, vol.90, no.3, pp.319342, 2002.
 P. L. Butzer, P. J. S. G. Ferreira, J. R. Higgins, S. Saitoh, G. Schmeisser, and R. L. Stens: "Interpolation and sampling: E. T. Whittaker, K. Ogura and their followers," J. Fourier Anal. Appl., vol.17, no.2, pp.320354, 2011.
Lecture 5: Basic Theory of Fourier Series; Smoothness of Functions
and Decay Rate of the Fourier Coefficients
Orthogonal Polynomials:
 G. Szegő: Orthogonal Polynomials, 4th
Ed., AMS, 1975.
 Folland: Fourier Analysis, Chap. 6.
The Gibbs (or more appropriately GibbsWilbraham) Phenomenon:
Almost all books on Fourier analysis listed above, e.g.,
DymMcKean, Folland, Pinsky, etc., describe it. Yet the following interesting and
scholastic paper is clearly the best information source:
 E. Hewitt and R. E. Hewitt: "The GibbsWilbraham phenomenon: An episode in Fourier analysis," Archive for History of Exact Sciences, vol. 21, no. 2, pp. 129160, 1979.
In higher dimensions, very peculiar things can happen. Gray and Pinsky
discovered a Gibbslike phenomenon can occur at a point of continuity
in R^{d} for d > 2.
It is known as the Pinsky phenomenon. See the following articles
for the details.
 A. Gray and M. A. Pinsky: "Computer graphics and a new Gibbs
phenomenon for FourierBessel series," Experiment. Math., vol. 1, no. 4, pp. 313316, 1992.
 M. A. Pinsky, N. K. Stanton, and P. E. Trapa: "Fourier series of radial functions in several variables,"
J. Funct. Anal., vol. 116, no. 1, pp. 111132, 1993.
On the Basel Problem ∑ k^{2} =
π^{2}/6, Euler, different proofs, etc.
 W. Dunham: Euler: The Master of Us All, Math. Assoc. Amer., 1999.
Chap.3.
 R. Ayoub: "Euler and the zeta function," Amer. Math. Monthly, vol.81, no.10, pp.10671086, 1974.
 Dan Kalman: "Six ways to sum a series," College Math. Jour., vol.24, no.5, pp.402421, 1993.
Smoothness Class Hierarchy:  P. J. Davis and P.
Rabinowitz: Methods of Numerical Integration, Academic Press, 1984 (Reprinted by Dover Pub. Inc., 2007)
Sec. 1.9.
Lecture 6: Functions of Bounded Variations; the Decay Rate of the
Fourier Coefficients II; Fourier Series on Intervals
Functions of Bounded Variation, the Fourier Coefficients:
 C. Lanczos: Discourse on Fourier Series, Hafner Publishing Co., New York, 1966. Sec 2. This is the best book on 1D Fourier series from the applied perspective. Unfortunately, this book is out of print.
 V. I. Smirnov: A Course of Higher Mathematics, Vol. V,
Pergamon Press, 1964, Chap. 1. This is out of print too.
 M.Taibleson: "Fourier coefficients of functions of bounded variation," Proc. Amer. Math. Soc., vol.18, pp.766, 1967.
The definition of BV in higher dimensions can be found in:  L. C.
Evans and R. F. Gariepy: Measure Theory and Fine Properties of
Functions, CRC Press, 1992, Chap.5.
Fourier Series on Intervals, Fourier Cosine and Sine Series:
 Folland: Fourier Analysis, Sec. 2.4.
 C. Lanczos: Applied Analysis, PrenticeHall, Inc., 1956,
Reprinted by Dover, 1988, Sec. 4.5. This book is still in print. I
strongly urge you to buy this book and read it from cover to cover!
Lecture 7: Discrete Fourier Transform
Advanced topics on DFT:
 J. H. McClellan ad T. W. Parks: "Eigenvalue and eigenvector decomposition of the discrete Fourier transform," IEEE Trans. Audio and
Electroacoustics, vol.AU20, no.1, pp.6674, 1972 (with comments, vol.AU21, no.1, pp.65, 1973).

L. Auslander and R. Tolimieri: "Is computing with the finite Fourier transform pure or applied mathematics?" Bull. AMS, vol.1, no.6, pp.847897, 1979.
 A. Terras: Fourier Analysis on Finite Groups and Applications,
London Mathematical Society Student Texts vol.43, Cambridge Univ.Press,
1999.
Relationship between Fourier Series, DFT, and Trigonometric
Interpolation:  C. Lanczos: Discourse on Fourier Series,
Hafner Publishing Co., New York, 1966. Sec 17.
 I. P. Natanson: "On the convergence of trigonometrical interpolation at
equidistant knots," Annals of Math., vol.45, no.3, pp.457471, 1944.
 J. P. Boyd: Chebyshev and Fourier Spectral Methods, 2nd Ed., Dover, 2001. Chapter 4, in particular, Sec.4.5.
 D. M. Young and R. T. Gregory: A Survey of Numerical
Mathematics, Vol. I, AddisonWesley, 1972, pp.329339.
Lecture 8: Fast Fourier Transform (FFT)
There are many references on FFT, but the following are particularly
useful: 
J. W. Cooley and J. W. Tukey: "An algorithm for the machine
calculation of complex Fourier series," Math. Comput., vol.19,
pp.297301, 1965.
 Briggs and Henson: Chap. 10.
 C. F. Van Loan: Computational Frameworks for the Fast Fourier
Transform, SIAM, 1992.
 W. T. Cochran et al.: "What is the Fast Fourier Transform?", Proc. IEEE, vol.55, no.10, pp.16641674, 1967.
Perhaps, the best FFT public software package is:  FFTW, which also includes
higher dimensional FFT as well as DCT/DST.
Lecture 9: From the SturmLiouville Theory to Discrete Cosine and Sine Transforms (DCT/DST)
For the SturmLiouville Theory I referred to in today's lecture,
the following are nice references:
 Folland: Fourier Analysis: Sec.3.5, 3.6, 7.4.
 Dym and McKean: Sec. 1.7, 1.9.
 R. Courant and D. Hilbert: Methods of Mathematical Physics,
Vol. I, First English Edition, John Wiley and Sons, 1953.
Republished as Wiley Classics Library in 1989. See Chap. V
in particular.
For the history and the current status of the SturmLiouville theory,
the following book is quite informative:
 W. O. Amrein, A. M. Hinz, and D. P. Pearson
(eds.): SturmLiouville Theory: Past and Present, Birkhäuser, 2005.
For basic and important references on DCT/DST are:
 N. Ahmed, T. Natarayan, and K. R. Rao: "Discrete cosine transform," IEEE Trans. Comput., vol.COM23, pp.9093, 1974.
 K. R. Rao and P. Yip: Discrete Cosine Transform: Algorithms,
Advantages, and Applications, Academic Press, 1990.
 G. Strang: "The discrete cosine transform," SIAM Review, vol.41, no.1, pp.135147, 1999.
 M. V. Wickerhauser: Adapted Wavelet Analysis from Theory to
Software, A K Peters, Ltd., 1994. Chap. 3.
Lecture 10: KarhunenLoève Transform (KLT)
Discrete version (aka Principal Component Analysis [PCA]): 
K. Fukunaga: Introduction to Statistical Pattern Recognition,
2nd Edition, Academic Press, 1990. Chap. 9, Appendix A.
 K. V. Madia, J. T. Kent, and J. M. Bibby: Multivariate
Analysis, Academic Press, 1979. Chap. 8.
 S. Watanabe: "KarhunenLoève expansion and factor
analysis: Theoretical remarks and applications," Trans. 4th Prague
Conf. Inform. Theory, Statist. Decision Functions, Random Processes,
Publishing House of the Czechoslovak Academy of Sciences, Prague,
pp.635660, 1965.
 R. Kannan and S. Vempala:
"Spectral algorithms," Foudations and Trends in Theoretical Computer Science, vol.4, nos.34, pp.157288, 2008.
We only discussed the discrete version in the class, but KLT has its
continuous version. The following are some references:
 U. Grenander: "Stochastic processes and statistical inference," Arkiv för Matematik, vol.1, no.3, pp.195277, 1950.
 W. B. Davenport and W. L. Root: An Introduction to the Theory of
Random Signals and Noise, McGraw Hill, 1958, republished by IEEE
Press, 1987. Chap. 6.
 W. D. Ray and R. M. Driver: "Further decomposition of
the KarhunenLoève series representation of a stationary random process," IEEE Trans. Inform. Theory, vol.IT16, no.6, pp.663668, 1970.
Relationship between KLT/PCA and SVD:
 N. Saito: "Image approximation and modeling via least statistically dependent bases", Pattern Recognition, vol.34, no.9, pp.17651784, 2001.
 L. Lieu and N. Saito: "Signal ensemble classification using lowdimensional embeddings and Earth Mover's Distance", in Wavelets and Multiscale Analysis: Theory and Applications (J. Cohen and A. I. Zayed, eds.), Chap.11, pp.227256, Birkhäuser, 2011.
Basics of Singular Value Decomposition (SVD):
 L. N. Trefethen and D. Bau, III: Numerical Linear Algebra, SIAM, 1997, Chap.4: The Singular Value Decomposition.
 L. N. Trefethen and D. Bau, III: Numerical Linear Algebra, SIAM, 1997, Chap.5: More about the SVD.
 G. H. Golub and C. F. Van Loan: Matrix Computations, 4th Ed.,
Johns Hopkins Univ. Press, 2013. Sec. 2.4.
 G. W. Stewart: "On the early history of the singular value decomposition," SIAM Review, vol.35, no.4, pp.551566, 1993.
Applications: Eigenfaces/The Rogues Gallery Problem:
 M. Kirby and L. Sirovich, "Application of KarhunenLoeve procedure for the characterization of human faces," IEEE Trans. Pattern Anal. Machine Intell., vol.12, no.1, pp.103108, 1990.
 N. Saito: "Image approximation and modeling via least statistically dependent bases", Pattern Recognition, vol.34, no.9, pp.17651784, 2001.
Relationship between KLT/PCA and DCT:
 N. Ahmed, T. Natarayan, and K. R. Rao: "Discrete cosine transform," IEEE Trans. Comput., vol.COM23, pp.9093, 1974.
 R. J. Clarke: "Relation between the Karhunen Loève and cosine transforms," IEE Proc., vol.128, Part F, no.6, pp.359360, 1981.
On Toeplitz matrices:  U. Grenander and G. Szegő: Toeplitz
Forms and Their Applications, 2nd Ed., AMSChelsea, 1984.
 R. M.
Gray: Toeplitz and circulant matrices: A review, Technical Report,
Information Systems Laboratory, Department of Electrical Engineering,
Stanford University, 2009.
 H. Widom: "Toeplitz matrices," in Studies in Real and Complex
Analysis (I. I. Hirschman, Jr. ed.), MAA Studies in Mathematics,
1965.
Lecture 11: TimeFrequency Analysis and Synthesis; Windowed
(or ShortTime) Fourier Transform
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Chap. 4.
 I. Daubechies: Ten Lectures on Wavelets, SIAM, 1992.
Chap.2.
 I. Daubechies: "The wavelettransform, timefrequency localization and signal analysis," IEEE Trans. Inform. Theory, vol.36, no.5, pp.9611005, 1990.
Some historical papers:
 D. Gabor: "Theory of communication: Part I: The analysis of information," J. IEE (London), vol.93, no.26, pp.429441, 1946.
 D. Gabor: "Theory of communication: Part II: The analysis of hearing," J. IEE (London), vol.93, no.26, pp.442445, 1946.
 D. Gabor: "Theory of communication: Part III: Frequency compression and expansion," J. IEE (London), vol.93, no.26, pp.445457, 1946.
 J. Ville: "Théorie et applications de la notion de signal
analytique," Cables et Transmissions, 2ème A, no.1,
pp.6174, 1948.
For more data adaptive tilings of the timefrequency plane, see e.g.:
 C. Herley, J. Kovačević, K. Ramchandran, and M. Vetterli: "Tilings of the timefrequency plane: construction of arbitrary orthogonal bases and fast tiling algorithms," IEEE Trans. Signal Process., vol.41, no.12, pp.33413359, 1993.
 C. M. Thiele and L. F. Villemoes: "A fast algorithm for adapted timefrequency tilings," Applied and Computational Harmonic Analysis, vol.3, no.2, pp.9199, 1996.
Lecture 12: Introductory Frame Theory; The BalianLow Theorem
Some basic references:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed., Academic Press, 2009. Chap. 5.
 I. Daubechies: Ten Lectures on Wavelets, SIAM, 1992. Chap. 3, 4.
 K.Gröchenig: Foundations of TimeFrequency Analysis,
Birkhäuser, 2001. Chap. 57.
 O. Christensen: Frames and Bases: An Introductory Course, Birkhäuser, 2002.
 J.P. Kahane and P.G. LemariéRieusset: Fourier Series
and Wavelets, Studies in the Development of Modern Mathematcis,
Vol.3, Gordon and Breach Publishers, 1995. Chap. 1 of the Wavelet portion.
See also the following original papers:
 R. Balian: "Un principe d'incertitude fort en théorie du signal ou en mécanique quantique," C. R. Acad. Sci. Paris, vol.292, pp.13571362, 1981.
 M. J. Bastiaans: "Gabor's expansion of a signal into Gaussian elementary signals,"
Proc. IEEE, vol.68, no.4, pp.538539, 1980.
 G. Battle: "Heisenberg proof of the BalianLow theorem," Lett. Math. Phys., vol.15, pp.175177, 1988.
 I. Daubechies: "The wavelettransform, timefrequency localization and signal analysis," IEEE Trans. Inform. Theory, vol.36, no.5, pp.9611005, 1990.
 I. Daubechies and A. J. E. M. Janssen: "Two theorems on lattice expansions," IEEE Trans. Inform. Theory, vol.39, no.1, pp.36, 1993.
Lecture 13: Continuous Wavelet Transform
Some basic references:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Chap. 4, 5.
 I. Daubechies: Ten Lectures on Wavelets, SIAM, 1992.
Chap. 3, 4.
 M. Holschneider: Wavelets: An Analysis Tool, Clarendon Press,
Oxford, 1995. Chap. 1.
 I. Daubechies: "The wavelettransform, timefrequency localization and signal analysis," IEEE Trans. Inform. Theory, vol.36, no.5, pp.9611005, 1990.
Historic papers by Calderón and Grossman & Morlet can be found at:
 A.
P. Calderón: "Intermediate spaces and interpolation, the complex
method," Studia Mathematica, vol.XXIV, pp.113190, 1964.
 A. Grossmann and J. Morlet: "Decomposition of Hardy functions into square integrable wavelets of constant shape," SIAM J. Math. Anal., vol.15, no.4, pp.723736, 1984.
Lecture 14: Continuous Wavelet Transform II: Analytic Wavelets
Analytic Signals:
 D. Gabor: "Theory of communication: Part I: The analysis of information," J. IEE (London), vol.93, no.26, pp.429441, 1946.
 D. E. Vakman: "On the definition of concepts of amplitude, phase, and frequency of a signal," Radio Eng. Electron. Phys., vol.17, no.5, pp.754759, 1972.
 A. Papoulis: Signal Analysis, McGrawHill, 1977. Sec.42.
 M. T. Taner, F. Koehler, and R. E. Sheriff: "Complex seismic trace analysis," Geophysics, vol.44, no.6, pp.10411064, 1979; See also the errata, Geophysics, vol.44, no.11, p.1896, 1979.
 L. Cohen, P. Loughlin, and D. Vakman: "On an ambiguity in the definition of the amplitude and phase of a signal," Signal Processing, vol.79, no.3, pp.301307, 1999.
General Analytic Wavelets:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Chap. 4.
 M. Holschneider: Wavelets: An Analysis Tool, Clarendon Press,
Oxford, 1995. Chap. 1.
 J. M. Lilly and S. C. Olheda: "On the analytic wavelet transform," IEEE Trans. Inform. Theory, vol.56, no.8, pp.41354156, 2010.
The Generalized Morse Wavelets:
 S. C. Olheda and A. T. Walden: "Generalized Morse wavelets," IEEE Trans. Signal Process., vol.50, no.11, pp.26612670, 2002.
 J. M. Lilly and S. C. Olheda: "Higherorder properties of analytic wavelets," IEEE Trans. Signal Process., vol.57, no.1, pp.146160, 2009.
 J. M. Lilly and S. C. Olheda: "Generalized Morse wavelets as a superfamily of analytic wavelets," IEEE Trans. Signal Process., vol.60, no.11, pp.60366041, 2012.
Some historic papers by J. Morlet and collaborators:
 J. Morlet, G. Arens, E. Fourgeau, and D. Glard: "Wave propagation and sampling theoryPart I: Complex signal and scattering in multilayered media," Geophysics, vol.47, no.2, pp.203221, 1982.
 J. Morlet, G. Arens, E. Fourgeau, and D. Glard: "Wave propagation and sampling theoryPart II: Sampling theory and complex waves," Geophysics, vol.47, no.2, pp.222236, 1982.
 A. Grossmann and J. Morlet: "Decomposition of Hardy functions into square integrable wavelets of constant shape," SIAM J. Math. Anal., vol.15, no.4, pp.723736, 1984.
Lecture 15: Discrete Wavelet Transforms; Multiresolution Approximation; Scaling Functions
For the regular hyperbolic sampling scheme and the frame conditions for
discretizing the continuous wavelet transform, see:
 I. Daubechies: "The wavelettransform, timefrequency localization and signal analysis," IEEE Trans. Inform. Theory, vol.36, no.5, pp.9611005, 1990.
 J.P. Kahane and P.G. LemariéRieusset: Fourier Series
and Wavelets, Studies in the Development of Modern Mathematcis, Vol.3,
Gordon and Breach Publishers, 1995. Chap. 2 of the Wavelet portion.
The standard references on the multiresolution approximations are:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Chap. 7.
 I. Daubechies: Ten Lectures on Wavelets, SIAM, 1992. Chap. 5.
 J.P. Kahane and P.G. LemariéRieusset: Fourier Series
and Wavelets, Studies in the Development of Modern Mathematcis, Vol.3,
Gordon and Breach Publishers, 1995. Chap 3 of the Wavelet portion.
Lecture 16: Conjugate Mirror Filters; Mother Wavelets; Orthonormal Wavelet Basis
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Chap. 7.
 I. Daubechies: Ten Lectures on Wavelets, SIAM, 1992. Chap. 5, 6.
The following article provides an excellent overiew of the wavelet transforms/bases and their impact to applications:
 I. Daubechies: "Wavelets and Applications," in The Princeton Companion to Mathematics (T. Gower, Ed.), Princeton Univ. Press, 2008, pp.848862.
Lecture 17: Vanishing Moments; Support Size; Regularity; and Daubechies's Compactly Supported Wavelets
Some basic references:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Sec. 7.2
 I. Daubechies: Ten Lectures on Wavelets, SIAM, 1992. Chap. 6.
 I. Daubechies: "Orthonormal bases of compactly supported wavelets,"
Comm. Pure Appl. Math., vol.41, no.7, pp.909996, 1988.
Lecture 18: Fast Wavelet Transforms; Various Extensions
A basic reference on Fast Wavelet Transforms:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Sec. 7.3
On boundary treatment of input signals:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Sec. 7.5
 A. Cohen, I. Daubechies, and P. Vial: "Wavelet bases on the interval and fast algorithms," Applied and Computational Harmonic Analysis, vol.1, no.1, pp.5481, 1993.
On the lack of translation invariance of the orthogonal wavelet representations and possible solutions:
 G. Beylkin: "On the representation of operators in bases of compactly supported wavelets," SIAM J. Numerical Anal., vol. , no. , pp.17161740, 1992.
 G. Nason and B. W. Silverman: "The stationary wavelet transform and some statistical applications," in Lecture Notes in Statistics (A. Antoniadis and G. Oppenheim, eds.), vol.103, pp.281299, 1995.
For near translation invariant transforms, see, e.g.:
 E. P. Simoncelli, W. T. Freeman, E. H. Adelson, and D. J. Heeger: "Shiftable multiscale transforms," IEEE Trans. Inform. Theory, vol.38, no.2, pt.2, pp.587607, 1992.
 N. Kingsbury: "Complex wavelets for shift invariant analysis and filtering of signals," Applied and Computational Harmonic Analysis, vol.10, no.3, pp.234253, 2001.
 I. W. Selesnick, B. G. Baraniuk, and N. C. Kingsbury: "The dualtree complex wavelet transform," IEEE Signal Processing Magazine, vol.22, no.6, pp.123151, 2005.
On the lack of symmetry/antisymmetry of the father and mother wavelets and possible solutions:
 I. Daubechies: Ten Lectures on Wavelets, SIAM, 1992. Chap. 8.
Near symmetric conjugate mirror filters leading to symmlets:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Sec. 7.2
Biorthogonal wavelet representations:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Sec. 7.4
 A. Cohen, I. Daubechies, and J.C. Feauveaux: "Biorthogonal bases of compactly supported wavelets", Comm. Pure Appl. Math., vol.45, no.5, pp.485560, 1992.
Wavelet frames/framelets: see, e.g.,
 I. Daubechies, B. Han, A. Ron, and Z. Shen: "Framelets: MRAbased constructions of wavelet frames," Applied and Computational Harmonic Analysis, vol.14, no.1, pp.146, 2003
and the references therein.
For the autocorrelation shell representation, see:
 N. Saito and G. Beylkin: "Multiresolution representations using the autocorrelation functions of compactly supported wavelets", IEEE Trans. Signal Process., vol.41, no.12, pp.35843590, 1993.; see also Errata.
Lecture 19: A Library of Othonormal Bases and Adapted Signal Analysis
The basic references on these subjects:
 S. Mallat: A Wavelet Tour of Signal Processing, 3rd Ed.,
Academic Press, 2009. Chap. 8
 M. V. Wickerhauser: Adapted Wavelet Analysis from Theory to
Software, A K Peters, Ltd., 1994. Chap. 4, 7, 8.
 R. R. Coifman and M. V. Wickerhauser: "Entropybased algorithms for best basis selection," IEEE Trans. Inform. Theory, vol.38, no.2, pp.713718, 1992.
For a variety of efficacy measures for selecting a basis from
basis dictionaries for classification, regression, and other applications,
see, e.g.,
 N. Saito: "Local feature extraction and its applications using a library of bases," in Topics in Analysis and Its Applications: Selected Theses (R. Coifman, ed.), pp.269451, World Scientific, 2000.
 N. Saito: "Image approximation and modeling via least statisticallydependent bases," Pattern Recognition, vol.34, no.9, pp.17651784, 2001.
 N. Saito, R. R. Coifman, F. B. Geshwind, and F. Warner: Discriminant feature extraction using empirical probability density estimation and a local basis library, Pattern Recognition, vol.35, no.12, pp.28412852, 2002.
Lecture 20: Multiscale Basis Dicionarites on Graphs and Networks
For a nice review on the recent explosion of interest in signal processing on graphs, see the following and the references therein.
 D. I. Shuman, S. K. Narang, P. Frossard, A. Ortega, and P. Vandergheynst: "The emerging field of signal processing on graphs: Extending highdimensional data analysis to networks and other irregular domains," IEEE Signal Processing Magazine, vol.30, no.3, pp.8398, 2013.
The basic references on graph Laplacians and spectral graph theory:
 F. R. K. Chung: Spectral Graph Theory, CBMS Regional Conference Series in Mathematics, no. 92, Amer. Math. Soc., 1997.
Some of the chapters are available from her website.
 D. Cvetković, P. Rowlinson, and S. Simić: An Introduction to the Theory of Graph Spectra, Vol. 75, London Mathematical Society Student Texts, Cambridge Univ. Press, 2010.
 A. E. Brouwer and W. H. Haemers: Spectra of Graphs, Springer, 2012.
 R. B. Bapat: Graphs and Matrices, Universitext, Springer, 2010.
 D. Spielman: "Spectral graph theory," in Combinatorial Scientific Computing (O. Schenk, ed.), Chap.18, pp.495524, CRC Press, 2012.