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Walter (mathematics, U. of Wisconsin-Milwaukee) and Shen (mathematics and computer sciences, Eastern Connecticut State U.) present wavelets in the same setting as other orthogonal systems, in particular Fourier series and orthogonal polynomials, in order to reveal their advantages and disadvantages directly. Their treatment should be accessible to graduate students in engineering and mathematics who have a command of analysis at the level of beginning graduate real and complex analysis courses. They mention no date for the first edition, but have corrected misprints and errors, and reviewed the chapter-end problems and added some to make their solution easier for students. Annotation c. Book News, Inc., Portland, OR (booknews.com)

A bestseller in its first edition, Wavelets and Other Orthogonal Systems: Second Edition has been fully updated to reflect the recent growth and development of this field, especially in the area of multiwavelets. The authors have incorporated more examples and numerous illustrations to help clarify concepts. They have also added a considerable amount of new material, including sections addressing impulse trains, an alternate approach to periodic wavelets, and positive wavelet s. Other new discussions include irregular sampling in wavelet subspaces, hybrid wavelet sampling, interpolating multiwavelets, and several new statistics topics.

With cutting-edge applications in data compression, image analysis, numerical analysis, and acoustics wavelets remain at the forefront of current research. Wavelets and Other Orthogonal Systems maintains its mathematical perspective in presenting wavelets in the same setting as other orthogonal systems, thus allowing their advantages and disadvantages to be seen more directly. Now even more student friendly, the second edition forms an outstanding text not only for graduate students in mathematics, but also for those interested in scientific and engineering applications.
Preface to first edition v
Preface to second edition ix
List of Figures
xvii
Orthogonal Series
1(18)
General theory
1(4)
Examples
5(10)
Trigonometric system
6(4)
Haar system
10(2)
The Shannon system
12(3)
Problems
15(4)
A Primer on Tempered Distributions
19(18)
Intuitive introduction
20(2)
Test functions
22(3)
Tempered distributions
25(5)
Simple properties based on duality
27(2)
Further properties
29(1)
Fourier transforms
30(2)
Periodic distributions
32(1)
Analytic representations
33(2)
Sobolev spaces
35(1)
Problems
35(2)
An Introduction to Orthogonal Wavelet Theory
37(36)
Multiresolution analysis
38(6)
Mother wavelet
44(9)
Reproducing kernels and a moment condition
53(2)
Regularity of wavelets as a moment condition
55(9)
More on example 3
59(5)
Mallat's decomposition and reconstruction algorithm
64(1)
Filters
65(5)
Problems
70(3)
Convergence and Summability of Fourier Series
73(18)
Pointwise convergence
73(6)
Summability
79(2)
Gibbs phenomenon
81(3)
Periodic distributions
84(3)
Problems
87(4)
Wavelets and Tempered Distributions
91(18)
Multiresolution analysis of tempered distributions
92(3)
Wavelets based on distributions
95(5)
Distribution solutions of dilation equations
95(4)
A partial distributional multiresolution analysis
99(1)
Distributions with point support
100(4)
Approximation with impulse trains
104(3)
Problems
107(2)
Orthogonal Polynomials
109(20)
General theory
109(5)
Classical orthogonal polynomials
114(12)
Legendre polynomials
115(4)
Jacobi polynomials
119(1)
Laguerre polynomials
120(1)
Hermite polynomials
121(5)
Problems
126(3)
Other Orthogonal Systems
129(32)
Self adjoint eigenvalue problems on finite intervals
130(2)
Hilbert-Schmidt integral operators
132(2)
An anomaly: the prolate spheroidal functions
134(1)
A lucky accident?
135(5)
Rademacher functions
140(2)
Walsh function
142(1)
Periodic wavelets
143(7)
Periodizing wavelets
144(2)
Periodic wavelets from scratch
146(4)
Local sine or cosine basis
150(4)
Biorthogonal wavelets
154(5)
Problems
159(2)
Pointwise Convergence of Wavelet Expansions
161(26)
Reproducing kernel delta sequences
162(1)
Positive and quasi-positive delta sequences
163(6)
Local convergence of distribution expansions
169(3)
Convergence almost everywhere
172(1)
Rate of convergence of the delta sequence
173(4)
Other partial sums of the wavelet expansion
177(1)
Gibbs phenomenon
178(3)
Positive scaling functions
181(5)
A general construction
181(1)
Back to wavelets
182(4)
Problems
186(1)
A Shannon Sampling Theorem in Wavelet Subspaces
187(30)
A Riesz basis of Vm
188(1)
The sampling sequence in Vm
189(2)
Examples of sampling theorems
191(4)
The sampling sequence in Tm
195(2)
Shifted sampling
197(2)
Gibbs phenomenon for sampling series
199(13)
The Shannon case revisited
201(1)
Back to wavelets
201(11)
Irregular sampling in wavelet subspaces
212(2)
Problems
214(3)
Extensions of Wavelet Sampling Theorems
217(38)
Oversampling with scaling functions
218(5)
Hybrid sampling series
223(2)
Positive hybrid sampling
225(3)
The convergence of the positive hybrid series
228(4)
Cardinal scaling functions
232(8)
Interpolating multiwavelets
240(2)
Orthogonal finite element multiwavelets
242(10)
Sobolev type norm
244(1)
The mother multiwavelets
245(7)
Problems
252(3)
Translation and Dilation Invariance in Orthogonal Systems
255(14)
Trigonometric system
255(1)
Orthogonal polynomials
256(1)
An example where everything works
257(1)
An example where nothing works
258(1)
Weak translation invariance
259(6)
Dilations and other operations
265(2)
Problems
267(2)
Analytic Representations Via Orthogonal Series
269(26)
Trigonometric series
270(4)
Hermite series
274(6)
Legendre polynomial series
280(2)
Analytic and harmonic wavelets
282(4)
Analytic solutions to dilation equations
286(1)
Analytic representation of distributions by wavelets
287(4)
Wavelets analytic in the entire complex plane
291(2)
Problems
293(2)
Orthogonal Series in Statistics
295(34)
Fourier series density estimators
296(3)
Hermite series density estimators
299(2)
The histogram as a wavelet estimator
301(4)
Smooth wavelet estimators of density
305(4)
Local convergence
309(1)
Positive density estimators based on characteristic functions
310(2)
Positive estimators based on positive wavelets
312(6)
Numerical experiment
316(2)
Density estimation with noisy data
318(4)
Other estimation with wavelets
322(2)
Spectral density estimation
322(2)
Regression estimators
324(1)
Threshold Methods
324(2)
Problems
326(3)
Orthogonal Systems and Stochastic Processes
329(22)
K-L expansions
329(3)
Stationary processes and wavelets
332(3)
A series with uncorrelated coefficients
335(6)
Wavelets based on band limited processes
341(4)
Nonstationary processes
345(4)
Problems
349(2)
Bibliography 351(12)
Index 363
Walter, Gilbert G.; Shen, Xiaoping