A Wavelet Tour of Signal Processing(2nd).part09.rar

A Wavelet Tour of Signal Processing, Second Edition (Wavelet Analysis & Its Applications)
作者: Stéphane Mallat

ISBN: 9780124666061
页数: 637
定价: USD 81.95
出版社: Academic Press
装帧: Hardcover
出版年: 1999-09-15
简介 · · · · · · 　　This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Insti... (展开全部) 　　This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and École
　　Polytechnique in Paris.
　　
　　Key Features
　　* Provides a broad perspective on the principles and applications of transient signal processing with wavelets
　　* Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms
　　* Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection,
　　multifractal analysis, and time-varying frequency measurements
　　* Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet
　　* Content is accessible on several level of complexity, depending on the individual reader's needs
　　New to the Second Edition
　　* Optical flow calculation and video compression algorithms
　　* Image models with bounded variation functions
　　* Bayes and Minimax theories for signal estimation
　　* 200 pages rewritten and most illustrations redrawn
　　* More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics　　

INTRODUCTION_TO_A_TRANSIENT_WORLD_
2_
I._I_Fourier_Kingdom_
2_
I_.2_Time-Frequency_Wedding_
3_
I_.2._I_
Windowed_Fourier_Transform_
4_
I_.2.2_Wavelet_Transform_
6_
Bases_of_Time-Frequency_Atoms_
I_.3_
7_
I_.3._I_Wavelet_Bases_and_Filter_Banks_
9_
Tilings_
of_Wavelet_Packet_and_Local_Cosine_Bases_
I_
.3.2_
11_
I_.4_Bases_for_What?_
12_
I_.4._I_Approximation_
14_
I_.4.2_Estimation_
16_
I_.4.3_Compression_
17_
I_.5_Travel_Guide_
17_
Reproducible_Computational_Science_
I_.5._I_
18_
I_.5.2_Road_Map_
vii_

viii_
CONTENTS_
FOURIER_KINGDOM_
20_
Linear_Time-Invariant_Filtering_'_
2._I_
21_
2._I._I_Impulse_Response_
22_
2._I_.2_Transfer_Functions_
22_
Fourier_Integrals_
2.2_
23_
2.2._I_Fourier_Transform_in_L'(R)_
25_
2.2.2_Fourier_Transform_in_L2(R)_
27_
2.2.3_Examples_
29_
Properties_
'_
2.3_
29_
2.3._I_Regularity_and_Decay_
30_
2.3.2_Uncertainty_Principle_
33_
2.3.3_Total_Variation_
38_
Two-Dimensional_Fourier_Transform_
'_
2.4_
40_
2.5_
Problems_
DISCRETE_REVOLUTION_
42_
Sampling_Analog_Signals_'_
I_
3._
43_
Whittaker_Sampling_Theorem_
3._I._I_
44_
3.1.2_Aliasing_
47_
General_Sampling_Theorems_
3._I_.3_
49_
Discrete_Time-Invariant_Filters_
3.2_
49_
Impulse_Response_and_Transfer_Function_
3.2._I_
51_
3.2.2_Fourier_Series_
54_
'_
Finite_Signals_
3.3_
55_
3.3._I_Circular_Convolutions_
55_
3.3.2_Discrete_Fourier_Transform_
57_
3.3.3_Fast_Fourier_Transform_
58_
3.3.4_Fast_Convolutions_
59_
'_
Discrete_Image_Processing_
3.4_
60_
3.4._I_7ho-Dimensional_Sampling_Theorem_
61_
3.4.2_Discrete_Image_Filtering_
62_
Circular_Convolutions_and_Fourier_Basis_
3.4.3_
64_
3.5_Problems_

CONTENTS_ix_
IV_
TIME_MEETS_FREQUENCY_
67_
Time-Frequency_Atoms_
4._I_
69_
Windowed_Fourier_Transform_
4.2_
72_
4.2._I_Completeness_and_Stability_
75_
4.2.2_Choice_of_Widow_
77_
4.2.3_Discrete_Windowed_Fourier_Transform_
79_
Wavelet_Transforms_
4.3_
80_
4.3._I_Real_Wavelets_
84_
4.3.2_Analytic_Wavelets_
89_
4.3.3_Discrete_Wavelets_
91_
Instantaneous_Frequency_
4.4_
94_
4.4._I_Windowed_Fourier_Ridges_
102_
4.4.2_Wavelet_Ridges_
107_
Quadratic_Time-Frequency_Energy_
4.5_
107_
4.5._I_Wigner-ViUe_Distribution_
112_
4.5.2_Interferences_and_Positivity_
116_
4.5.3_Cohen’s_Class_
120_
4.5.4_Discrete_Wigner-Ville_Computations_
121_
Problems_
4.6_
V_
FRAMES_
125_
Frame_Theory_
5._
I_
125_
Frame_Definition_and_Sampling_
5._I._I_
127_
5._I_.2_Pseudo_Inverse_
132_
Inverse_Frame_Computations_
5._I_.3_
135_
Frame_Projector_and_Noise_Reduction_
5._I_.4_
138_
Windowed_Fourier_Frames_
5.2_
143_
Wavelet_Frames_
5.3_
146_
Translation_Invariance_
5.4_
148_
Dyadic_Wavelet_Transform_
5.5_
150_
5.5._I_Wavelet_Design_
153_
5.5.2_“Algorithme_B_Trous”_
156_
Oriented_Wavelets_for_a_Vision_
5.5.3_
160_
Problems_
5.6_

X_
CONTENTS_
VI_
WAVELET_ZOOM_
163_
Lipschitz_Regularity_'_
6._I_
164_
Lipschitz_Definition_and_Fourier_Analysis_
6._I._I_
166_
Wavelet_Vanishing_Moments_
6._I_.2_
169_
Regularity_Measurements_
with_Wavelets_
6._I_.3_
176_
Wavelet_Transform_Modulus_Maxima_
6.2_
176_
6.2._I_Detection_of_Singularities_
183_
6.2.2_Reconstruction_From_Dyadic_Maxima_
189_
Multiscale_Edge_Detection_
6.3_
189_
6.3._I_Wavelet_Maxima_for_Images_
197_
6.3.2_Fast_Multiscale_Edge_Computations_
200_
Multifractals_
6.4_
200_
Fractal_Sets_and_Self-similar_Functions_
6.4._I_
205_
6.4.2_Singularity_Spectrum_
21_1_
6.4.3_Fractal_Noises_
216_
Problems_
6.5_
VI_I_
WAVELET_BASES_
220_
Orthogonal_Wavelet_Bases_'_
7._I_
1_
22_
7._I._I_Multiresolution_Approximations_
224_
7._I_.2_Scaling_Function_
228_
7._I_.3_Conjugate_Mirror_Filters_
235_
7._I_.4_In_Which_Orthogonal_Wavelets_Finally_Arrive_
241_
Classes_of_Wavelet_Bases_
'_
7.2_
24_
1_
7.2._I_Choosing_a_Wavelet_
246_
Shannon,_Meyer_and_Battle-LemariC_Wavelets_
7.2.2_
249_
7.2.3_
Daubechies_Compactly_Supported_Wavelets_
255_
Wavelets_and_Filter_Banks_
'_
7.3_
255_
7.3._I_Fast_Orthogonal_Wavelet_Transform_
259_
7.3.2_Perfect_Reconstruction_Filter_Banks_
263_
7.3.3_Biorthogonal_Bases_of_I2(Z)_
265_
7.4_Biorthogonal_Wavelet_Bases_
265_
Construction_of_Biorthogonal_Wavelet_Bases_
7.4._I_
268_
7.4.2_Biorthogonal_Wavelet_Design_
270_
7.4.3_Compactly_Supported_Biorthogonal_Wavelets_
273_
7.4.4_Lifting_Wavelets_
1_
28_
Wavelet_Bases_on_
an_Interval_7.5_
282_
7.5._I_Periodic_Wavelets_

xi_
CONTENTS_
7.5.2_Folded_Wavelets_
284_
7.5.3_Boundary_Wavelets_
286_
7.6_Multiscale_Interpolations_
293_
7.6._I_
Interpolation_and_Sampling_Theorems_
293_
7.6.2_Interpolation_Wavelet_Basis_
299_
7.7_Separable_Wavelet_Bases_'_
303_
7.7._I_Separable_Multiresolutions_
304_
7.7.2_Two-Dimensional_Wavelet_Bases_
306_
7.7.3_Fast_'ho-Dimensional_Wavelet_Transform_
3_10_
7.7.4_Wavelet_Bases_in_Higher_Dimensions_
313_
7.8_
Problems_
314_
VIII_
WAVELET_PACKET_AND_LOCAL_COSINE_BASES_
8._I_Wavelet_Packets_322_
8._I._I_Wavelet_Packet_Tree_322_
8._I_.2_Time-Frequency_Localization_327_
8._I_.3_Particular_Wavelet_Packet_Bases_333_
8._I_.4_Wavelet_Packet_Filter_Banks_336_
8.2_Image_Wavelet_Packets_339_
8.2._I_Wavelet_Packet_Quad-Tree_339_
8.2.2_Separable_Filter_Banks_341_
8.3_Block_Transforms_'_343_
8.3._I_Block_Bases_344_
8.3.2_Cosine_Bases_346_
8.3.3_Discrete_Cosine_Bases_349_
8.3.4_Fast_Discrete_Cosine_Transforms_350_
8.4_Lapped_Orthogonal_Transforms_353_
8.4._I_Lapped_Projectors_353_
8.4.2_Lapped_Orthogonal_Bases_359_
8.4.3_Local_Cosine_Bases_361_
8.4.4_Discrete_Lapped_Transforms_364_
8.5_Local_Cosine_Trees_368_
8.5._I_Binary_Tree_of_Cosine_Bases_369_
8.5.2_Tree_of_Discrete_Bases_37_1_
8.5.3_Image_Cosine_Quad-Tree_372_
8.6_Problems_374_

xii_CONTENTS_
IX_
AN_APPROXIMATION_TOUR_
9._I_Linear_Approximations_377_
377_
9._I._I_
Linear_Approximation_Error_
378_
9._I_.2_
Linear_Fourier_Approximations_
382_
Linear_Multiresolution_Approximations_
I_.3_
9._
3_85_
9._I_.4_Karhunen-Lo2ve_Approximations_
389_
9.2_Non-Linear_Approximations_
389_
9.2._I_Non-Linear_Approximation_Error_
391_
9.2.2_Wavelet_Adaptive_Grids_
394_
9.2.3_Besov_Spaces_
9.3_Image_Approximations_with_Wavelets_
398_
405_
9.4_Adaptive_Basis_Selection_
406_
Best_Basis_and_Schur_Concavity_
9.4._I_
41_
Fast_Best_Basis_Search_in_Trees_
9.4.2_1_
Wavelet_Packet_and_Local_Cosine_Best_Bases_
413_
9.4.3_
417_
9.5_Approximations_with_Pursuits_
418_
9.5._I_Basis_Pursuit_
42_
1_
9.5.2_Matching_Pursuit_
9.5.3_Orthogonal_Matching_Pursuit_
428_
430_
9.6_Problems_
X_
ESTIMATIONS_ARE_APPROXIMATIONS_
435_
IO._I_Bayes_Versus_Minimax_
IO._I._I_Bayes_Estimation_
435_
442_
IO._I_.2_Minimax_Estimation_
10.2_Diagonal_Estimation_in_a_Basis_
446_
10.2._I_Diagonal_Estimation_with_Oracles_
446_
10.2.2_Thresholding_Estimation_
450_
10.2.3_Thresholding_Refinements_
455_
I_0.2.4_Wavelet_Thresholding_
458_
10.2.5_Best_Basis_Thresholding_
466_
10.3_Minimax_Optimality_
469_
10.3._I_Linear_Diagonal_Minimax_Estimation_
469_
10.3.2_Orthosymmetric_Sets_
474_
10.3.3_Nearly_Minimax_with_Wavelets_
479_
10.4_Restoration_
486_
10.4._I_Estimation_in_Arbitrary_Gaussian_Noise_
486_
10.4.2_Inverse_Problems_and_Deconvolution_
49_
1_

xiii_
CONTENTS_
50_1_
10.5_Coherent_Estimation_
502_
10.5._I_Coherent_Basis_Thresholding_
505_
10.5.2_Coherent_Matching_Pursuit_
507_
10.6_Spectrum_Estimation_
508_
10.6._I_Power_Spectrum_
512_
10.6.2_Approximate_Karhunen-Lo&e_Search_
516_
10.6.3_Locally_Stationary_Processes_
520_
10.7_Problems_
XI_
TRANSFORM_CODING_
526_
I_I._I_Signal_Compression_
526_
11.1.1_StateoftheArt_
527_
I_I._I_.2_Compression_in_Orthonormal_Bases_
528_
I_I_.2_Distortion_Rate_of_Quantization_
529_
I_I_.2._I_Entropy_Coding_
531_
I_I_.2.2_Scalar_Quantization_
540_
I_I_.3_High_Bit_Rate_Compression_
540_
I_I_.3._I_Bit_Allocation_
542_
I_I_.3.2_Optimal_Basis_and_Karhunen-Lotwe_
544_
I_I_.3.3_Transparent_Audio_Code_
548_
I_I_.4_Image_Compression_
548_
I_I_.4._I_Deterministic_Distortion_Rate_
557_
I_I_.4.2_Wavelet_Image_Coding_
1_
56_
I_I_.4.3_Block_Cosine_Image_Coding_
566_
I_I_.4.4_Embedded_Transform_Coding_
57_1_
I_I_.4.5_Minimax_Distortion_Rate_
577_
I_I_.5_Video_Signals_
577_
optical_Mow_
I_I_.5._I_
585_
I_I_.5.2_MPEG_Video_Compression_
587_
11.6_Problems_
Appendix_A_
MATHEMATICAL_COMPLEMENTS_
1_
59_
A._I_Functions_and_Integration_
593_
A2_Banach_and_Hilbert_Spaces_
595_
A3_Bases_of_Hilbert_Spaces_
596_
A.4_Linear_Operators_
598_
A.5_Separable_Spaces_and_Bases_

XiV_CONTENTS_
599_
A6_Random_Vectors_and_Covariance_Operators_
1_
60_
A.7_Dims_
Appendix_B_
SOFTWARE_TOOLBOXES_
603_
B.1_WAVELAB_
609_
B.2_LASTWAVE_
610_
B.3_Freeware_Wavelet_Toolboxes_
BIBLIOGRAPHY_6_I2_
INDEX_629_

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再来张大封面：

谢谢分享。:30bb :30bb

谢分享。 {:7_1234:}

看过，感觉写的不错，就是看得中文的，翻译的不是特别到位

xuexizhong

xuexizhong

小波分析吗们谢谢

谢谢，学习中

大牛的书啊！

感谢分享！

好多个包呀，下载还是个体力活，感谢分享！

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