图书简介
This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.
It explains how to use the Fourier matrix to extract frequency information from a digital signal and how to use circulant matrices to emphasize selected frequency ranges. It introduces discrete wavelet transforms for digital signals through the lifting method and illustrates through examples and computer explorations how these transforms are used in signal and image processing. Then the general theory of discrete wavelet transforms is developed via the matrix algebra of two-channel filter banks. Finally, wavelet transforms for analog signals are constructed based on filter bank results already presented, and the mathematical framework of multiresolution analysis is examined.
Key Features:
○ Accessible account of the theory and applications of discrete Fourier and wavelet transforms based on ten years of classroom use
○ Introduction of discrete wavelet transforms for digital signals via elementary lifting steps and filter banks
○ Interweaving of mathematical theory with examples and applications to digital signal processing and image compression
○ Computer explorations of signal and image processing in each chapter
○ Mathematical concepts clarified by more than 90 figures and 75 exercises with detailed solutions
Vector Space Models for Signals and Images; Vector Graphics and Animation; Inner Product Spaces and Fourier Series; Discrete Fourier Transform; Shift Operator and Circulant Matrices; Fast Fourier Transform; Discrete Wavelet Transforms via Lifting; Multiple Scale Haar Transform; Wavelet Bases; Two-Dimensional Discrete Wavelet Transforms; Perfect Reconstruction Filter Banks; Polyphase and Modulation Matrices; Filter Design; Lifting Step Factorization; Biorthogonal and Orthogonal Wavelet Transforms from Filter Banks; Daubechies Wavelet Transforms; Wavelet Transforms for Analog Signals; Scaling and Wavelet Functions from Filter Banks; Multiresolution Analysis of Analog Signals; A: Mathematical and Computational Tools; B: Solutions to Exercises
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