Discrete wavelet transform : a signal processing approach / D. Sundararajan.
Provides easy learning and understanding of DWT from a signal processing point of view Presents DWT from a digital signal processing point of view, in contrast to the usual mathematical approach, making it highly accessible Offers a comprehensive coverage of related topics, including convolution and...
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Full Text (via ProQuest) |
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| Format: | eBook |
| Language: | English |
| Published: |
Singapore :
John Wiley & Sons, Inc.,
[2015]
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| Subjects: |
MARC
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| 100 | 1 | |a Sundararajan, D., |e author. |0 http://id.loc.gov/authorities/names/no2005104467 |1 http://isni.org/isni/0000000122327563. | |
| 245 | 1 | 0 | |a Discrete wavelet transform : |b a signal processing approach / |c D. Sundararajan. |
| 264 | 1 | |a Singapore : |b John Wiley & Sons, Inc., |c [2015] | |
| 264 | 4 | |c ©2015. | |
| 300 | |a 1 online resource (ix, 323 pages) | ||
| 336 | |a text |b txt |2 rdacontent. | ||
| 337 | |a computer |b c |2 rdamedia. | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Cover; Title Page; Copyright; Contents; Preface; List of Abbreviations; Chapter 1 Introduction; 1.1 The Organization of This Book; Chapter 2 Signals; 2.1 Signal Classifications; 2.1.1 Periodic and Aperiodic Signals; 2.1.2 Even and Odd Signals; 2.1.3 Energy Signals; 2.1.4 Causal and Noncausal Signals; 2.2 Basic Signals; 2.2.1 Unit-Impulse Signal; 2.2.2 Unit-Step Signal; 2.2.3 The Sinusoid; 2.3 The Sampling Theorem and the Aliasing Effect; 2.4 Signal Operations; 2.4.1 Time Shifting; 2.4.2 Time Reversal; 2.4.3 Time Scaling; 2.5 Summary; Exercises; Chapter 3 Convolution and Correlation. | |
| 505 | 8 | |a 3.1 Convolution3.1.1 The Linear Convolution; 3.1.2 Properties of Convolution; 3.1.3 The Periodic Convolution; 3.1.4 The Border Problem; 3.1.5 Convolution in the DWT; 3.2 Correlation; 3.2.1 The Linear Correlation; 3.2.2 Correlation and Fourier Analysis; 3.2.3 Correlation in the DWT; 3.3 Summary; Exercises; Chapter 4 Fourier Analysis of Discrete Signals; 4.1 Transform Analysis; 4.2 The Discrete Fourier Transform; 4.2.1 Parseval's Theorem; 4.3 The Discrete-Time Fourier Transform; 4.3.1 Convolution; 4.3.2 Convolution in the DWT; 4.3.3 Correlation; 4.3.4 Correlation in the DWT. | |
| 505 | 8 | |a 4.3.5 Time Expansion4.3.6 Sampling Theorem; 4.3.7 Parseval's Theorem; 4.4 Approximation of the DTFT; 4.5 The Fourier Transform; 4.6 Summary; Exercises; Chapter 5 The z-Transform; 5.1 The z-Transform; 5.2 Properties of the z-Transform; 5.2.1 Linearity; 5.2.2 Time Shift of a Sequence; 5.2.3 Convolution; 5.3 Summary; Exercises; Chapter 6 Finite Impulse Response Filters; 6.1 Characterization; 6.1.1 Ideal Lowpass Filters; 6.1.2 Ideal Highpass Filters; 6.1.3 Ideal Bandpass Filters; 6.2 Linear Phase Response; 6.2.1 Even-Symmetric FIR Filters with Odd Number of Coefficients. | |
| 505 | 8 | |a 6.2.2 Even-Symmetric FIR Filters with Even Number of Coefficients6.3 Summary; Exercises; Chapter 7 Multirate Digital Signal Processing; 7.1 Decimation; 7.1.1 Downsampling in the Frequency-Domain; 7.1.2 Downsampling Followed by Filtering; 7.2 Interpolation; 7.2.1 Upsampling in the Frequency-Domain; 7.2.2 Filtering Followed by Upsampling; 7.3 Two-Channel Filter Bank; 7.3.1 Perfect Reconstruction Conditions; 7.4 Polyphase Form of the Two-Channel Filter Bank; 7.4.1 Decimation; 7.4.2 Interpolation; 7.4.3 Polyphase Form of the Filter Bank; 7.5 Summary; Exercises. | |
| 505 | 8 | |a Chapter 8 The Haar Discrete Wavelet Transform8.1 Introduction; 8.1.1 Signal Representation; 8.1.2 The Wavelet Transform Concept; 8.1.3 Fourier and Wavelet Transform Analyses; 8.1.4 Time-Frequency Domain; 8.2 The Haar Discrete Wavelet Transform; 8.2.1 The Haar DWT and the 2-Point DFT; 8.2.2 The Haar Transform Matrix; 8.3 The Time-Frequency Plane; 8.4 Wavelets from the Filter Coefficients; 8.4.1 Two Scale Relations; 8.5 The 2-D Haar Discrete Wavelet Transform; 8.6 Discontinuity Detection; 8.7 Summary; Exercises; Chapter 9 Orthogonal Filter Banks; 9.1 Haar Filter; 9.2 Daubechies Filter. | |
| 520 | |a Provides easy learning and understanding of DWT from a signal processing point of view Presents DWT from a digital signal processing point of view, in contrast to the usual mathematical approach, making it highly accessible Offers a comprehensive coverage of related topics, including convolution and correlation, Fourier transform, FIR filter, orthogonal and biorthogonal filters Organized systematically, starting from the fundamentals of signal processing to the more advanced topics of DWT and Discrete Wavelet Packet Transform. Written in a clear and concise manner with abundant examples, fi. | ||
| 588 | 0 | |a Vendor-supplied metadata. | |
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| 650 | 0 | |a Image processing |x Mathematics. |0 http://id.loc.gov/authorities/subjects/sh2009126758. | |
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| 650 | 7 | |a Signal processing |x Digital techniques |x Mathematics. |2 fast |0 (OCoLC)fst01118294. | |
| 650 | 7 | |a Wavelets (Mathematics) |2 fast |0 (OCoLC)fst01172896. | |
| 655 | 0 | |a Electronic book. | |
| 776 | 0 | 8 | |i Print version: |a Sundararajan, D. |t Discrete Wavelet Transform : A Signal Processing Approach. |d Hoboken : Wiley, ©2015 |z 9781119046066. |
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