Unser bisheriger Preis:ORGPRICE: 80,24 EUR

Jetzt 72,22 EUR*

Alle Preise inkl. MwSt.
| zzgl. Versand

9781402066283

Buch

01.09.2010

423

Kamisetty Rao

796 g

239x164x30 mm

Signals and Communication Technology

Englisch

This book presents an introduction to the principles of the fast Fourier transform. The book covers FFTs, frequency domain filtering, and applications to video and audio signal processing. It feeds the demand for an updated book reflecting the various developments in FFT and its applications, and it fills the need from instructors and students for a book dealing with the latest FFT topics. It also has adopted modern approaches like MATLAB examples and projects for better understanding of diverse FFTs. The emphasis of the book is on the foundation of FFTs such as the decimation-in-time FFT, decimation-in-frequency FFT algorithms, integer FFT, prime factor DFT and so on. It includes references to books, review papers, lists of applications, hardware/software, and useful websites.

This book presents an introduction to the principles of the fast Fourier transform. The book covers FFTs, frequency domain filtering, and applications to video and audio signal processing. It feeds the demand for an updated book reflecting the various developments in FFT and its applications, and it fills the need from instructors and students for a book dealing with the latest FFT topics. It also has adopted modern approaches like MATLAB examples and projects for better understanding of diverse FFTs. The emphasis of the book is on the foundation of FFTs such as the decimation-in-time FFT, decimation-in-frequency FFT algorithms, integer FFT, prime factor DFT and so on. It includes references to books, review papers, lists of applications, hardware/software, and useful websites.

Preface. Acknowledgements. Acronyms.

1 Introduction. 1.1 Applications of Discrete Fourier Transform.

2 Discrete Fourier Transform. 2.1 Definitions. 2.2 The Z-transform. 2.3 Properties of the DFT. 2.4 Convolution Theorem. 2.5 Correlation Theorem. 2.6 Overlap-Add and Overlap-Save Methods. 2.7 Zero Padding in the Data Domain. 2.8 Computation of DFTs of Two Real Sequences Using One Complex FFT. 2.9 A circulant matrix is diagonalized by the DFT matrix. 2.10 Summary. Projects. Problems.

3 Fast Algorithms. 3.1 Radix-2 DIT-FFT. 3.2 Fast Algorithms by Sparse Matrix Factorization. 3.3 Radix-2 DIF-FFT. 3.4 Radix-3 DIT-FFT. 3.5 Radix-3 DIF-FFT. 3.6 FFT for N a Composite Number. 3.7 Radix-4 DIT-FFT. 3.8 Radix-4 DIF-FFT. 3.9 Split-Radix FFT Algorithm. 3.10 Fast Fourier and BIFORE Transforms by Matrix Partitioning. 3.11 The Winograd Fourier Transform Algorithm. 3.12 Sparse Factorization of the DFT Matrix. 3.13 Unified Discrete Fourier-Hartley Transform. 3.14 Bluestein's FFT Algorithm. 3.15 Rader Prime Algorithm. 3.16 Summary. Projects. Problems.

4 Integer Fast Fourier Transform. 4.1 Introduction. 4.2 Lifting Scheme. 4.3 Integer FFT. 4.4 Integer Discrete Fourier Transform. 4.5 Summary. Projects. Problems.

5 Two-Dimensional Discrete Fourier Transform. 5.1 Definitions. 5.2 Properties. 5.3 Two-Dimensional Filtering. 5.4 Inverse and Wiener Filtering. 5.5 Three-Dimensional DFT. 5.6 Variance Distribution in the 1-D DFT Domain. 5.7 Sum of variances under orthogonal transformation is invariant. 5.8 Variance Distribution in the 2-D DFT Domain. 5.9 Quantization of transform coefficients can be based on their variances. 5.10 Maximum Variance Zonal Sampling (MVZS). 5.11 Geometrical Zonal Sampling (GZS). 5.12 Summary. Projects. Problems.

6 Vector-Radix 2-D FFT Algorithm. 6.1 Vector Radix DIT-FFT. 6.2 Vector Radix DIF-FFT. 6.3 Summary. Projects. Problems.

7 Nonuniform DFT. 7.1 Introduction. 7.2 One-Dimensional NDFT. 7.3 Fast Computation of NDFT. 7.4 Two-Dimensional NDFT. 7.5 Filter Design Using NDFT. 7.6 Summary. Problems.

8 Applications. 8.1 Frequency Domain Downsampling. 8.2 Fractal Image Compression. 8.3 Phase Only Correlation. 8.4 Image Rotation and Translation Using DFT/FFT. 8.5 Intraframe Error Concealment. 8.6 Surface Texture Analysis. 8.7 FFT-Based Ear Model. 8.8 Image Watermarking. 8.9 Audio Watermarking. 8.10 OFDM. 8.11 FFT Processors for OFDM. 8.12 DF DFT-Based Channel Estimation Method. 8.13 The Conjugate-Gradient Fast Fourier Transform (CG-FFT). 8.14 Modified Discrete Cosine Transform (MDCT). 8.15 Oddly Stacked TDAC. 8.16 Preceptual Transform Audio Coder. 8.17 OCF Coder. 8.18 NMR Measurement System. 8.19 Audio Coder for Mobile Reception. 8.20 ASPEC. 8.21 RELP Vocoder. 8.22 Homomorphic Vocoders. 8.23 MUSICAM. 8.24 AC-2 Audio Coder. 8.25 IMDCT/IMDST Implementation via IFFT. 8.26 MDCT/MDST Implementation via IFFT. 8.27 Autocorrelation Function and Power Density Spectrum. 8.28 Three-Dimensional Face Recognition. 8.29 Two-Dimensional Multirate Processing. 8.30 Fast Uniform Discrete Curvelet Transform. 8.31 Problems. 8.32 Projects.

Appendix A: Performance Comparison of Various Discrete Transforms. A.1 Transform Coding Gain. A.2 Variance Distribution in the Transform Domain. A.3 Normalized MSE. A.4 Rate Versus Distortion. A.5 Residual Correlation. A.6 Scalar Wiener Filtering. A.7 Geometrical Zonal Sampling. A.8 Maximum Variance Zonal Sampling.

Appendix B: Spectral Distance Measures of Image Quality. Project B.

Appendix C: Integer Discrete Cosine Transform. C.1 Integer DCT Via Lifting. C.2 Integer DCT by the Principle of Dyadic Symmetry. Problems. Projects.

Appendix D: DCT and DST. D.1 Kernels for DCT and DST. D.2 Derivation of Unitary DCTs and DSTs. D.3 Circular Convolution Using DCTs and DSTs Instead of FFTs. D.4 Circular Shifting Property of the DCT. Problems. Projects.

Appendix E: Kronecker Products and Separability. E.1 Kronecker Products. E.2 Generalized Kronecker Product. E.3 Separable Transformation.

A

1 Introduction. 1.1 Applications of Discrete Fourier Transform.

2 Discrete Fourier Transform. 2.1 Definitions. 2.2 The Z-transform. 2.3 Properties of the DFT. 2.4 Convolution Theorem. 2.5 Correlation Theorem. 2.6 Overlap-Add and Overlap-Save Methods. 2.7 Zero Padding in the Data Domain. 2.8 Computation of DFTs of Two Real Sequences Using One Complex FFT. 2.9 A circulant matrix is diagonalized by the DFT matrix. 2.10 Summary. Projects. Problems.

3 Fast Algorithms. 3.1 Radix-2 DIT-FFT. 3.2 Fast Algorithms by Sparse Matrix Factorization. 3.3 Radix-2 DIF-FFT. 3.4 Radix-3 DIT-FFT. 3.5 Radix-3 DIF-FFT. 3.6 FFT for N a Composite Number. 3.7 Radix-4 DIT-FFT. 3.8 Radix-4 DIF-FFT. 3.9 Split-Radix FFT Algorithm. 3.10 Fast Fourier and BIFORE Transforms by Matrix Partitioning. 3.11 The Winograd Fourier Transform Algorithm. 3.12 Sparse Factorization of the DFT Matrix. 3.13 Unified Discrete Fourier-Hartley Transform. 3.14 Bluestein's FFT Algorithm. 3.15 Rader Prime Algorithm. 3.16 Summary. Projects. Problems.

4 Integer Fast Fourier Transform. 4.1 Introduction. 4.2 Lifting Scheme. 4.3 Integer FFT. 4.4 Integer Discrete Fourier Transform. 4.5 Summary. Projects. Problems.

5 Two-Dimensional Discrete Fourier Transform. 5.1 Definitions. 5.2 Properties. 5.3 Two-Dimensional Filtering. 5.4 Inverse and Wiener Filtering. 5.5 Three-Dimensional DFT. 5.6 Variance Distribution in the 1-D DFT Domain. 5.7 Sum of variances under orthogonal transformation is invariant. 5.8 Variance Distribution in the 2-D DFT Domain. 5.9 Quantization of transform coefficients can be based on their variances. 5.10 Maximum Variance Zonal Sampling (MVZS). 5.11 Geometrical Zonal Sampling (GZS). 5.12 Summary. Projects. Problems.

6 Vector-Radix 2-D FFT Algorithm. 6.1 Vector Radix DIT-FFT. 6.2 Vector Radix DIF-FFT. 6.3 Summary. Projects. Problems.

7 Nonuniform DFT. 7.1 Introduction. 7.2 One-Dimensional NDFT. 7.3 Fast Computation of NDFT. 7.4 Two-Dimensional NDFT. 7.5 Filter Design Using NDFT. 7.6 Summary. Problems.

8 Applications. 8.1 Frequency Domain Downsampling. 8.2 Fractal Image Compression. 8.3 Phase Only Correlation. 8.4 Image Rotation and Translation Using DFT/FFT. 8.5 Intraframe Error Concealment. 8.6 Surface Texture Analysis. 8.7 FFT-Based Ear Model. 8.8 Image Watermarking. 8.9 Audio Watermarking. 8.10 OFDM. 8.11 FFT Processors for OFDM. 8.12 DF DFT-Based Channel Estimation Method. 8.13 The Conjugate-Gradient Fast Fourier Transform (CG-FFT). 8.14 Modified Discrete Cosine Transform (MDCT). 8.15 Oddly Stacked TDAC. 8.16 Preceptual Transform Audio Coder. 8.17 OCF Coder. 8.18 NMR Measurement System. 8.19 Audio Coder for Mobile Reception. 8.20 ASPEC. 8.21 RELP Vocoder. 8.22 Homomorphic Vocoders. 8.23 MUSICAM. 8.24 AC-2 Audio Coder. 8.25 IMDCT/IMDST Implementation via IFFT. 8.26 MDCT/MDST Implementation via IFFT. 8.27 Autocorrelation Function and Power Density Spectrum. 8.28 Three-Dimensional Face Recognition. 8.29 Two-Dimensional Multirate Processing. 8.30 Fast Uniform Discrete Curvelet Transform. 8.31 Problems. 8.32 Projects.

Appendix A: Performance Comparison of Various Discrete Transforms. A.1 Transform Coding Gain. A.2 Variance Distribution in the Transform Domain. A.3 Normalized MSE. A.4 Rate Versus Distortion. A.5 Residual Correlation. A.6 Scalar Wiener Filtering. A.7 Geometrical Zonal Sampling. A.8 Maximum Variance Zonal Sampling.

Appendix B: Spectral Distance Measures of Image Quality. Project B.

Appendix C: Integer Discrete Cosine Transform. C.1 Integer DCT Via Lifting. C.2 Integer DCT by the Principle of Dyadic Symmetry. Problems. Projects.

Appendix D: DCT and DST. D.1 Kernels for DCT and DST. D.2 Derivation of Unitary DCTs and DSTs. D.3 Circular Convolution Using DCTs and DSTs Instead of FFTs. D.4 Circular Shifting Property of the DCT. Problems. Projects.

Appendix E: Kronecker Products and Separability. E.1 Kronecker Products. E.2 Generalized Kronecker Product. E.3 Separable Transformation.

A

Fast Fourier Transform - Algorithms and Applications presents an introduction to the principles of the fast Fourier transform (FFT). It covers FFTs, frequency domain filtering, and applications to video and audio signal processing.As fields like communications, speech and image processing, and related areas are rapidly developing, the FFT as one of the essential parts in digital signal processing has been widely used. Thus there is a pressing need from instructors and students for a book dealing with the latest FFT topics.

Fast Fourier Transform - Algorithms and Applications provides a thorough and detailed explanation of important or up-to-date FFTs. It also has adopted modern approaches like MATLAB examples and projects for better understanding of diverse FFTs.

Fast Fourier Transform - Algorithms and Applications is designed for senior undergraduate and graduate students, faculty, engineers, and scientists in the field, and self-learners to understand FFTs and directly apply them to their fields, efficiently. It is designed to be both a text and a reference. Thus examples, projects and problems all tied with MATLAB, are provided for grasping the concepts concretely. It also includes references to books and review papers and lists of applications, hardware/software, and useful websites. By including many figures, tables, bock diagrams and graphs, this book helps the reader understand the concepts of fast algorithms readily and intuitively. It provides new MATLAB functions and MATLAB source codes.

The material in Fast Fourier Transform - Algorithms and Applications is presented without assuming any prior knowledge of FFT. This book is for any professional who wants to have a basic understanding of the latest developments in and applications of FFT. It provides a good reference for any engineer planning to work in this field, either in basic implementation or in research and development.

Fast Fourier Transform - Algorithms and Applications provides a thorough and detailed explanation of important or up-to-date FFTs. It also has adopted modern approaches like MATLAB examples and projects for better understanding of diverse FFTs.

Fast Fourier Transform - Algorithms and Applications is designed for senior undergraduate and graduate students, faculty, engineers, and scientists in the field, and self-learners to understand FFTs and directly apply them to their fields, efficiently. It is designed to be both a text and a reference. Thus examples, projects and problems all tied with MATLAB, are provided for grasping the concepts concretely. It also includes references to books and review papers and lists of applications, hardware/software, and useful websites. By including many figures, tables, bock diagrams and graphs, this book helps the reader understand the concepts of fast algorithms readily and intuitively. It provides new MATLAB functions and MATLAB source codes.

The material in Fast Fourier Transform - Algorithms and Applications is presented without assuming any prior knowledge of FFT. This book is for any professional who wants to have a basic understanding of the latest developments in and applications of FFT. It provides a good reference for any engineer planning to work in this field, either in basic implementation or in research and development.