Digital Signal Processing

Höfundur: Mitra (Útgáfa: 4)
Digital Signal Processing

Kaup valmöguleikar

Digital Signal Processing: A Computer-Based Approach is intended for a two-semester course on digital signal processing for seniors or first-year graduate students. The prerequisite for this book is a junior-level course in linear continuous-time and discrete-time systems, which is usually required in most universities. A key feature of this book is the extensive use of MATLAB-based examples that illustrate the program's powerful capability to solve signal processing problems.

Practical examples and applications bring the theory to life. This popular book introduces the tools used in the analysis and design of discrete-time systems for signal processing.

Nánar um bókina

Útgefandi
McGraw-Hill UK
ISBN
0077159705
Print ISBN
9780071289467
Format
Page Fidelity (PDF)
Útgáfa
4
Höfundar
Mitra
Tungumál
English
Útgefið
Prent takmörkun á líftíma
100
Prent takmörkun
2
Afritunar takmörkun
2

Kaflar

  • Copyright
  • About the Author
  • Preface
  • Acknowledgements
  • Chapter 1 Signals and Signal Processing
  • 1.1 Characterization and Classification of Signals
  • 1.2 Typical Signal Processing Operations
  • 1.3 Examples of Typical Signals
  • 1.4 Typical Signal Processing Applications
  • 1.5 Why Digital Signal Processing?
  • Chapter 2 Discrete-Time Signals in the Time Domain
  • 2.1 Time-Domain Representation
  • 2.2 Operations on Sequences
  • 2.3 Operations on Finite-Length Sequences
  • 2.4 Typical Sequences and Sequence Representation
  • 2.5 The Sampling Process
  • 2.6 Correlation of Signals
  • 2.7 Random Signals
  • 2.8 Summary
  • 2.9 Problems
  • 2.10 MATLAB Exercises
  • Chapter 3 Discrete-Time Signals in the Frequency Domain
  • 3.1 The Continuous-Time Fourier Transform
  • 3.3 Discrete-Time Fourier Transform Theorems
  • 3.4 Energy Density Spectrum of a Discrete-Time Sequence
  • 3.5 Band-Limited Discrete-Time Signals
  • 3.6 DTFT Computation Using MATLAB
  • 3.7 The Unwrapped Phase Function
  • 3.8 Digital Processing of Continuous-Time Signals
  • 3.9 Sampling of Bandpass Signals
  • 3.10 Effect of Sample-and-Hold Operation
  • 3.11 Summary
  • 3.12 Problems
  • 3.13 MATLAB Exercises
  • Chapter 4 Discrete-Time Systems
  • 4.1 Discrete-Time System Examples
  • 4.2 Classification of Discrete-Time Systems
  • 4.3 Impulse and Step Responses
  • 4.4 Time-Domain Characterization of LTI Discrete-Time Systems
  • 4.5 Simple Interconnection Schemes
  • 4.6 Finite-Dimensional LTI Discrete-Time Systems
  • 4.7 Classification of LTI Discrete-Time Systems
  • 4.8 Frequency-Domain Representations of LTI Discrete-Time Systems
  • 4.9 Phase and Group Delays
  • 4.10 Summary
  • 4.11 Problems
  • 4.12 MATLAB Exercises
  • Chapter 5 Finite-Length Discrete Transforms
  • 5.1 Orthogonal Transforms
  • 5.2 The Discrete Fourier Transform
  • 5.3 Relation Between the DTFT and the DFT and Their Inverses
  • 5.4 Circular Convolution
  • 5.5 Classifications of Finite-Length Sequences
  • 5.6 DFT Symmetry Relations
  • 5.7 Discrete Fourier Transform Theorems
  • 5.8 Fourier-Domain Filtering
  • 5.9 Computation of the DFT of Real Sequences
  • 5.10 Linear Convolution Using the DFT
  • 5.11 Short-Time Fourier Transform
  • 5.12 Discrete Cosine Transform
  • 5.13 The Haar Transform
  • 5.14 Energy Compaction Properties
  • 5.15 Summary
  • 5.16 Problems
  • 5.17 MATLAB Exercises
  • Chapter 6 z-Transform
  • 6.1 Definition
  • 6.2 Rational z-Transforms
  • 6.3 Region of Convergence of a Rational z-Transform
  • 6.4 The Inverse z-Transform
  • 6.5 z-Transform Theorems
  • 6.6 Computation of the Convolution Sum of Finite-Length Sequences
  • 6.7 The Transfer Function
  • 6.8 Summary
  • 6.9 Problems
  • 6.10 MATLAB Exercises
  • Chapter 7 LTI Discrete-Time Systems in the Transform Domain
  • 7.1 Transfer Function Classification Based on Magnitude Characteristics
  • 7.2 Transfer Function Classification Based on Phase Characteristics
  • 7.3 Types of Linear-Phase FIR Transfer Functions
  • 7.4 Simple Digital Filters
  • 7.5 Complementary Transfer Functions
  • 7.6 Inverse Systems
  • 7.7 System Identification
  • 7.8 Digital Two-Pairs
  • 7.9 Algebraic Stability Test
  • 7.10 Summary
  • 7.11 Problems
  • 7.12 MATLAB Exercises
  • Chapter 8 Digital Filter Structures
  • 8.1 Block Diagram Representation
  • 8.2 Equivalent Structures
  • 8.3 Basic FIR Digital Filter Structures
  • 8.4 Basic IIR Digital Filter Structures
  • 8.5 Realization of Basic Structures Using MATLAB
  • 8.6 Allpass Filters
  • 8.7 Parametrically Tunable Low-Order IIR Digital Filter Pairs
  • 8.8 IIR Tapped Cascaded Lattice Structures
  • 8.9 FIR Cascaded Lattice Structures
  • 8.10 Parallel Allpass Realization of IIR Transfer Functions
  • 8.11 Tunable High-Order Digital Filters
  • 8.12 Computational Complexity of Digital Filter Structures
  • 8.13 Summary
  • 8.14 Problems
  • 8.15 MATLAB Exercises
  • Chapter 9 IIR Digital Filter Design
  • 9.1 Preliminary Considerations
  • 9.2 Bilinear TransformationMethod of IIR Filter Design
  • 9.3 Design of Lowpass IIR Digital Filters
  • 9.4 Design of Highpass, Bandpass, and Bandstop IIR Digital Filters
  • 9.5 Spectral Transformations of IIR Filters
  • 9.6 IIR Digital Filter Design Using MATLAB
  • 9.7 Computer-Aided Design of IIR Digital Filters
  • 9.8 Summary
  • 9.9 Problems
  • 9.10 MATLAB Exercises
  • Chapter 10 FIR Digital Filter Design
  • 10.1 Preliminary Considerations
  • 10.2 FIR Filter Design Based on Windowed Fourier Series
  • 10.3 Computer-Aided Design of Equiripple Linear-Phase FIR Filters
  • 10.4 Design of Minimum-Phase FIR Filters
  • 10.5 FIR Digital Filter Design Using MATLAB
  • 10.6 Design of Computationally Efficient FIR Digital Filters
  • 10.7 Summary
  • 10.8 Problems
  • 10.9 MATLAB Exercises
  • Chapter 11 DSP Algorithm Implementation
  • 11.1 Basic Issues
  • 11.2 Structure Simulation and Verification Using MATLAB
  • 11.3 Computation of the Discrete Fourier Transform
  • 11.4 Fast DFT Algorithms Based on Index Mapping
  • 11.5 DFT and IDFT Computation Using MATLAB
  • 11.6 Sliding Discrete Fourier Transform
  • 11.7 DFT Computation over a Narrow Frequency Band
  • 11.8 Number Representation
  • 11.9 Handling of Overflow
  • 11.10 Summary
  • 11.11 Problems
  • 11.12 MATLAB Exercises
  • Chapter 12 Analysis of FiniteWordlength Effects
  • 12.1 The Quantization Process and Errors
  • 12.2 Quantization of Fixed-Point Numbers
  • 12.3 Quantization of Floating-Point Numbers
  • 12.4 Analysis of Coefficient Quantization Effects
  • 12.5 A/D Conversion Noise Analysis
  • 12.6 Analysis of Arithmetic Round-Off Errors
  • 12.7 Dynamic Range Scaling
  • 12.8 Signal-to-Noise Ratio in Low-Order IIR Filters
  • 12.9 Low-Sensitivity Digital Filters
  • 12.10 Reduction of Product Round-Off Noise Using Error Feedback
  • 12.11 Limit Cycles in IIR Digital Filters
  • 12.12 Round-Off Errors in FFT Algorithms
  • 12.13 Summary
  • 12.14 Problems
  • 12.15 MATLAB Exercises
  • Chapter 13 Multirate Digital Signal Processing Fundamentals
  • 13.1 The Basic Sampling Rate Alteration Devices
  • 13.2 Multirate Structures for Sampling Rate Conversion
  • 13.3 Multistage Design of Decimator and Interpolator
  • 13.4 The Polyphase Decomposition
  • 13.5 Arbitrary-Rate Sampling Rate Converter
  • 13.6 Nyquist Filters
  • 13.7 CIC Decimators and Interpolators
  • 13.8 Summary
  • 13.9 Problems
  • 13.10 Matlab Exercises
  • Chapter 14 Multirate Filter Banks and Wavelets
  • 14.1 Digital Filter Banks
  • 14.2 Two-Channel Quadrature-Mirror Filter Bank
  • 14.3 Perfect Reconstruction Two-Channel FIR Filter Banks
  • 14.4 L-Channel QMF Banks
  • 14.5 Multilevel Filter Banks
  • 14.6 Discrete Wavelet Transform
  • 14.7 Summary
  • 14.8 Problems
  • 14.9 MATLAB Exercises
  • Appendix A Analog Lowpass Filter Design
  • A.1 Analog Filter Specifications
  • A.2 Butterworth Approximation
  • A.3 Chebyshev Approximation
  • A.4 Elliptic Approximation
  • A.5 Linear-Phase Approximation
  • A.6 Analog Filter Design Using MATLAB
  • A.7 Analog Lowpass Filter Design Examples
  • A.8 A Comparison of the Filter Types
  • A.9 Anti-Aliasing Filter Design
  • A.10 Reconstruction Filter Design
  • Appendix B Design of Analog Highpass, Bandpass, and Bandstop Filters
  • B.1 Analog Highpass Filter Design
  • B.2 Analog Bandpass Filter Design
  • B.3 Analog Bandstop Filter Design
  • Appendix C Discrete-Time Random Signals
  • C.1 Statistical Properties of a Random Variable
  • C.2 Statistical Properties of a Random Signal
  • C.3 Wide-Sense Stationary Random Signal
  • C.4 Concept of Power in a Random Signal
  • C.5 Ergodic Signal
  • C.6 Transform-Domain Representations of Random Signals
  • C.7 White Noise
  • C.8 Discrete-Time Processing of Random Signals
  • Bibliography
  • Index