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.

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