Digital Signal Processing Principles, Algorithms, and Applications

ISBN-10: 0131873741

ISBN-13: 9780131873742

Edition: 4th 2007 (Revised)

List price: $244.20
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A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing.
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Book details

List price: $244.20
Edition: 4th
Copyright year: 2007
Publisher: Prentice Hall PTR
Publication date: 3/28/2006
Binding: Paperback
Pages: 1004
Size: 7.25" wide x 9.25" long x 1.75" tall
Weight: 4.180
Language: English

Signals, Systems, and Signal Processing
Basic Elements of a Digital Signal Processing System
Advantages of Digital over Analog Signal Processing
Classification of Signals
Multichannel and Multidimensional Signals
Continuous-Time Versus Discrete-Time Signals
Continuous-Valued Versus Discrete-Valued Signals
Deterministic Versus Random Signals
The Concept of Frequency in Continuous-Time and Discrete-Time Signals
Continuous-Time Sinusoidal Signals
Discrete-Time Sinusoidal Signals
Harmonically Related Complex Exponentials
Analog-to-Digital and Digital-to-Analog Conversion
Sampling of Analog Signals
The Sampling Theorem
Quantization of Continuous-Amplitude Signals
Quantization of Sinusoidal Signals
Coding of Quantized Samples
Digital-to-Analog Conversion
Analysis of Digital Signals and Systems Versus Discrete-Time Signals and Systems
Summary and References
Discrete-Time Signals and Systems
Discrete-Time Signals
Some Elementary Discrete-Time Signals
Classification of Discrete-Time Signals
Simple Manipulations of Discrete-Time Signals
Discrete-Time Systems
Input-Output Description of Systems
Block Diagram Representation of Discrete-Time Systems
Classification of Discrete-Time Systems
Interconnection of Discrete-Time Systems
Analysis of Discrete-Time Linear Time-Invariant Systems
Techniques for the Analysis of Linear Systems
Resolution of a Discrete-Time Signal into Impulses
Response of LTI Systems to Arbitrary Inputs: The Convolution Sum
Properties of Convolution and the Interconnection of LTI Systems
Causal Linear Time-Invariant Systems
Stability of Linear Time-Invariant Systems
Systems with Finite-Duration and Infinite-Duration Impulse Response
Discrete-Time Systems Described by Difference Equations
Recursive and Nonrecursive Discrete-Time Systems
Linear Time-Invariant Systems Characterized by Constant-Coefficient Difference Equations
Solution of Linear Constant-Coefficient Difference Equations
The Impulse Response of a Linear Time-Invariant Recursive System
Implementation of Discrete-Time Systems
Structures for the Realization of Linear Time-Invariant Systems
Recursive and Nonrecursive Realizations of FIR Systems
Correlation of Discrete-Time Signals
Crosscorrelation and Autocorrelation Sequences
Properties of the Autocorrelation and Crosscorrelation Sequences
Correlation of Periodic Sequences
Input-Output Correlation Sequences
Summary and References
The z-Transform and Its Application to the Analysis of LTI Systems
The z-Transform
The Direct z-Transform
The Inverse z-Transform
Properties of the z-Transform
Rational z-Transforms
Poles and Zeros
Pole Location and Time-Domain Behavior for Causal Signals
The System Function of a Linear Time-Invariant System
Inversion of the z-Transform
The Inverse z-Transform by Contour Integration
The Inverse z-Transform by Power Series Expansion
The Inverse z-Transform by Partial-Fraction Expansion
Decomposition of Rational z-Transforms
Analysis of Linear Time-Invariant Systems in the z-Domain
Response of Systems with Rational System Functions
Transient and Steady-State Responses
Causality and Stability
Pole-Zero Cancellations
Multiple-Order Poles and Stability
Stability of Second-Order Systems
The One-sided z-Transform
Definition and Properties
Solution of Difference Equations
Response of Pole-Zero Systems with Nonzero Initial Conditions
Summary and References
Frequency Analysis of Signals
Frequency Analysis of Continuous-Time Signals
The Fourier Series for Continuous-Time Periodic Signals
Power Density Spectrum of Periodic Signals
The Fourier Transform for Continuous-Time Aperiodic Signals
Energy Density Spectrum of Aperiodic Signals
Frequency Analysis of Discrete-Time Signals
The Fourier Series for Discrete-Time Periodic Signals
Power Density Spectrum of Periodic Signals
The Fourier Transform of Discrete-Time Aperiodic Signals
Convergence of the Fourier Transform
Energy Density Spectrum of Aperiodic Signals
Relationship of the Fourier Transform to the z-Transform
The Cepstrum
The Fourier Transform of Signals with Poles on the Unit Circle
Frequency-Domain Classification of Signals: The Concept of Bandwidth
The Frequency Ranges of Some Natural Signals
Frequency-Domain and Time-Domain Signal Properties
Properties of the Fourier Transform for Discrete-Time Signals
Symmetry Properties of the Fourier Transform
Fourier Transform Theorems and Properties
Summary and References
Frequency-Domain Analysis of LTI Systems
Frequency-Domain Characteristics of Linear Time-Invariant Systems
Response to Complex Exponential and Sinusoidal Signals: The Frequency Response Function
Steady-State and Transient Response to Sinusoidal Input Signals
Steady-State Response to Periodic Input Signals
Response to Aperiodic Input Signals
Frequency Response of LTI Systems
Frequency Response of a System with a Rational System Function
Computation of the Frequency Response Function
Correlation Functions and Spectra at the Output of LTI Systems
Input-Output Correlation Functions and Spectra
Correlation Functions and Power Spectra for Random Input Signals
Linear Time-Invariant Systems as Frequency-Selective Filters
Ideal Filter Characteristics
Lowpass, Highpass, and Bandpass Filters
Digital Resonators
Notch Filters
Comb Filters
All-Pass Filters
Digital Sinusoidal Oscillators
Inverse Systems and Deconvolution
Invertibility of Linear Time-Invariant Systems
Minimum-Phase, Maximum-Phase, and Mixed-Phase Systems
System Identification and Deconvolution
Homomorphic Deconvolution
Summary and References
Sampling and Reconstruction of Signals
Ideal Sampling and Reconstruction of Continuous-Time Signals
Discrete-Time Processing of Continuous-Time Signals
Analog-to-Digital and Digital-to-Analog Converters
Analog-to-Digital Converters
Quantization and Coding
Analysis of Quantization Errors
Digital-to-Analog Converters
Sampling and Reconstruction of Continuous-Time Bandpass Signals
Uniform or First-Order Sampling
Interleaved or Nonuniform Second-Order Sampling
Bandpass Signal Representations
Sampling Using Bandpass Signal Representations
Sampling of Discrete-Time Signals
Sampling and Interpolation of Discrete-Time Signals
Representation and Sampling of Bandpass Discrete-Time Signals
Oversampling A/D and D/A Converters
Oversampling A/D Converters
Oversampling D/A Converters
Summary and References
The Discrete Fourier Transform: Its Properties and Applications
Frequency-Domain Sampling: The Discrete Fourier Transform
Frequency-Domain Sampling and Reconstruction of Discrete-Time Signals
The Discrete Fourier Transform (DFT)
The DFT as a Linear Transformation
Relationship of the DFT to Other Transforms
Properties of the DFT
Periodicity, Linearity, and Symmetry Properties
Multiplication of Two DFTs and Circular Convolution
Additional DFT Properties
Linear Filtering Methods Based on the DFT
Use of the DFT in Linear Filtering
Filtering of Long Data Sequences
Frequency Analysis of Signals Using the DFT
The Discrete Cosine Transform
Forward DCT
Inverse DCT
DCT as an Orthogonal Transform
Summary and References
Efficient Computation of the DFT: Fast Fourier Transform Algorithms
Efficient Computation of the DFT: FFT Algorithms
Direct Computation of the DFT
Divide-and-Conquer Approach to Computation of the DFT
Radix-2 FFT Algorithms
Radix-4 FFT Algorithms
Split-Radix FFT Algorithms
Implementation of FFT Algorithms
Applications of FFT Algorithms
Efficient Computation of the DFT of Two Real Sequences
Efficient Computation of the DFT of a 2N-Point Real Sequence
Use of the FFT Algorithm in Linear Filtering and Correlation
A Linear Filtering Approach to Computation of the DFT
The Goertzel Algorithm
The Chirp-z Transform Algorithm
Quantization Effects in the Computation of the DFT
Quantization Errors in the Direct Computation of the DFT
Quantization Errors in FFT Algorithms
Summary and References
Implementation of Discrete-Time Systems
Structures for the Realization of Discrete-Time Systems
Structures for FIR Systems
Direct-Form Structure
Cascade-Form Structures
Frequency-Sampling Structures
Lattice Structure
Structures for IIR Systems
Direct-Form Structures
Signal Flow Graphs and Transposed Structures
Cascade-Form Structures
Parallel-Form Structures
Lattice and Lattice-Ladder Structures for IIR Systems
Representation of Numbers
Fixed-Point Representation of Numbers
Binary Floating-Point Representation of Numbers
Errors Resulting from Rounding and Truncation
Quantization of Filter Coefficients
Analysis of Sensitivity to Quantization of Filter Coefficients
Quantization of Coefficients in FIR Filters
Round-Off Effects in Digital Filters
Limit-Cycle Oscillations in Recursive Systems
Scaling to Prevent Overflow
Statistical Characterization of Quantization Effects in Fixed-Point Realizations of Digital Filters
Summary and References
Design of Digital Filters
General Considerations
Causality and Its Implications
Characteristics of Practical Frequency-Selective Filters
Design of FIR Filters
Symmetric and Antisymmetric FIR Filters
Design of Linear-Phase FIR Filters Using Windows
Design of Linear-Phase FIR Filters by the Frequency-Sampling Method
Design of Optimum Equiripple Linear-Phase FIR Filters
Design of FIR Differentiators
Design of Hilbert Transformers
Comparison of Design Methods for Linear-Phase FIR Filters
Design of IIR Filters From Analog Filters
IIR Filter Design by Approximation of Derivatives
IIR Filter Design by Impulse Invariance
IIR Filter Design by the Bilinear Transformation
Characteristics of Commonly Used Analog Filters
Some Examples of Digital Filter Designs Based on the Bilinear Transformation
Frequency Transformations
Frequency Transformations in the Analog Domain
Frequency Transformations in the Digital Domain
Summary and References
Multirate Digital Signal Processing
Decimation by a Factor D
Interpolation by a Factor I
Sampling Rate Conversion by a Rational Factor I/D
Implementation of Sampling Rate Conversion
Polyphase Filter Structures
Interchange of Filters and Downsamplers/Upsamplers
Sampling Rate Conversion with Cascaded Integrator Comb Filters
Polyphase Structures for Decimation and Interpolation Filters
Structures for Rational Sampling Rate Conversion
Multistage Implementation of Sampling Rate Conversion
Sampling Rate Conversion of Bandpass Signals
Sampling Rate Conversion by an Arbitrary Factor
Arbitrary Resampling with Polyphase Interpolators
Arbitrary Resampling with Farrow Filter Structures
Applications of Multirate Signal Processing
Design of Phase Shifters
Interfacing of Digital Systems with Different Sampling Rates
Implementation of Narrowband Lowpass Filters
Subband Coding of Speech Signals
Digital Filter Banks
Polyphase Structures of Uniform Filter Banks
Two-Channel Quadrature Mirror Filter Bank
Elimination of Aliasing
Condition for Perfect Reconstruction
Polyphase Form of the QMF Bank
Linear Phase FIR QMF Bank
Perfect Reconstruction Two-Channel FIR QMF Bank
Two-Channel QMF Banks in Subband Coding
M-Channel QMF Bank
Alias-Free and Perfect Reconstruction Condition
Polyphase Form of the M-Channel QMF Bank
Summary and References
Linear Prediction and Optimum Linear Filters
Random Signals, Correlation Functions, and Power Spectra
Random Processes
Stationary Random Processes
Statistical (Ensemble) Averages
Statistical Averages for Joint Random Processes
Power Density Spectrum
Discrete-Time Random Signals
Time Averages for a Discrete-Time Random Process
Mean-Ergodic Process
Correlation-Ergodic Processes
Innovations Representation of a Stationary Random Process
Rational Power Spectra
Relationships Between the Filter Parameters and the Autocorrelation Sequence
Forward and Backward Linear Prediction
Forward Linear Prediction
Backward Linear Prediction
The Optimum Reflection Coefficients for the Lattice Forward and Backward Predictors
Relationship of an AR Process to Linear Prediction
Solution of the Normal Equations
The Levinson-Durbin Algorithm
The Schur Algorithm
Properties of the Linear Prediction-Error Filters
AR Lattice and ARMA Lattice-Ladder Filters
AR Lattice Structure
ARMA Processes and Lattice-Ladder Filters
Wiener Filters for Filtering and Prediction
FIR Wiener Filter
Orthogonality Principle in Linear Mean-Square Estimation
IIR Wiener Filter
Noncausal Wiener Filter
Summary and References
Adaptive Filters
Applications of Adaptive Filters
System Identification or System Modeling
Adaptive Channel Equalization
Echo Cancellation in Data Transmission over Telephone Channels
Suppression of Narrowband Interference in a Wideband Signal
Adaptive Line Enhancer
Adaptive Noise Cancelling
Linear Predictive Coding of Speech Signals
Adaptive Arrays
Adaptive Direct-Form FIR Filters-The LMS Algorithm
Minimum Mean-Square-Error Criterion
The LMS Algorithm
Related Stochastic Gradient Algorithms
Properties of the LMS Algorithm
Adaptive Direct-Form Filters-RLS Algorithms
RLS Algorithm
The LDU Factorization and Square-Root Algorithms
Fast RLS Algorithms
Properties of the Direct-Form RLS Algorithms
Adaptive Lattice-Ladder Filters
Recursive Least-Squares Lattice-Ladder Algorithms
Other Lattice Algorithms
Properties of Lattice-Ladder Algorithms
Summary and References
Power Spectrum Estimation
Estimation of Spectra from Finite-Duration Observations of Signals
Computation of the Energy Density Spectrum
Estimation of the Autocorrelation and Power Spectrum of Random Signals: The Periodogram
The Use of the DFT in Power Spectrum Estimation
Nonparametric Methods for Power Spectrum Estimation
The Bartlett Method: Averaging Periodograms
The Welch Method: Averaging Modified Periodograms
The Blackman and Tukey Method: Smoothing the Periodogram
Performance Characteristics of Nonparametric Power Spectrum Estimators
Computational Requirements of Nonparametric Power Spectrum Estimates
Parametric Methods for Power Spectrum Estimation
Relationships Between the Autocorrelation and the Model Parameters
The Yule-Walker Method for the AR Model Parameters
The Burg Method for the AR Model Parameters
Unconstrained Least-Squares Method for the AR Model Parameters
Sequential Estimation Methods for the AR Model Parameters
Selection of AR Model Order
MA Model for Power Spectrum Estimation
ARMA Model for Power Spectrum Estimation
Some Experimental Results
Filter Bank Methods
Filter Bank Realization of the Periodogram
Minimum Variance Spectral Estimates
Eigenanalysis Algorithms for Spectrum Estimation
Pisarenko Harmonic Decomposition Method
Eigen-decomposition of the Autocorrelation Matrix for Sinusoids in White Noise
MUSIC Algorithm
ESPRIT Algorithm
Order Selection Criteria
Experimental Results
Summary and References
Random Number Generators
Tables of Transition Coefficients for the Design of Linear-Phase FIR Filters
References and Bibliography
Answers to Selected Problems
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