Includes bibliographical references and index.

Cover -- Title Page -- Copyright Page -- Dedication -- About the Author -- Contents -- Preface -- 1 Introduction to Digital Signal Processing -- 1.1 Introduction -- 1.2 Signals -- 1.3 Frequency-Domain Representation -- 1.4 Notation -- 1.5 Signal Processing -- 1.6 Analog Filters -- 1.7 Applications of Analog Filters -- 1.8 Digital Filters -- 1.9 Three DSP Applications -- 2 Discrete-Time Systems -- 2.1 Introduction -- 2.2 Basic System Properties -- 2.3 Characterization of Discrete-Time Systems -- 2.4 Discrete-Time System Networks -- 2.5 Introduction to Time-Domain Analysis -- 2.6 Convolution Summation -- 2.7 Stability -- 2.8 State-Space Representation -- 2.9 Problems -- 3 The Fourier Series and Transform -- 3.1 Introduction -- 3.2 Fourier Series -- 3.3 Fourier Transform -- 3.4 Interrelation between the Fourier Series and the Fourier Transform -- 3.5 Poisson’s Summation Formula -- 3.6 Laplace Transform -- 3.7 Problems -- 4 The Z Transform -- 4.1 Introduction -- 4.2 Definition of Z Transform -- 4.3 Convergence Properties -- 4.4 The Z Transform as a Laurent Series -- 4.5 Inverse Z Transform -- 4.6 Additional Theorems and Properties -- 4.7 Z Transforms of Elementary Discrete-Time Signals -- 4.8 Z-Transform Inversion Techniques -- 4.9 Spectral Representation of Discrete-Time Signals -- 4.10 Problems -- 5 Application of Transform Theory to Systems -- 5.1 Introduction -- 5.2 The Discrete-Time Transfer Function -- 5.3 Stability -- 5.4 Time-Domain Analysis -- 5.5 Frequency-Domain Analysis -- 5.6 Transfer Functions for Digital Filters -- 5.7 Amplitude and Delay Distortion -- 5.8 Continuous-Time Systems -- 5.9 Problems -- 6 The Sampling Process -- 6.1 Introduction -- 6.2 Impulse-Modulated Signals -- 6.3 The Sampling Theorem -- 6.4 Aliasing -- 6.5 Graphical Representation of Interrelations -- 6.6 Processing of Continuous-Time Signals Using Digital Filters -- 6.7 Practical A/D and D/A Converters -- 6.8 Problems -- 7 The Discrete Fourier Transform -- 7.1 Introduction -- 7.2 Definition -- 7.3 Inverse DFT -- 7.4 Properties -- 7.5 Interrelation between the DFT and the Z Transform -- 7.6 Interrelation between the DFT and the CFT -- 7.7 Interrelation between the DFT and the Fourier Series -- 7.8 Simplified Notation -- 7.9 Periodic Convolutions -- 7.10 Fast Fourier-Transform Algorithms -- 7.11 Application of the FFT Approach to Signal Processing -- 7.12 Problems -- 8 The Window Technique -- 8.1 Introduction -- 8.2 Basic Principles -- 8.3 Discrete-Time Windows -- 8.4 Problems -- 9 Realization of Digital Filters -- 9.1 Introduction -- 9.2 Realization -- 9.3 Implementation -- 9.4 Problems -- 10 Design of Nonrecursive Filters -- 10.1 Introduction -- 10.2 Properties of Constant-Delay Nonrecursive Filters -- 10.3 Design Using the Fourier Series -- 10.4 Use of Window Technique -- 10.5 Prescribed Filter Specifications -- 10.6 Design Based on Numerical-Analysis Formulas -- 10.7 Problems -- 11 Approximations for Analog Filters -- 11.1 Introduction -- 11.2 Basic Concepts -- 11.3 Butterworth Approximation -- 11.4 Chebyshev Approximation -- 11.5 Inverse-Chebyshev Approximation -- 11.6 Elliptic Approximation -- 11.7 Bessel-Thomson Approximation -- 11.8 Transformations -- 11.9 Problems -- 12 Design of Recursive Filters -- 12.1 Introduction -- 12.2 Realizability Constraints.

12.3 Invariant Impulse-Response Method -- 12.4 Modified Invariant Impulse-Response Method -- 12.5 Matched-Z Transformation Method -- 12.6 Bilinear-Transformation Method -- 12.7 Digital-Filter Transformations -- 12.8 Comparison between Recursive and Nonrecursive Designs -- 12.9 Problems -- 13 Recursive Filters Satisfying Prescribed Specifications -- 13.1 Introduction -- 13.2 Design Procedure -- 13.3 Design Formulas -- 13.4 Design Using the Formulas and Tables -- 13.5 Constant Group Delay -- 13.6 Amplitude-Response Equalization -- 13.7 Problems -- 14 Effects of Finite Word Length in Digital Filters -- 14.1 Introduction -- 14.2 Number Representation -- 14.3 Coefficient Quantization -- 14.4 Low-Sensitivity Structures -- 14.5 Product Quantization -- 14.6 Signal Scaling -- 14.7 Minimization of Output Roundoff Noise -- 14.8 Limit-Cycle Oscillations -- 14.9 Problems -- 15 Design of Nonrecursive Filters Using Optimization Methods -- 15.1 Introduction -- 15.2 Problem Formulation -- 15.3 Remez Exchange Algorithm -- 15.4 Improved Search Methods -- 15.5 Efficient Remez Exchange Algorithm -- 15.6 Gradient Information -- 15.7 Prescribed Specifications -- 15.8 Generalization -- 15.9 Digital Differentiators -- 15.10 Arbitrary Amplitude Responses -- 15.11 Multiband Filters -- 15.12 Problems -- 16 Design of Recursive Filters Using Unconstrained Optimization -- 16.1 Introduction -- 16.2 Problem Formulation -- 16.3 Newton’s Method -- 16.4 Quasi-Newton Algorithms -- 16.5 Minimax Algorithms -- 16.6 Improved Minimax Algorithms -- 16.7 Design of Recursive Filters -- 16.8 Design of Recursive Delay Equalizers -- 16.9 Problems -- 17 Design of Recursive Filters Using Constrained Optimization -- 17.1 Introduction -- 17.2 Design Problem -- 17.3 Constrained Optimization Problem -- 17.4 Design Procedure -- 17.5 Alternative Initialization Approaches -- 17.6 Comparison of Recursive versus Nonrecursive Digital Filters -- 17.7 Problems -- 18 Wave Digital Filters -- 18.1 Introduction -- 18.2 Sensitivity Considerations -- 18.3 Wave Network Characterization -- 18.4 Element Realizations -- 18.5 Lattice Wave Digital Filters -- 18.6 Ladder Wave Digital Filters -- 18.7 Filters Satisfying Prescribed Specifications -- 18.8 Frequency-Domain Analysis -- 18.9 Scaling -- 18.10 Elimination of Limit-Cycle Oscillations -- 18.11 Related Synthesis Methods -- 18.12 A Cascade Synthesis Based on the Wave Characterization -- 18.13 Choice of Structure -- 18.14 Problems -- 19 Signal Processing Applications -- 19.1 Introduction -- 19.2 Sampling-Frequency Conversion -- 19.3 Quadrature-Mirror-Image Filter Banks -- 19.4 Hilbert Transformers -- 19.5 Two-Dimensional Digital Filters -- 19.6 Adaptive Digital Filters -- 19.7 Problems -- Appendix: Complex Analysis -- A.1 Introduction -- A.2 Complex Numbers -- A.3 Functions of a Complex Variable -- A.4 Basic Principles of Complex Analysis -- A.5 Series -- A.6 Laurent Theorem -- A.7 Residue Theorem -- A.8 Analytic Continuation -- A.9 Conformal Transformations -- References -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W -- Z.

Up-to-date digital filter design principles, techniques, and applications. Written by a Life Fellow of the IEEE, this comprehensive textbook teaches digital filter design, realization, and implementation and provides detailed illustrations and real-world applications of digital filters to signal processing. Digital Filters: Analysis, Design, and Signal Processing Applications gives a solid foundation in the fundamentals and concepts of DSP and continues with state-of-the-art methodologies and algorithms for the design of digital filters. You will get clear explanations of key topics such as spectral analysis, discrete-time systems, and the sampling process. This hands-on resource is supported by a rich collection of online materials that include PDF presentations, detailed solutions of the end-of-chapter problems, MATLAB programs that can be used to analyze and design digital filters of professional quality, and the author's DSP software D-Filter.

Also available in print edition.

Electronic reproduction. New York, N.Y. : McGraw Hill, 2018. Mode of access: World Wide Web. System requirements: Web browser. Access may be restricted to users at subscribing institutions.

Mode of access: Internet via World Wide Web.

In English.

Description based on e-Publication PDF.