Digital Signal Processing: Spectral Computation and Filter Design by Chi-Tsong ChenDigital Signal Processing: Spectral Computation and Filter Design by Chi-Tsong Chen

Digital Signal Processing: Spectral Computation and Filter Design

byChi-Tsong Chen

Hardcover | December 15, 2000

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Designed for a first course in digital signal processing, Digital Signal Processing: Spectral Computation and Filter Design covers two major topics: the computation of frequency contents of signals and the design of digital filters. While it focuses on basic ideas and procedures and covers thestandard topics in the field, this unique text distinguishes itself from competing texts by extensively employing the fast Fourier transform (FFT). Part 1: Spectral Computation deals with continuous-time (CT), discrete-time (DT), and digital signals; CT and DT Fourier series (frequency components); CT and DT Fourier transforms (frequency spectra); and discrete Fourier transform (DFT) and fast Fourier transform (FFT). Part 2: Digital FilterDesign discusses linear time-invariant lumped systems; ideal and practical digital filters; design of FIR digital filters; design of IIR filters; and structures of digital filters. Digital Signal Processing covers numerous topics not found in similar texts. It: DT Establishes a simplified version of the sampling theorem for periodic signals DT Uses FFT to compute frequency spectra of DT and CT signals and inverse FFT to compute DT and CT signals from their frequency spectra DT Employs FFT to compute the inverse z-transform DT Covers steady-state and transient responses of digital filters and gives an estimated time for a transient response to die out DT Gives a mathematical justification for using an antialiasing analog filter in digital signal processing DT Introduces a discrete least-squares method to design FIR filters DT Presents an analog bandstop transformation that yields better results than ones generated by MATLABRG Digital Signal Processing features careful definitions of all terminology and a wealth of examples and problems. All numerical examples and most end-of-chapter problems are simple enough to be solved analytically by hand; these results can then be compared with the computer-generated solutions.MATLABRG is an integral part of the text.
Chi-Tsong Chen is at State University of New York, Stony Brook.
Title:Digital Signal Processing: Spectral Computation and Filter DesignFormat:HardcoverPublished:December 15, 2000Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0195136381

ISBN - 13:9780195136388

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Table of Contents

Preface1. Introduction1.1. Continuous-Time (CT), Discrete-Time (DT), and Digital Signals1.2. Representation of Digital Signals1.3. A/D and D/A Conversions1.4. Comparison of Digital and Analog Techniques1.5. Applications of Digital Signal Processing1.6. Scope of the BookPART 1: SPECTRAL COMPUTATION2. CT and DT Fourier Series--Frequency components2.1. Introduction2.2. Frequency and Frequency Range of Sinusoidal Sequences2.3. Frequencies of CT Sinusoids and Their Sampled Sequences2.4. Continuous-Time Fourier Series (CTFS)2.5. Discrete-Time Fourier Series (DTFS)2.6. FFT Computation of DTFS Coefficients2.7. FFT Computation of CTFS Coefficients2.8. Average Power and Its Computation2.9. Concluding Remarks3. CT and DT Fourier Transforms--Frequency Spectra3.1. Introduction3.2. CT Fourier Transform (CTFT)3.3. Properties of Frequency Spectra3.4. Distribution of Energy in Frequencies3.5. Effects of Truncation3.6. DT Fourier Transform (DTFT)3.7. Effects of Truncation3.8. Nyquist Sampling Theorem3.9. Time-limited Bandlimited Theorem4. DFT and FFT--Spectral Computation4.1. Introduction4.2. Discrete Fourier Transform (DFT)4.3. Properties of DFT4.4. Fast Fourier Transform (FFT)4.5. Spectral Computation of Finite Sequences4.6. Spectral Computation of CT Signals4.7. Computing DT Signals from Spectra4.8. Computing Energy Using FFT4.9. Concluding RemarksPART 2: FILTER DESIGN5. Linear Time-Invariant Lumped Systems5.1. Introduction5.2. Linearity and Time Invariance5.3. LTIL Systems--Difference Equations5.4. z-Transform5.5. Transfer Functions5.6. Stability5.7. Frequency Response5.8. Continuous-Time LTIL Systems5.9. CT Transfer Function, Stability, and Frequency Response5.10. Concluding Remarks6. Ideal and Some Practical Digital Filters6.1. Introduction6.2. Ideal Digital Filters6.3. Realizability6.4. First-Order Digital Filters6.5. Reciprocal Roots and All-Pass Filters6.6. Miscellaneous Topics6.7. Analog Ideal Low-Pass Filters7. Design of FIR Filters7.1. Introduction7.2. Classification of Linear-Phase FIR Filters7.3. Least-Square Optimal Filters--Direct Truncation7.4. Window Method7.5. Desired Filters with Specified Transition Bands7.6. Discrete Least-Squares Optimal FIR Filters7.7. Minimax Optimal FIR Filters7.8. Design of Digital Differentiators7.9. Hilbert Transformers7.10. A Design Example8. Design of IIR Filter Design8.1. Introduction8.2. Difficulties in Direct IIR Filter Design8.3. Design of Analog Prototype Filters8.4. Analog Frequency Transformations8.5. Impulse Invariance Method8.6. Bilinear Transformation8.7. Analog-Prototype-to-Digital Transformations8.8. Comparisons with FIR Filters9. Structures of Digital Filters9.1. Introduction9.2. Direct Form of FIR Filters9.3. DFT of Periodic Convolutions9.4. Direct and Canonical Forms of IIR Filters9.5. Effects of Filter Coefficient Quantizations9.6. Cascade and Parallel ImplementationsAppendix: The ImpulseReferencesIndex