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9780521781756

Digital Signal Processing: System Analysis and Design

by
  • ISBN13:

    9780521781756

  • ISBN10:

    0521781752

  • Format: Hardcover
  • Copyright: 2002-05-13
  • Publisher: Cambridge University Press
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List Price: $80.00

Summary

Digital signal processing lies at the heart of the communications revolution and is an essential element of key technologies such as mobile phones and the Internet. This book covers all the major topics in digital signal processing (DSP) design and analysis, supported by MatLab examples and other modelling techniques. The authors explain clearly and concisely why and how to use digital signal processing systems; how to approximate a desired transfer function characteristic using polynomials and ratio of polynomials; why an appropriate mapping of a transfer function on to a suitable structure is important for practical applications; and how to analyse, represent and explore the trade-off between time and frequency representation of signals. An ideal textbook for students, it will also be a useful reference for engineers working on the development of signal processing systems.

Author Biography

Eduardo A. B. da Silva is an Associate Professor at the undergraduate Department of Electronics and Computer Engineering at the Federal University of Rio de Janeiro (UFRJ) and at the graduate Program of Electrical Engineering at COPPE/UFRJ.

Table of Contents

Preface xv
Introduction 1(4)
Discrete-time systems
5(31)
Introduction
5(1)
Discrete-time signals
6(3)
Discrete-time systems
9(6)
Linearity
9(1)
Time invariance
10(1)
Causality
10(2)
Impulse response and convolution sums
12(2)
Stability
14(1)
Difference equations and time-domain response
15(4)
Sampling of continuous-time signals
19(10)
Basic principles
20(1)
Sampling theorem
20(9)
Discrete-time signals and systems with MATLAB
29(1)
Summary
30(1)
Exercises
30(6)
The z and Fourier transforms
36(49)
Introduction
36(1)
Definition of the z transform
37(6)
Inverse z transform
43(10)
Computation based on residue theorem
45(4)
Computation based on partial-fraction expansions
49(2)
Computation based on polynomial division
51(1)
Computation based on series expansion
52(1)
Properties of the z transform
53(7)
Linearity
53(1)
Time-reversal
54(1)
Time-shift theorem
54(1)
Multiplication by an exponential
55(1)
Complex differentiation
55(1)
Complex conjugation
56(1)
Real and imaginary sequences
56(1)
Initial value theorem
57(1)
Convolution theorem
57(1)
Product of two sequences
58(1)
Parseval's theorem
59(1)
Table of basic z transforms
60(1)
Transfer functions
60(3)
Stability in the z domain
63(3)
Frequency response
66(6)
Fourier transform
72(3)
Properties of the Fourier transform
75(4)
Linearity
75(1)
Time-reversal
75(1)
Time-shift theorem
76(1)
Multiplication by an exponential
76(1)
Complex differentiation
76(1)
Complex conjugation
76(1)
Real and imaginary sequences
76(1)
Symmetric and antisymmetric sequences
77(1)
Convolution theorem
78(1)
Product of two sequences
78(1)
Parseval's theorem
78(1)
Transfer functions with MATLAB
79(2)
Summary
81(1)
Exercises
81(4)
Discrete transforms
85(63)
Introduction
85(1)
Discrete Fourier transform
86(6)
Properties of the DFT
92(8)
Linearity
93(1)
Time-reversal
93(1)
Time-shift theorem
93(1)
Circular frequency-shift theorem (modulation theorem)
94(1)
Circular convolution in time
95(1)
Correlation
96(1)
Real and imaginary sequences
97(1)
Symmetric and antisymmetric sequences
97(2)
Parseval's theorem
99(1)
Relationship between the DFT and the z transform
99(1)
Digital filtering using the DFT
100(9)
Linear and circular convolutions
100(5)
Overlap-and-add method
105(3)
Overlap-and-save method
108(1)
Fast Fourier transform
109(21)
Radix-2 algorithm with decimation in time
112(9)
Decimation in frequency
121(1)
Radix-4 algorithm
122(6)
Algorithms for arbitrary values of N
128(1)
Alternative techniques for determining the DFT
129(1)
Other discrete transforms
130(8)
Discrete cosine transform
130(4)
A family of sine and cosine transforms
134(1)
Discrete Hartley transform
135(2)
Hadamard transform
137(1)
Other important transforms
138(1)
Signal representations
138(103)
Discrete transforms with MATLAB
141(2)
Summary
143(1)
Exercises
144(4)
Digital filters
148(40)
Introduction
148(1)
Basic structures of nonrecursive digital filters
148(11)
Direct form
149(2)
Cascade form
151(1)
Linear-phase forms
151(8)
Basic structures of recursive digital filters
159(6)
Direct forms
159(3)
Cascade form
162(1)
Parallel form
163(2)
Digital network analysis
165(5)
State-space description
170(1)
Basic properties of digital networks
171(9)
Tellegen's theorem
172(1)
Reciprocity
173(1)
Interreciprocity
174(1)
Transposition
175(1)
Sensitivity
175(5)
Digital filter forms with MATLAB
180(4)
Summary
184(1)
Exercises
184(4)
FIR filter approximations
188(66)
Introduction
188(1)
Ideal characteristics of standard filters
189(5)
Lowpass, highpass, bandpass, and bandstop filters
189(1)
Differentiators
190(2)
Hilbert transformers
192(2)
Summary
194(1)
FIR filter approximation by frequency sampling
194(8)
FIR filter approximation with window functions
202(17)
Rectangular window
205(1)
Triangular windows
205(1)
Hamming and Hanning windows
206(1)
Blackman window
207(2)
Kaiser window
209(7)
Dolph-Chebyshev window
216(3)
Maximally flat FIR filter approximation
219(3)
FIR filter approximation by optimization
222(18)
Weighted-least-squares method
228(1)
Chebyshev method
229(6)
WLS-Chebyshev method
235(5)
FIR filter approximation with MATLAB
240(6)
Summary
246(2)
Exercises
248(6)
IIR filter approximations
254(56)
Introduction
254(1)
Analog filter approximations
255(19)
Analog filter specification
255(1)
Butterworth approximation
256(2)
Chebyshev approximation
258(3)
Elliptic approximation
261(3)
Frequency transformations
264(10)
Continuous-time to discrete-time transformations
274(11)
Impulse-invariance method
274(4)
Bilinear transformation method
278(7)
Frequency transformation in the discrete-time domain
285(3)
Lowpass to lowpass transformation
285(1)
Lowpass to highpass transformation
286(1)
Lowpass to bandpass transformation
286(1)
Lowpass to bandstop transformation
287(1)
Variable cutoff filter design
288(1)
Magnitude and phase approximation
288(10)
Basic principles
289(4)
Multi-variable function minimization method
293(3)
Alternative methods
296(2)
Time-domain approximation
298(3)
IIR filter approximation with MATLAB
301(6)
Summary
307(1)
Exercises
307(3)
Finite-precision effects
310(44)
Introduction
310(1)
Binary number representation
310(3)
Fixed-point representations
310(2)
Floating-point representation
312(1)
Product quantization
313(6)
Signal scaling
319(7)
Coefficient quantization
326(7)
Deterministic sensitivity criterion
326(4)
Statistical forecast of the wordlength
330(3)
Limit cycles
333(18)
Granular limit cycles
334(1)
Overflow limit cycles
335(2)
Elimination of zero-input limit cycles
337(8)
Elimination of constant-input limit cycles
345(2)
Forced-response stability of digital filters with nonlinearities due to overflow
347(4)
Summary
351(1)
Exercises
351(3)
Multirate systems
354(21)
Introduction
354(1)
Basic principles
354(1)
Decimation
355(5)
Interpolation
360(4)
Examples of interpolators
364(1)
Rational sampling-rate changes
364(1)
Inverse operations
365(1)
Decimation and interpolation for efficient filter implementation
365(6)
Narrowband FIR filters
366(2)
Wideband FIR filters with narrow transition bands
368(3)
Multirate systems with MATLAB
371(2)
Summary
373(1)
Exercises
374(1)
Filter banks and wavelets
375(78)
Introduction
375(1)
Filter banks
375(5)
Decimation of a bandpass signal
376(1)
Inverse decimation of a bandpass signal
377(1)
Critically decimated M-band filter banks
378(2)
Perfect reconstruction
380(10)
Noble identities
380(1)
Polyphase decompositions
381(1)
Commutator models
382(1)
M-band filter banks in terms of polyphase components
383(2)
Perfect reconstruction M-band filter banks
385(4)
Transmultiplexers
389(1)
General 2-band perfect reconstruction filter banks
390(4)
QMF filter banks
394(3)
CQF filter banks
397(2)
Block transforms
399(2)
Cosine-modulated filter banks
401(9)
Lapped transforms
410(17)
Fast algorithms and biorthogonal LOT
420(2)
Generalized LOT
422(5)
Wavelet transforms
427(15)
Hierarchical filter banks
428(1)
Wavelets
429(8)
Scaling functions
437(1)
Relation between x(t) and x(n)
437(1)
Relation between the wavelets and the filter coefficients
438(1)
Regularity
439(2)
Examples
441(1)
Filter banks and wavelets with MATLAB
442(7)
Summary
449(1)
Exercises
450(3)
Efficient FIR structures
453(38)
Introduction
453(1)
Lattice form
453(4)
Filter banks using the lattice form
455(2)
Polyphase form
457(2)
Frequency-domain form
459(1)
Recursive running sum form
459(1)
Realizations with reduced number of arithmetic operations
460(25)
Prefilter approach
460(4)
Interpolation approach
464(3)
Frequency response masking approach
467(12)
Quadrature approach
479(6)
Efficient FIR structures with MATLAB
485(2)
Summary
487(1)
Exercises
488(3)
Efficient IIR structures
491(68)
Introduction
491(1)
IIR parallel and cascade filters
491(11)
Parallel form
492(2)
Cascade form
494(4)
Error spectrum shaping
498(3)
Closed-form scaling
501(1)
State-space sections
502(15)
Optimal state-space sections
503(5)
State-space sections without limit cycles
508(9)
Lattice filters
517(7)
Wave filters
524(29)
Motivation
526(2)
Wave elements
528(16)
Lattice wave digital filters
544(9)
Efficient IIR structures with MATLAB
553(1)
Summary
553(1)
Exercises
554(5)
Implementation of DSP systems
559(35)
Introduction
559(1)
Basic elements
560(12)
Properties of the two's-complement representation
560(1)
Serial adder
561(2)
Serial multiplier
563(8)
Parallel adder
571(1)
Parallel multiplier
572(1)
Distributed arithmetic implementation
572(8)
Programmable logic devices
580(1)
ASIC implementation
581(5)
Digital signal processors
586(5)
Analog Devices DSPs
588(1)
Motorola DSPs
588(1)
Texas Instruments DSPs
589(2)
Summary
591(1)
Exercises
592(2)
References 594(10)
Index 604

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