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Digital Signal Processing with Student CD ROM 4th edition [Multiple-component retail product]

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  • Formatas: Multiple-component retail product, aukštis x plotis x storis: 234x208x43 mm, weight: 1724 g, Illustrations +, Contains 1 Hardback and 1 CD-ROM
  • Išleidimo metai: 17-Sep-2010
  • Leidėjas: McGraw Hill Higher Education
  • ISBN-10: 007736676X
  • ISBN-13: 9780077366766
Kitos knygos pagal šią temą:
Digital Signal Processing with Student CD ROM 4th editionDidesnis paveikslėlis
  • Formatas: Multiple-component retail product, aukštis x plotis x storis: 234x208x43 mm, weight: 1724 g, Illustrations +, Contains 1 Hardback and 1 CD-ROM
  • Išleidimo metai: 17-Sep-2010
  • Leidėjas: McGraw Hill Higher Education
  • ISBN-10: 007736676X
  • ISBN-13: 9780077366766
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9780077366766.html
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 programs powerful capability to solve signal processing problems. Practical examples and applications bring the theory to life. This popular book introduces the tools used in the analysis and design of discrete-time systems for signal processing.
Preface ix
Acknowledgements xiii
1 Signals and Signal Processing
1(40)
1.1 Characterization and Classification of Signals
1(3)
1.2 Typical Signal Processing Operations
4(9)
1.3 Examples of Typical Signals
13(8)
1.4 Typical Signal Processing Applications
21(16)
1.5 Why Digital Signal Processing?
37(4)
2 Discrete-Time Signals in the Time Domain
41(48)
2.1 Time-Domain Representation
42(4)
2.2 Operations on Sequences
46(9)
2.3 Operations on Finite-Length Sequences
55(7)
2.4 Typical Sequences and Sequence Representation
62(10)
2.5 The Sampling Process
72(2)
2.6 Correlation of Signals
74(6)
2.7 Random Signals
80(1)
2.8 Summary
81(1)
2.9 Problems
81(6)
2.10 Matlab Exercises
87(2)
3 Discrete-Time Signals in the Frequency Domain
89(54)
3.1 The Continuous-Time Fourier Transform
89(16)
3.3 Discrete-Time Fourier Transform Theorems
105(6)
3.4 Energy Density Spectrum of a Discrete-Time Sequence
111(1)
3.5 Band-Limited Discrete-Time Signals
112(1)
3.6 DTFT Computation Using MATLAB
113(1)
3.7 The Unwrapped Phase Function
113(2)
3.8 Digital Processing of Continuous-Time Signals
115(14)
3.9 Sampling of Bandpass Signals
129(2)
3.10 Effect of Sample-and-Hold Operation
131(1)
3.11 Summary
132(1)
3.12 Problems
133(9)
3.13 MATLAB Exercises
142(1)
4 Discrete-Time Systems
143(56)
4.1 Discrete-Time System Examples
143(6)
4.2 Classification of Discrete-Time Systems
149(4)
4.3 Impulse and Step Responses
153(1)
4.4 Time-Domain Characterization of LTI Discrete-Time Systems
154(7)
4.5 Simple Interconnection Schemes
161(3)
4.6 Finite-Dimensional LTI Discrete-Time Systems
164(8)
4.7 Classification of LTI Discrete-Time Systems
172(3)
4.8 Frequency-Domain Representations of LTI Discrete-Time Systems
175(10)
4.9 Phase and Group Delays
185(4)
4.10 Summary
189(1)
4.11 Problems
190(8)
4.12 MATLAB Exercises
198(1)
5 Finite-Length Discrete Transforms
199(78)
5.1 Orthogonal Transforms
199(2)
5.2 The Discrete Fourier Transform
201(4)
5.3 Relation Between the DTFT and the DFT and Their Inverses
205(6)
5.4 Circular Convolution
211(5)
5.5 Classifications of Finite-Length Sequences
216(5)
5.6 DFT Symmetry Relations
221(3)
5.7 Discrete Fourier Transform Theorems
224(6)
5.8 Fourier-Domain Filtering
230(2)
5.9 Computation of the DFT of Real Sequences
232(2)
5.10 Linear Convolution Using the DFT
234(11)
5.11 Short-Time Fourier Transform
245(4)
5.12 Discrete Cosine Transform
249(7)
5.13 The Haar Transform
256(3)
5.14 Energy Compaction Properties
259(3)
5.15 Summary
262(1)
5.16 Problems
262(13)
5.17 MATLAB Exercises
275(2)
6 z-Transform
277(56)
6.1 Definition
277(4)
6.2 Rational z-Transforms
281(2)
6.3 Region of Convergence of a Rational z-Transform
283(6)
6.4 The Inverse z-Transform
289(8)
6.5 z-Transform Theorems
297(8)
6.6 Computation of the Convolution Sum of Finite-Length Sequences
305(3)
6.7 The Transfer Function
308(12)
6.8 Summary
320(1)
6.9 Problems
320(12)
6.10 MATLAB Exercises
332(1)
7 LTI Discrete-Time Systems in the Transform Domain
333(84)
7.1 Transfer Function Classification Based on Magnitude Characteristics
333(9)
7.2 Transfer Function Classification Based on Phase Characteristics
342(7)
7.3 Types of Linear-Phase FIR Transfer Functions
349(11)
7.4 Simple Digital Filters
360(19)
7.5 Complementary Transfer Functions
379(6)
7.6 Inverse Systems
385(4)
7.7 System Identification
389(3)
7.8 Digital Two-Pairs
392(2)
7.9 Algebraic Stability Test
394(5)
7.10 Summary
399(1)
7.11 Problems
400(14)
7.12 MATLAB Exercises
414(3)
8 Digital Filter Structures
417(72)
8.1 Block Diagram Representation
418(3)
8.2 Equivalent Structures
421(1)
8.3 Basic FIR Digital Filter Structures
422(5)
8.4 Basic IIR Digital Filter Structures
427(6)
8.5 Realization of Basic Structures Using MATLAB
433(3)
8.6 Allpass Filters
436(9)
8.7 Parametrically Tunable Low-Order IIR Digital Filter Pairs
445(2)
8.8 IIR Tapped Cascaded Lattice Structures
447(5)
8.9 FIR Cascaded Lattice Structures
452(8)
8.10 Parallel Allpass Realization of IIR Transfer Functions
460(5)
8.11 Tunable High-Order Digital Filters
465(7)
8.12 Computational Complexity of Digital Filter Structures
472(1)
8.13 Summary
472(1)
8.14 Problems
473(14)
8.15 MATLAB Exercises
487(2)
9 IIR Digital Filter Design
489(38)
9.1 Preliminary Considerations
489(5)
9.2 Bilinear Transformation Method of IIR Filter Design
494(5)
9.3 Design of Lowpass IIR Digital Filters
499(2)
9.4 Design of Highpass, Bandpass, and Bandstop IIR Digital Filters
501(4)
9.5 Spectral Transformations of IIR Filters
505(7)
9.6 IIR Digital Filter Design Using MATLAB
512(3)
9.7 Computer-Aided Design of IIR Digital Filters
515(4)
9.8 Summary
519(1)
9.9 Problems
519(6)
9.10 MATLAB Exercises
525(2)
10 FIR Digital Filter Design
527(72)
10.1 Preliminary Considerations
527(4)
10.2 FIR Filter Design Based on Windowed Fourier Series
531(15)
10.3 Computer-Aided Design of Equiripple Linear-Phase FIR Filters
546(9)
10.4 Design of Minimum-Phase FIR Filters
555(1)
10.5 FIR Digital Filter Design Using MATLAB
556(17)
10.6 Design of Computationally Efficient FIR Digital Filters
573(13)
10.7 Summary
586(1)
10.8 Problems
587(7)
10.9 MATLAB Exercises
594(5)
11 DSP Algorithm Implementation
599(64)
11.1 Basic Issues
599(11)
11.2 Structure Simulation and Verification Using MATLAB
610(7)
11.3 Computation of the Discrete Fourier Transform
617(15)
11.4 Fast DFT Algorithms Based on Index Mapping
632(8)
11.5 DFT and IDFT Computation Using MATLAB
640(2)
11.6 Sliding Discrete Fourier Transform
642(1)
11.7 DFT Computation over a Narrow Frequency Band
642(5)
11.8 Number Representation
647(5)
11.9 Handling of Overflow
652(1)
11.10 Summary
653(1)
11.11 Problems
653(8)
11.12 MATLAB Exercises
661(2)
12 Analysis of Finite Wordlength Effects
663(76)
12.1 The Quantization Process and Errors
664(1)
12.2 Quantization of Fixed-Point Numbers
665(3)
12.3 Quantization of Floating-Point Numbers
668(1)
12.4 Analysis of Coefficient Quantization Effects
668(13)
12.5 A/D Conversion Noise Analysis
681(10)
12.6 Analysis of Arithmetic Round-Off Errors
691(4)
12.7 Dynamic Range Scaling
695(11)
12.8 Signal-to-Noise Ratio in Low-Order IIR Filters
706(4)
12.9 Low-Sensitivity Digital Filters
710(6)
12.10 Reduction of Product Round-Off Noise Using Error Feedback
716(3)
12.11 Limit Cycles in IIR Digital Filters
719(8)
12.12 Round-Off Errors in FFT Algorithms
727(3)
12.13 Summary
730(1)
12.14 Problems
731(5)
12.15 MATLAB Exercises
736(3)
13 Multirate Digital Signal Processing Fundamentals
739(68)
13.1 The Basic Sampling Rate Alteration Devices
740(10)
13.2 Multirate Structures for Sampling Rate Conversion
750(8)
13.3 Multistage Design of Decimator and Interpolator
758(2)
13.4 The Polyphase Decomposition
760(11)
13.5 Arbitrary-Rate Sampling Rate Converter
771(12)
13.6 Nyquist Filters
783(9)
13.7 CIC Decimators and Interpolators
792(4)
13.8 Summary
796(1)
13.9 Problems
797(8)
13.10 MATLAB Exercises
805(2)
14 Multirate Filter Banks and Wavelets
807(56)
14.1 Digital Filter Banks
807(6)
14.2 Two-Channel Quadrature-Mirror Filter Bank
813(10)
14.3 Perfect Reconstruction Two-Channel FIR Filter Banks
823(9)
14.4 L-Channel QMF Banks
832(8)
14.5 Multilevel Filter Banks
840(4)
14.6 Discrete Wavelet Transform
844(9)
14.7 Summary
853(1)
14.8 Problems
853(8)
14.9 MATLAB Exercises
861(2)
A Analog Lowpass Filter Design
863(24)
A.1 Analog Filter Specifications
863(2)
A.2 Butterworth Approximation
865(2)
A.3 Chebyshev Approximation
867(3)
A.4 Elliptic Approximation
870(1)
A.5 Linear-Phase Approximation
871(1)
A.6 Analog Filter Design Using MATLAB
872(3)
A.7 Analog Lowpass Filter Design Examples
875(2)
A.8 A Comparison of the Filter Types
877(3)
A.9 Anti-Aliasing Filter Design
880(2)
A.10 Reconstruction Filter Design
882(5)
B Design of Analog Highpass, Bandpass, and Bandstop Filters
887(6)
B.1 Analog Highpass Filter Design
887(2)
B.2 Analog Bandpass Filter Design
889(3)
B.3 Analog Bandstop Filter Design
892(1)
C Discrete-Time Random Signals
893(14)
C.1 Statistical Properties of a Random Variable
893(2)
C.2 Statistical Properties of a Random Signal
895(1)
C.3 Wide-Sense Stationary Random Signal
896(1)
C.4 Concept of Power in a Random Signal
897(1)
C.5 Ergodic Signal
898(1)
C.6 Transform-Domain Representations of Random Signals
899(2)
C.7 White Noise
901(1)
C.8 Discrete-Time Processing of Random Signals
901(6)
Bibliography 907(20)
Index 927
Sanjit Mitra, Ph.D., University of California, Berkeley.

Professor Mitra transferred to UCSB in July 1977 after 10 years at UC Davis. He obtained his B.Sc. with honors in Physics (1953) and the M.Sc. (Tech.) in Radio Physics and Electronics (1956) in India. He then obtained his M.S. (1960) and Ph.D. (1962) in electrical engineering from UC Berkeley. He has published over 600 papers in the areas of analog and digital signal processing, and image processing. He has also authored and co-authored twelve books, and holds five patents. Dr. Mitra has served IEEE in various capacities including service as the President of the IEEE Circuits & Systems Society in 1986, and has held visiting appointments in Australia, Austria, Finland, India, Japan, Singapore and the United Kingdom.