Sanjit K. Mitra (ed.), James F. Kaiser (ed.), "Handbook for Digital Signal Processing"

 

John Wiley & Sons,
New York, USA, 1993
ISBN 0-471-61995-7

Authors:
Rashid Ansari
Nirmal K. Bose
C. Sidney Burrus
Youn-Shik Byun
John M. Cioffi
Jalil Fadavi-Ardekani
Petri Haavisto
William E. Higgins
W. Kenneth Jenkins
Yih C. Jenq
James F. Kaiser
Ramdas Kumaresan
Lawrence E. Larson
Bede Liu
Sanjit K. Mitra
Kalyan Mondal
David C. Munson, Jr.
Yrjö Neuvo
Philip A. Regalia
Tapio Saramäki
Ognjan V. Shentov
Henrik V. Sorensen
Kenneth Steiglitz
Wongyong Sung
Gabor C. Temes
Tran Thong
P. P. Vaidyanathan

Glossary of Notations and Abbreviations (XXV)
1. Introduction (1)
1.1. The Need for Signal Processing (2)
1.2. Why Digital Signal Processing? (13)
1.3. Applications of Signal Processing (17)
1.4. Typical Applications of Digital Signal Processing (35)
1.5. Notations (48)
1.6. Organization and Scope of the Handbook (49)
References (51)
General References (53)
2. Mathematical Foundations of Signal Processing (57)
2.1. Signals (57)
2.2. Digital Signal Processing - Definition and Brief History (61)
2.3. Time-Domain Representation of Signals and Filters (62)
2.4. Frequency-Domain Representation of Signals and Filters (67)
2.5. The z- and Laplace Transforms (70)
2.6. Properties of the z- and Laplace Transforms (73)
2.7. Real and Complex Convolution (76)
2.8. Finite-Dimensional Filters (78)
2.9. Ideal Sampling (80)
2.10. Reconstruction (82)
2.11. The Pulse Transfer Function (87)
2.12. The Discrete Fourier Transform (89)
2.13. Time-Limited Signals (92)
2.14. Random Signals (93)
2.15. Summary - The Six Domains of Signal Processing (97)
References (98)
3. Linear Time-Invariant Discrete-Time Systems (101)
3.1. System Classification (101)
3.2. Time-Domain Representation of Linear Systems (105)
3.3. Classification and Properties of LTI Discrete-Time Systems (111)
3.4. Transform-Domain Representation of Linear Systems (114)
3.5. Structural Representations of Linear Systems (125)
3.6. State-Space Representation of Linear Systems (142)
3.7. Block processing (147)
3.8. Summary and Future Trends (153)
References (153)
4. Finite Impulse Response Filter Design (155)
4.1. Digital Filter Design Problem (155)
4.2. Why FIR Filters? (163)
4.3. Characteristics of Linear-Phase FIR Filters (164)
4.4. FIR Filter Design by Windowing (174)
4.5. Design of FIR Filters in the Least-Mean-Square Sense (189)
4.6. Maximally Flat FIR Filters (193)
4.7. Some Simple FIR Filter Designs (195)
4.8. Design of FIR Filters in the Minimax Sense (198)
4.9. Design of Minimum-Phase FIR Filters (214)
4.10. Design of FIR with Constraints in the Time or Frequency Domain (218)
4.11. Design of FIR Filters Using Periodic Subfilters as Basic Building Blocks (231)
4.12. Design of FIR Filters Using Identical Subfilters as Basic Building Blocks (256)
4.13. Summary (271)
References (272)
5. Infinite Impulse Response Digital Filter Design (279)
5.1. Introduction (279)
5.2. IIR Digital Filter Design Based on Transformation of an Analog Filter (280)
5.3. Analog Lowpass Filter Designs (283)
5.4. Analog-to-Digital Transformations (293)
5.5. Design Examples for Lowpass Digital Filters (304)
5.6. Digital Frequency Transformations (319)
5.7. Phase Equalization (322)
5.8. Computer-Aided Design of IIR Filters (327)
5.9. Summary and Discussion (332)
References (333)
6. Digital Filter Implementation Considerations (337)
6.1. Introduction (337)
6.2. Number Representation and Arithmetic Schemes (338)
6.3. Characteristics of Filter Structures (344)
6.4. Structural Transformations (353)
6.5. Block Implementation (363)
6.6. Maximum Sampling Rate and Multiprocessor Implementations (366)
6.7. Quantization and Overflow Operations (372)
6.8. Coefficient Sensitivity (382)
6.9. Input Quantization Error (390)
6.10. Roundoff Noise and Dynamic Range Considerations (393)
6.11. Roundoff Noise Analysis of Floating-Point Filters (409)
6.12. Concluding Remarks (413)
References (413)
7. Robust Digital Filter Structures (419)
7.1. Introduction (419)
7.2. Roundoff Noise Reduction Using Error Feedback (421)
7.3. Cascade Form Digital Filter Structures (425)
7.4. State-Space Approach for Low-Noise Design (428)
7.5. Second-Order IIR Structures with Low Sensitivity (432)
7.6. Low-Sensitivity IIR Designs Based on Structural Passivity (434)
7.7. Wave Digital Filters (459)
7.8. Passive IIR Lattice Structures Based on LBR Building Blocks (466)
7.9. Roundoff Noise in Structurally Passive and Lossless Systems (474)
7.10. IIR Filter Structures Free from Limit Cycles (479)
7.11. Concluding Remarks (486)
References (486)
8. Fast DFT and Convolution Algorithms (491)
8.1. Computation of Convolution and Filtering (493)
8.2. Fast Computation of the DFT (517)
8.3. Other Transforms (553)
8.4. Conclusion (561)
References (562)
9. Finite Arithmetic Concepts (611)
9.1. Introduction (611)
9.2. Fundamentals of Modular Arithmetic (613)
9.3. The Design of VLSI Digital Filters Using RNS Arithmetic (623)
9.4. Fault-Tolerant Systems Designed with RNS Arithmetic (634)
9.5. Complex RNS Arithmetic (646)
9.6. Design Example - A RNS Digital Correlator (663)
9.7. Summary (673)
References (674)
10. Signal Conditioning and Interface Circuits (677)
10.1. Anti-aliasing Filters (677)
10.2. Analog-to-Digital Converters (690)
10.3. Digital-to-Analog Converters (708)
10.4. Smoothing Filters (716)
10.5. Summary (718)
References (719)
11. Hardware and Architecture (721)
11.1. Why Hardware? (721)
11.2. Digital Signal Processing Computational Requirements (723)
11.3. General Purpose DSP Chips and Development Systems (728)
11.4. Custom Hardware (754)
11.5. Summary (777)
References (778)
12. Software Considerations (783)
12.1. Introduction (783)
12.2. Implementation on a General Purpose Computer (787)
12.3. Parallel Computer Implementation (792)
12.4. Review of Representative DSP Chip Programming (807)
12.5. Examples of DSP Chip Implementation of FIR Filters (854)
12.6. Examples of DSP Chip Implementation of IIR Filters (861)
12.7. Examples of DSP Chip Implementation of FFT Algorithms (871)
References (904)
13. Special Filter Design (907)
13.1. Introduction (907)
13.2. Design of Hilbert Transformers (909)
13.3. Differentiators and Integrators (931)
13.4. Smoothing Filters (940)
13.5. Noninteger Delay Filters (948)
13.6. Median Filters (953)
13.7. Concluding Remarks (976)
References (978)
14. Multirate Signal Processing (981)
14.1. Introduction (981)
14.2. Sampling Rate Conversion (983)
14.3. Filter Design for Sampling Rate Alteration (1013)
14.4. Multistage Implementation of Rate Conversion (1031)
14.5. Multirate Filter Banks (1041)
14.6. Applications (1070)
14.7. Summary (1079)
References (1079)
15. Adaptive Filtering (1085)
15.1. Introduction (1085)
15.2. Adaptive Filters Basics (1086)
15.3. Stochastic-Gradient (LMS) Adaptive Algorithms (1092)
15.4. Recursive Least-Squares Adaptive Algorithms (1104)
15.5. Frequency-Domain and Block Adaptive Filters (1121)
15.6. Applications (1129)
15.7. Conclusion (1138)
References (1138)
16. Spectral Analysis (1143)
16.1. Introduction (1143)
16.2. Fourier transform of Finite-Time Signals (1146)
16.3. Fourier Analysis of Random Signals (1157)
16.4. Parametric Spectrum Analysis of Random Signals (1169)
16.5. Parametric Spectrum Analysis of Sinusoidal Signals (1191)
16.6. Spectrum Analysis for Sensor Array Processing (1225)
16.7. Summary (1237)
References (1237)
Index (1243)

 

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