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- Wiley
More About This Title Signal Processing and Integrated Circuits
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English
- Contains the fundamentals and advanced techniques of continuous-time and discrete-time signal processing.
- Presents in detail the design of analog MOS integrated circuits for signal processing, with application to the design of switched-capacitor filters.
- Uses the comprehensive design of integrated sigma-delta data converters to illustrate and unify the techniques of signal processing.
- Includes solved examples, end of chapter problems and MATLAB® throughout the book, to help readers understand the mathematical complexities of signal processing.
The treatment of the topic is at the senior undergraduate to graduate and professional levels, with sufficient introductory material for the book to be used as a self-contained reference.
- English
English
Hussein Baher, Dublin Institute of Technology, Ireland
Professor Baher is currently with the School of Electronic and Communications Engineering at the Dublin Institute of Technology. He is the Founder and Associate Editor of the Journal of Analog Integrated Circuits and Signal Processing. Professor Baher has authored 3 books in total, 2 of which with Wiley, Microelectronic Switched Capacitor Filters (1996), and the previous edition of Analog and Digital Signal Processing (2001). He is a Fellow of the Institution of Engineers of Ireland, and a Senior Fellow of the IEEE.
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English
Preface xvii
Part I PERSPECTIVE
1 Analog, Digital and Mixed-mode Signal Processing 3
1.1 Digital Signal Processing 3
1.2 Moore’s Law and the “Cleverness” Factor 3
1.3 System on a Chip 3
1.4 Analog and Mixed-mode Signal Processing 4
1.5 Scope 5
Part II ANALOG (CONTINUOUS-TIME) AND DIGITAL SIGNAL PROCESSING
2 Analog Continuous-time Signals and Systems 9
2.1 Introduction 9
2.2 The Fourier Series in Signal Analysis and Function Approximation 9
2.2.1 Definitions 9
2.2.2 The Time and Discrete Frequency Domains 10
2.2.3 Convolution 12
2.2.4 Parseval’s Theorem and Power Spectrum 12
2.2.5 The Gibbs’ Phenomenon 12
2.2.6 Window Functions 13
2.3 The Fourier Transformation and Generalized Signals 14
2.3.1 Definitions and Properties 14
2.3.2 Parseval’s Theorem and Energy Spectra 16
2.3.3 Correlation Functions 17
2.3.4 The Unit Impulse and Generalized Signals 17
2.3.5 The Impulse Response and System Function 18
2.3.6 Periodic Signals 19
2.3.7 The Uncertainty Principle 19
2.4 The Laplace Transform and Analog Systems 19
2.4.1 The Complex Frequency 19
2.4.2 Properties of the Laplace Transform 21
2.4.3 The System Function 22
2.5 Elementary Signal Processing Building Blocks 24
2.5.1 Realization of the Elementary Building Blocks using Operational Amplifier Circuits 24
2.6 Realization of Analog System Functions 29
2.6.1 General Principles and the Use of Op Amp Circuits 29
2.6.2 Realization Using OTAs and Gm− C Circuits 32
2.7 Conclusion 34
Problems 34
3 Design of Analog Filters 39
3.1 Introduction 39
3.2 Ideal Filters 39
3.3 Amplitude-oriented Design 43
3.3.1 Maximally Flat Response in both Pass-band and Stop-band 44
3.3.2 Chebyshev Response 46
3.3.3 Elliptic Function Response 48
3.4 Frequency Transformations 49
3.4.1 Low-pass to Low-pass Transformation 50
3.4.2 Low-pass to High-pass Transformation 50
3.4.3 Low-pass to Band-pass Transformation 50
3.4.4 Low-pass to Band-stop Transformation 51
3.5 Examples 52
3.6 Phase-oriented Design 54
3.6.1 Phase and Delay Functions 54
3.6.2 Maximally Flat Delay Response 56
3.7 Passive Filters 58
3.8 Active Filters 59
3.9 Use of MATLAB® for the Design of Analog Filters 62
3.9.1 Butterworth Filters 62
3.9.2 Chebyshev Filters 63
3.9.3 Elliptic Filters 63
3.9.4 Bessel Filters 64
3.10 Examples of the use of MATLAB® 65
3.11 A Comprehensive Application: Pulse Shaping for Data Transmission 67
3.12 Conclusion 70
Problems 72
4 Discrete Signals and Systems 75
4.1 Introduction 75
4.2 Digitization of Analog Signals 75
4.2.1 Sampling 76
4.2.2 Quantization and Encoding 84
4.3 Discrete Signals and Systems 85
4.4 Digital Filters 87
4.5 Conclusion 92
Problems 93
5 Design of Digital Filters 95
5.1 Introduction 95
5.2 General Considerations 95
5.3 Amplitude-oriented Design of IIR Filters 98
5.3.1 Low-pass Filters 98
5.3.2 High-pass Filters 105
5.3.3 Band-pass Filters 107
5.3.4 Band-stop Filters 108
5.4 Phase-oriented Design of IIR Filters 108
5.4.1 General Considerations 108
5.4.2 Maximally Flat Group-delay Response 109
5.5 FIR Filters 111
5.5.1 The Exact Linear Phase Property 111
5.5.2 Fourier-coefficient Filter Design 118
5.5.3 Monotonic Amplitude Response with the Optimum Number of Constraints 128
5.5.4 Optimum Equiripple Response in both Passband and Stopband 128
5.6 Comparison Between IIR and FIR Filters 133
5.7 Use of MATLAB® for the Design of Digital Filters 133
5.7.1 Butterworth IIR Filters 134
5.7.2 Chebyshev IIR Filters 136
5.7.3 Elliptic IIR Filters 138
5.7.4 Realization of the Filter 140
5.7.5 Linear Phase FIR Filters 140
5.8 A Comprehensive Application: Pulse Shaping for Data Transmission 142
5.8.1 Optimal Design 142
5.8.2 Use of MATLAB® for the Design of Data Transmission Filters 144
5.9 Conclusion 146
Problems 146
6 The Fast Fourier Transform and its Applications 149
6.1 Introduction 149
6.2 Periodic Signals 150
6.3 Non-periodic Signals 153
6.4 The Discrete Fourier Transform 157
6.5 The Fast Fourier Transform Algorithms 160
6.5.1 Decimation-in-time Fast Fourier Transform 161
6.5.2 Decimation-in-frequency Fast Fourier Transform 166
6.5.3 Radix 4 Fast Fourier Transform 168
6.6 Properties of the Discrete Fourier Transform 170
6.6.1 Linearity 170
6.6.2 Circular Convolution 170
6.6.3 Shifting 171
6.6.4 Symmetry and Conjugate Pairs 172
6.6.5 Parseval’s Relation and Power Spectrum 173
6.6.6 Circular Correlation 174
6.6.7 Relation to the z -transform 175
6.7 Spectral Analysis Using the FFT 176
6.7.1 Evaluation of the Fourier Integral 176
6.7.2 Evaluation of the Fourier Coefficients 178
6.8 Spectral Windows 180
6.8.1 Continuous-time Signals 180
6.8.2 Discrete-time Signals 184
6.9 Fast Convolution, Filtering and Correlation Using the FFT 184
6.9.1 Circular (Periodic) Convolution 184
6.9.2 Non-periodic Convolution 185
6.9.3 Filtering and Sectioned Convolution 185
6.9.4 Fast Correlation 188
6.10 Use of MATLAB® 190
6.11 Conclusion 190
Problems 190
7 Stochastic Signals and Power Spectra 193
7.1 Introduction 193
7.2 Random Variables 193
7.2.1 Probability Distribution Function 193
7.2.2 Probability Density Function 194
7.2.3 Joint Distributions 195
7.2.4 Statistical Parameters 195
7.3 Analog Stochastic Processes 198
7.3.1 Statistics of Stochastic Processes 198
7.3.2 Stationary Processes 200
7.3.3 Time Averages 201
7.3.4 Ergodicity 201
7.3.5 Power Spectra of Stochastic Signals 203
7.3.6 Signals through Linear Systems 207
7.4 Discrete-time Stochastic Processes 209
7.4.1 Statistical Parameters 209
7.4.2 Stationary Processes 209
7.5 Power Spectrum Estimation 213
7.5.1 Continuous-time Signals 213
7.5.2 Discrete-time Signals 216
7.6 Conclusion 217
Problems 217
8 Finite Word-length Effects in Digital Signal Processors 219
8.1 Introduction 219
8.2 Input Signal Quantization Errors 221
8.3 Coefficient Quantization Effects 225
8.4 Effect of Round-off Accumulation 227
8.4.1 Round-off Accumulation without Coefficient Quantization 228
8.4.2 Round-off Accumulation with Coefficient Quantization 235
8.5 Auto-oscillations: Overflow and Limit Cycles 238
8.5.1 Overflow Oscillations 238
8.5.2 Limit Cycles and the Dead-band Effect 241
8.6 Conclusion 244
Problems 244
9 Linear Estimation, System Modelling and Adaptive Filters 245
9.1 Introduction 245
9.2 Mean-square Approximation 245
9.2.1 Analog Signals 245
9.2.2 Discrete Signals 247
9.3 Linear Estimation, Modelling and Optimum Filters 248
9.4 Optimum Minimum Mean-square Error Analog Estimation 250
9.4.1 Smoothing by Non-causal Wiener Filters 250
9.4.2 Causal Wiener Filters 253
9.5 The Matched Filter 253
9.6 Discrete-time Linear Estimation 255
9.6.1 Non-recursive Wiener Filtering 256
9.6.2 Adaptive Filtering Using the Minimum Mean Square Error Gradient Algorithm 260
9.6.3 The Least Mean Square Error Gradient Algorithm 263
9.7 Adaptive IIR Filtering and System Modelling 263
9.8 An Application of Adaptive Filters: Echo Cancellers for Satellite Transmission of Speech Signals 266
9.9 Conclusion 267
Part III ANALOG MOS INTEGRATED CIRCUITS FOR SIGNAL PROCESSING
10 MOS Transistor Operation and Integrated Circuit Fabrication 271
10.1 Introduction 271
10.2 The MOS Transistor 271
10.2.1 Operation 272
10.2.2 The Transconductance 276
10.2.3 Channel Length Modulation 278
10.2.4 PMOS Transistors and CMOS Circuits 279
10.2.5 The Depletion-type MOSFET 280
10.3 Integrated Circuit Fabrication 280
10.3.1 Wafer Preparation 281
10.3.2 Diffusion and Ion Implantation 281
10.3.3 Oxidation 283
10.3.4 Photolithography 285
10.3.5 Chemical Vapour Deposition 286
10.3.6 Metallization 287
10.3.7 MOSFET Processing Steps 287
10.4 Layout and Area Considerations for IC MOSFETs 288
10.5 Noise In MOSFETs 290
10.5.1 Shot Noise 290
10.5.2 Thermal Noise 290
10.5.3 Flicker (1/f) Noise 290
10.5.4 Modelling of Noise 290
Problems 291
11 Basic Integrated Circuits Building Blocks 293
11.1 Introduction 293
11.2 MOS Active Resistors and Load Devices 293
11.3 MOS Amplifiers 295
11.3.1 NMOS Amplifier with Enhancement Load 295
11.3.2 Effect of the Substrate 296
11.3.3 NMOS Amplifier with Depletion Load 297
11.3.4 The Source Follower 298
11.4 High Frequency Considerations 300
11.4.1 Parasitic Capacitances 300
11.4.2 The Cascode Amplifier 303
11.5 The Current Mirror 304
11.6 The CMOS Amplifier 305
11.7 Conclusion 308
Problems 308
12 Two-stage CMOS Operational Amplifiers 311
12.1 Introduction 311
12.2 Op Amp Performance Parameters 311
12.3 Feedback Amplifier Fundamentals 314
12.4 The CMOS Differential Amplifier 316
12.5 The Two-stage CMOS Op Amp 321
12.5.1 The dc Voltage Gain 322
12.5.2 The Frequency Response 322
12.5.3 The Nulling Resistor 323
12.5.4 The Slew Rate and Settling Time 325
12.5.5 The Input Common-mode Range and CMRR 325
12.5.6 Summary of the Two-stage CMOS Op Amp Design Calculations 327
12.6 A Complete Design Example 329
12.7 Practical Considerations and Other Non-ideal Effects in Operational Amplifier Design 332
12.7.1 Power Supply Rejection 332
12.7.2 dc Offset Voltage 332
12.7.3 Noise Performance 332
12.8 Conclusion 334
Problems 334
13 High Performance CMOS Operational Amplifiers and Operational Transconductance Amplifiers 337
13.1 Introduction 337
13.2 Cascode CMOS Op Amps 337
13.3 The Folded Cascode Op Amp 338
13.4 Low-noise Operational Amplifiers 340
13.4.1 Low-noise Design by Control of Device Geometries 340
13.4.2 Noise Reduction by Correlated Double Sampling 342
13.4.3 Chopper-stabilized Operational Amplifiers 342
13.5 High-frequency Operational Amplifiers 344
13.5.1 Settling Time Considerations 345
13.6 Fully Differential Balanced Topology 346
13.7 Operational Transconductance Amplifiers 353
13.8 Conclusion 353
Problems 354
14 Capacitors, Switches and the Occasional Passive Resistor 357
14.1 Introduction 357
14.2 MOS Capacitors 357
14.2.1 Capacitor Structures 357
14.2.2 Parasitic Capacitances 358
14.2.3 Capacitor-ratio Errors 358
14.3 The MOS Switch 362
14.3.1 A Simple Switch 362
14.3.2 Clock Feed-through 362
14.3.3 The CMOS Switch: Transmission Gate 364
14.4 MOS Passive Resistors 366
14.5 Conclusion 366
Part IV SWITCHED-CAPACITOR AND MIXED-MODE SIGNAL PROCESSING
15 Design of Microelectronic Switched-capacitor Filters 369
15.1 Introduction 369
15.2 Sampled and Held Signals 371
15.3 Amplitude-oriented Filters of the Lossless Discrete Integrator Type 374
15.3.1 The State-variable Ladder Filter 374
15.3.2 Strays-insensitive LDI Ladders 381
15.3.3 An Approximate Design Technique 384
15.4 Filters Derived from Passive Lumped Prototypes 388
15.5 Cascade Design 396
15.6 Applications in Telecommunications: Speech Codecs and Data Modems 399
15.6.1 CODECs 399
15.6.2 Data Modems 399
15.7 Conclusion 400
Problems 400
16 Non-ideal Effects and Practical Considerations in Microelectronic Switched-capacitor Filters 403
16.1 Introduction 403
16.2 Effect of Finite Op Amp Gain 403
16.3 Effect of Finite Bandwidth and Slew Rate of Op Amps 405
16.4 Effect of Finite Op Amp Output Resistance 405
16.5 Scaling for Maximum Dynamic Range 405
16.6 Scaling for Minimum Capacitance 407
16.7 Fully Differential Balanced Designs 407
16.8 More on Parasitic Capacitances and Switch Noise 410
16.9 Pre-filtering and Post-filtering Requirements 412
16.10 Programmable Filters 413
16.11 Layout Considerations 415
16.12 Conclusion 416
17 Integrated Sigma-Delta Data Converters: Extension and Comprehensive Application of Analog and Digital Signal Processing 417
17.1 Motivation and General Considerations 417
17.2 The First-order Converter 419
17.3 The Second-order Converter 423
17.4 Decimation and Digital Filtering 426
17.4.1 Principles 426
17.4.2 Decimator Structures 429
17.5 Simulation and Performance Evaluation 433
17.6 A Case Study: Fourth-order Converter 435
17.7 Conclusion 438
Answers to Selected Problems 439
References 445
Index 447