Digital Signal Processing: Fundamentals and Applications, Third Edition [3rd Ed] (Complete Instructor's Resources with Solution Manual) (Solutions)

__Digital Signal Processing: Fundamentals and Applications, Third Edition,__ not only introduces students to the fundamental principles of DSP, it also provides a working knowledge that they take with them into their engineering careers. Many instructive, worked examples are used to illustrate the material, and the use of mathematics is minimized for an easier grasp of concepts. As such, this title is also useful as a reference for non-engineering students and practicing engineers. The book goes beyond DSP theory, showing the implementation of algorithms in hardware and software. Additional topics covered include adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as PCM, μ-law, ADPCM, and multi-rate DSP, over-sampling ADC subband coding, and wavelet transform. Cover 1 Digital Signal Processing: Fundamentals and Applications 3 Copyright 4 Preface 5 1 Introduction to Digital Signal Processing 8 Basic Concepts of Digital Signal Processing 8 Basic Digital Signal Processing Examples in Block Diagrams 9 Digital Filtering 10 Signal Frequency (Spectrum) Analysis 11 Overview of Typical Digital Signal Processing in Real-World Applications 12 Digital Crossover Audio System 12 Interference Cancellation in Electrocardiography 13 Speech Coding and Compression 13 Compact-Disc Recording System 14 Vibration Signature Analysis for Defected Gear Tooth 16 Digital Image Enhancement 17 Digital Signal Processing Applications 19 Summary 19 2 Signal Sampling and Quantization 20 Sampling of Continuous Signal 20 Signal Reconstruction 27 Practical Considerations for Signal Sampling: Anti-Aliasing Filtering 31 Practical Considerations for Signal Reconstruction: Anti-Image Filter and Equalizer 35 Analog-to-Digital Conversion, Digital-to-Analog Conversion, and Quantization 42 Summary 54 MATLAB Programs 55 Problems 56 3 Digital Signals and Systems 66 Digital Signals 66 Common Digital Sequences 67 Generation of Digital Signals 70 Linear Time-Invariant, Causal Systems 72 Linearity 73 Time Invariance 74 Causality 75 Difference Equations and Impulse Responses 76 Format of Difference Equation 76 System Representation Using Its Impulse Response 77 Digital Convolution 80 Bounded-Input and Bounded-Output Stability 88 Summary 89 Problems 90 4 Discrete Fourier Transform and Signal Spectrum 97 Discrete Fourier Transform 97 Fourier Series Coefficients of Periodic Digital Signals 98 Discrete Fourier Transform Formulas 102 Amplitude Spectrum and Power Spectrum 108 Spectral Estimation Using Window Functions 118 Application to Signal Spectral Estimation 127 Fast Fourier Transform 133 Method of Decimation-in-Frequency 134 Method of Decimation-in-Time 139 Summary 143 Problems 143 5 The z-Transform 149 Definition 149 Properties of the z-Transform 152 Inverse z-Transform 156 Partial Fraction Expansion and Look-Up Table 157 Partial Fraction Expansion Using MATLAB 161 Power Series Method 164 Inversion Formula Method 165 Solution of Difference Equations Using the z-Transform 168 Two-Sided z-Transform 171 Summary 173 Problems 174 6 Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations 179 Difference Equation and Digital Filtering 179 Difference Equation and Transfer Function 184 Impulse Response, Step Response, and System Response 187 The z-Plane Pole-Zero Plot and Stability 190 Digital Filter Frequency Response 196 Basic Types of Filtering 203 Realization of Digital Filters 210 Direct-Form I Realization 210 Direct-Form II Realization 211 Cascade (Series) Realization 213 Parallel Realization 213 Application: Signal Enhancement and Filtering 217 Preemphasis of Speech 217 Bandpass Filtering of Speech 220 Enhancement of ECG Signal Using Notch Filtering 223 Summary 225 Problems 225 7 Finite Impulse Response Filter Design 235 Finite Impulse Response Filter Format 235 Fourier Transform Design 237 Window Method 248 Applications: Noise Reduction and Two-Band Digital Crossover 271 Noise Reduction 271 Speech Noise Reduction 273 Noise Reduction in Vibration Signal 275 Two-Band Digital Crossover 276 Frequency Sampling Design Method 278 Optimal Design Method 288 Design of FIR Differentiator and Hilbert Transformer 299 Realization Structures of Finite Impulse Response Filters 301 Transversal Form 302 Linear Phase Form 303 Coefficient Accuracy Effects on Finite Impulse Response Filters 304 Summary of FIR Design Procedures and Selection of the FIR Filter Design Methods in Practice 307 Summary 310 MATLAB Programs 310 Problems 312 8 Infinite Impulse Response Filter Design 320 Infinite Impulse Response Filter Format 321 Bilinear Transformation Design Method 322 Analog Filters Using Lowpass Prototype Transformation 323 Bilinear Transformation and Frequency Warping 327 Bilinear Transformation Design Procedure 333 Digital Butterworth and Chebyshev Filter Designs 337 Lowpass Prototype Function and Its Order 337 Lowpass and Highpass Filter Design Examples 340 Bandpass and Bandstop Filter Design Examples 349 Higher-Order Infinite Impulse Response Filter Design Using the Cascade Method 357 Application: Digital Audio Equalizer 360 Impulse Invariant Design Method 364 Pole-Zero Placement Method for Simple Infinite Impulse Response Filters 370 Second-Order Bandpass Filter Design 371 Second-Order Bandstop (Notch) Filter Design 373 First-Order Lowpass Filter Design 374 First-Order Highpass Filter Design 377 Realization Structures of Infinite Impulse Response Filters 378 Realization of Infinite Impulse Response Filters in Direct-Form I and Direct-Form II 378 Realization of Higher-Order Infinite Impulse Response Filters Via the Cascade Form 381 Application: 60-Hz Hum Eliminator and Heart Rate Detection Using Electrocardiography 382 Coefficient Accuracy Effects on Infinite Impulse Response Filters 389 Application: Generation and Detection of DTMF Tones Using the Goertzel Algorithm 393 Single-Tone Generator 394 Dual-Tone Multifrequency Tone Generator 396 Goertzel Algorithm 397 Dual-Tone Multifrequency Tone Detection Using the Modified Goertzel Algorithm 403 Summary of Infinite Impulse Response (IIR) Design Procedures and Selection of the IIR Filter Design Methods in Practice 409 Summary 412 Problems 412 9 Adaptive Filters and Applications 425 Introduction to Least Mean Square Adaptive Finite Impulse Response Filters 425 Basic Wiener Filter Theory and Adaptive Algorithms 429 Wiener Filter Theory and Linear Prediction 429 Basic Wiener Filter Theory 429 Forward Linear Prediction 433 Steepest Descent Algorithm 437 Least Mean Square Algorithm 440 Recursive Least Squares Algorithm 441 Applications: Noise Cancellation, System Modeling, and Line Enhancement 444 Noise Cancellation 444 System Modeling 452 Line Enhancement Using Linear Prediction 458 Other Application Examples 461 Canceling Periodic Interferences Using Linear Prediction 461 Electrocardiography Interference Cancellation 462 Echo Cancellation in Long-Distance Telephone Circuits 464 Summary 465 Problems 466 10 Waveform Quantization and Compression 479 Linear Midtread Quantization 479 μ-Law Companding 482 Analog μ-Law Companding 483 Digital μ-Law Companding 487 Examples of Differential Pulse Code Modulation (DPCM), Delta Modulation, and Adaptive DPCM G.721 490 Examples of DPCM and Delta Modulation 491 Adaptive Differential Pulse Code Modulation G.721 494 Discrete Cosine Transform, Modified Discrete Cosine Transform, and Transform Coding in MPEG Audio 500 Discrete Cosine Transform 500 Modified Discrete Cosine Transform 503 Transform Coding in MPEG Audio 506 Summary 509 MATLAB Programs 510 Problems 525 11 Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandp ... 532 Multirate Digital Signal Processing Basics 532 Sampling Rate Reduction by an Integer Factor 533 Sampling Rate Increase by an Integer Factor 539 Changing Sampling Rate by a Non-Integer Factor L/M 544 Application: CD Audio Player 548 Multistage Decimation 551 Polyphase Filter Structure and Implementation 555 Oversampling of Analog-To-Digital Conversion 562 Oversampling and ADC Resolution 563 Sigma-Delta Modulation ADC 568 Application Example: CD Player 577 Undersampling of Bandpass Signals 579 Summary 586 Problems 587 MATLAB Problems 591 MATLAB Project 593 12 Subband and Wavelet-Based Coding 594 Subband Coding Basics 594 Subband Decomposition and Two-Channel Perfect Reconstruction-Quadrature Mirror Filter Bank 599 Subband Coding of Signals 607 Wavelet Basics and Families of Wavelets 610 Multiresolution Equations 622 Discrete Wavelet Transform 626 Wavelet Transform Coding of Signals 635 MATLAB Programs 641 Summary 643 Problems 644 13 Image Processing Basics 652 Image Processing Notation and Data Formats 653 8-Bit Gray Level Images 653 24-Bit Color Images 654 8-Bit Color Images 655 Intensity Images 656 RGB Components and Grayscale Conversion 657 MATLAB Functions for Format Conversion 659 Image Histogram and Equalization 661 Grayscale Histogram and Equalization 661 24-Bit Color Image Equalization 666 8-Bit Indexed Color Image Equalization 667 MATLAB Functions for Equalization 668 Image Level Adjustment and Contrast 672 Linear Level Adjustment 672 Adjusting the Level for Display 673 MATLAB Functions for Image Level Adjustment 675 Image Filtering Enhancement 676 Lowpass Noise Filtering 676 Median Filtering 680 Edge Detection 682 MATLAB Functions for Image Filtering 685 Image Pseudo-Color Generation and Detection 687 Image Spectra 690 Image Compression by Discrete Cosine Transform 694 Two-Dimensional Discrete Cosine Transform 695 Two-Dimensional JPEG Grayscale Image Compression Example 697 JPEG Color Image Compression 700 Image Compression Using Wavelet Transform Coding 704 Creating a Video Sequence by Mixing two Images 711 Video Signal Basics 712 Analog Video 712 Digital Video 717 Motion Estimation in Video 719 Summary 722 Problems 723 14 Hardware and Software for Digital Signal Processors 730 Digital Signal Processor Architecture 730 DSP Hardware Units 733 Multiplier and Accumulator 733 Shifters 734 Address Generators 734 DSPs and Manufactures 736 Fixed-Point and Floating-Point Formats 736 Fixed-Point Format 737 Floating-Point Format 744 IEEE Floating-Point Formats 748 Fixed-Point DSPs 751 Floating-Point DSPs 752 Finite Impulse Response and Infinite Impulse Response Filter Implementations in Fixed-Point Systems 754 Digital Signal Processing Programming Examples 759 Overview of TMS320C67x DSK 760 Concept of Real-Time Processing 764 Linear Buffering 764 Sample C Programs 767 Additional Real-Time DSP Examples 771 Adaptive Filtering Using the TMS320C6713 DSK 771 Signal Quantization Using the TMS320C6713 DSK 776 Sampling Rate Conversion Using the TMS320C6713 DSK 779 Summary 784 Problems 785 Appendix A: Introduction to the Matlab Environment 788 Basic Commands and Syntax 788 MATLAB Array and Indexing 792 Plot Utilities: Subplot, Plot, Stem, and Stair 793 MATLAB Script Files 794 MATLAB Functions 795 Appendix B: Review of Analog Signal Processing Basics 797 Fourier Series and Fourier Transform 797 Sine-Cosine Form 797 Amplitude-Phase Form 798 Complex Exponential Form 798 Spectral Plots 801 Fourier Transform 808 Laplace Transform 812 Laplace Transform and Its Table 812 Solving Differential Equations Using Laplace Transform 814 Transfer Function 815 Poles, Zeros, Stability, Convolution, and Sinusoidal Steady-State Response 816 Poles, Zeros, and Stability 816 Convolution 817 Sinusoidal Steady-State Response 820 Problems 822 Appendix C: Normalized Butterworth and Chebyshev Functions 826 Normalized Butterworth Function 826 Normalized Chebyshev Function 829 Appendix D: Sinusoidal Steady-State Response of Digital Filters 834 Sinusoidal Steady-State Response 834 Properties of the Sinusoidal Steady-State Response 835 Appendix E: Finite Impulse Response Filter Design Equations by Frequency Sampling Design Method 838 Appendix F: Wavelet Analysis and Synthesis Equations 842 Basic Properties 842 Analysis Equations 843 Wavelet Synthesis Equations 844 Appendix G: Review of Discrete-Time Random Signals 846 Random Variable Statistical Properties 846 Random Signal Statistical Properties 848 Wide-Sense Stationary Random Signals 849 Ergodic Signals 850 Statistical Properties of Linear System Output Signal 851 Z-Transform Domain Representation of Statistical Properties 852 Appendix H: Some Useful Mathematical Formulas 854 Answers to Selected Problems 859 References 884 Index 887 A 887 B 888 C 888 D 889 E 891 F 891 G 893 H 893 I 893 J 894 K 895 L 895 M 895 N 896 O 897 P 897 Q 897 R 898 S 898 T 899 U 900 V 900 W 900 Y 901 Z 901 Back Cover 902 This textbook presents digital signal processing (DSP) principles, applications, and hardware implementation issues, emphasizing achievable results and conclusions through the presentation of numerous worked examples, while reducing the use of mathematics for an easier grasp of the concepts. Digital Signal Processing: Fundamentals and Applications, Third Edition, not only introduces students to the fundamental principles of DSP, it also provides a working knowledge that they take with them into their engineering careers. Many instructive, worked examples are used to illustrate the material, and the use of mathematics is minimized for an easier grasp of concepts. As such, this title is also useful as a reference for non-engineering students and practicing engineers. The book goes beyond DSP theory, showing the implementation of algorithms in hardware and software. Additional topics covered include adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as PCM, ae-law, ADPCM, and multi-rate DSP, over-sampling ADC subband coding, and wavelet transform "Bridging the gap between theory and application, this text covers all the main areas of modern DSP. Principles, applications, and hardware implementation issues are presented, and a wealth of worked examples and end of chapter exercises provide the opportunity for self-learning. Throughout the book emphasis is placed on applications to signal, image, and video processing, and real time implementation of DSP algorithms using DSP processors is highlighted."--Back cover