Torrent Signal Processing First Problems. Answer this job interview question to determine if you are prepared for a successful job interview. Digital Signal Processing (DSP) Return to www.101science.com home page. Digital signal processing is still a new technology and is rapidly developing. The Apollo FireWire audio interface gives you. Solutions to Exercises in Chapter 5. 2 June, 2016 - 15:17. In discrete-time signal processing, an amplifier amounts to a multiplication, a very easy operation to perform. The delay is not computational delay here the plot shows the first output value is aligned with the filter's first input although in real systems this is an important.

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Description

Digital Signal Processing, Second Edition enables electrical engineers and technicians in the fields of biomedical, computer, and electronics engineering to master the essential fundamentals of DSP principles and practice. Many instructive worked examples are used to illustrate the material, and the use of mathematics is minimized for easier grasp of concepts. As such, this title is also useful to undergraduates in electrical engineering, and as a reference for science students and practicing engineers.

The book goes beyond DSP theory, to show 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, u-law, ADPCM, and multi-rate DSP and over-sampling ADC.

New to this edition:

• MATLAB projects dealing with practical applications added throughout the book
• New chapter (chapter 13) covering sub-band coding and wavelet transforms, methods that have become popular in the DSP field
• New applications included in many chapters, including applications of DFT to seismic signals, electrocardiography data, and vibration signals
• All real-time C programs revised for the TMS320C6713 DSK

• Covers DSP principles with emphasis on communications and control applications
• Chapter objectives, worked examples, and end-of-chapter exercises aid the reader in grasping key concepts and solving related problems
• Website with MATLAB programs for simulation and C programs for real-time DSP

Readership

This book is targeted to meet the needs of electrical engineers and technicians who design and build hardware and software for DSP systems.

This textbook can also be used in an introductory DSP course at the junior level in undergraduate electrical engineering program at traditional colleges. Additionally, the book should be useful as a reference for undergraduate engineering students, science students, and practicing engineers

Preface

Chapter 1. Introduction to Digital Signal Processing

Objectives

1.1 Basic Concepts of Digital Signal Processing

1.2 Basic Digital Signal Processing Examples in Block Diagrams

1.3 Overview of Typical Digital Signal Processing in Real-World Applications

1.4 Digital Signal Processing Applications

1.5 Summary

Chapter 2. Signal Sampling and Quantization

Objectives

2.1 Sampling of Continuous Signal

2.2 Signal Reconstruction

2.3 Analog-to-Digital Conversion, Digital-to-Analog Conversion, and Quantization

2.4 Summary

2.5 MATLAB Programs

Chapter 3. Digital Signals and Systems

Objectives

3.1 Digital Signals

3.2 Linear Time-Invariant, Causal Systems

3.3 Difference Equations and Impulse Responses

3.4 Bounded-In and Bounded-Out Stability

3.5 Digital Convolution

3.6 Summary

Chapter 4. Discrete Fourier Transform and Signal Spectrum

Objectives

4.1 Discrete Fourier Transform

4.2 Amplitude Spectrum and Power Spectrum

4.3 Spectral Estimation Using Window Functions

4.4 Application to Signal Spectral Estimation

4.5 Fast Fourier Transform

4.6 Summary

Chapter 5. The z-Transform

Objectives

5.1 Definition

5.2 Properties of the z-Transform

5.3 Inverse z-Transform

5.4 Solution of Difference Equations Using the z-Transform

5.5 Summary

Chapter 6. Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations

Objectives:

6.1 The Difference Equation and Digital Filtering

6.2 Difference Equation and Transfer Function

6.3 The z-Plane Pole-Zero Plot and Stability

6.4 Digital Filter Frequency Response

6.5 Basic Types of Filtering

6.6 Realization of Digital Filters

6.7 Application: Signal Enhancement and Filtering

6.8 Summary

Signal Processing First

Chapter 7. Finite Impulse Response Filter Design

Objectives:

7.1 Finite Impulse Response Filter Format

7.2 Fourier Transform Design

7.3 Window Method

7.4 Applications: Noise Reduction and Two-Band Digital Crossover

7.5 Frequency Sampling Design Method

7.6 Optimal Design Method

7.7 Realization Structures of Finite Impulse Response Filters

7.8 Coefficient Accuracy Effects on Finite Impulse Response Filters

7.9 Summary of FIR Design Procedures and Selection of FIR Filter Design Methods in Practice

7.10 Summary

7.11 MATLAB Programs

Chapter 8. Infinite Impulse Response Filter Design

OBJECTIVES:

8.1 Infinite Impulse Response Filter Format

8.2 Bilinear Transformation Design Method

8.3 Digital Butterworth and Chebyshev Filter Designs

8.4 Higher-Order Infinite Impulse Response Filter Design Using the Cascade Method

8.5 Application: Digital Audio Equalizer

8.6 Impulse-Invariant Design Method

8.7 Pole-Zero Placement Method for Simple Infinite Impulse Response Filters

8.8 Realization Structures of Infinite Impulse Response Filters

8.9 Application: 60-Hz Hum Eliminator and Heart Rate Detection Using Electrocardiography

8.10 Coefficient Accuracy Effects on Infinite Impulse Response Filters

Signal Processing First Cd

8.11 Application: Generation and Detection of DTMF Tones Using the Goertzel Algorithm

8.12 Summary of Infinite Impulse Response (IIR) Design Procedures and Selection of the IIR Filter Design Methods in Practice

8.13 Summary

Chapter 9. Hardware and Software for Digital Signal Processors

Objectives

9.1 Digital Signal Processor Architecture

9.2 Digital Signal Processor Hardware Units

9.3 Digital Signal Processors and Manufacturers

9.4 Fixed-Point and Floating-Point Formats

9.5 Finite Impulse Response and Infinite Impulse Response Filter Implementations in Fixed-Point Systems

9.6 Digital Signal Processing Programming Examples

9.7 Summary

Chapter 10. Adaptive Filters and Applications

Objectives

10.1 Introduction to Least Mean Square Adaptive Finite Impulse Response Filters

10.2 Basic Wiener Filter Theory and Least Mean Square Algorithm

10.3 Applications: Noise Cancellation, System Modeling, and Line Enhancement

10.4 Other Application Examples

10.5 Laboratory Examples Using the TMS320C6713 DSK

10.6 Summary

Chapter 11. Waveform Quantization and Compression

Objectives

11.1 Linear Midtread Quantization

11.2 μ-law Companding

11.3 Examples of Differential Pulse Code Modulation (DPCM), Delta Modulation, and Adaptive DPCM G.721

11.4 Discrete Cosine Transform, Modified Discrete Cosine Transform, and Transform Coding in MPEG Audio

11.5 Laboratory Examples of Signal Quantization Using the TMS320C6713 DSK

11.6 Summary

11.7 MATLAB Programs

Chapter 12. Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpass Signals

Objectives

12.1 Multirate Digital Signal Processing Basics

12.2 Polyphase Filter Structure and Implementation

12.3 Oversampling of Analog-to-Digital Conversion

12.4 Application Example: CD Player

12.5 Undersampling of Bandpass Signals

12.6 Sampling Rate Conversion Using the TMS320C6713 DSK

12.7 Summary

Chapter 13. Subband- and Wavelet-Based Coding

Objectives

13.1 Subband Coding Basics

13.2 Subband Decomposition and Two-Channel Perfect Reconstruction Quadrature Mirror Filter Bank

13.3 Subband Coding of Signals

13.4 Wavelet Basics and Families of Wavelets

13.5 Multiresolution Equations

13.6 Discrete Wavelet Transform

13.7 Wavelet Transform Coding of Signals

13.8 MATLAB Programs

13.9 Summary

Chapter 14. Image Processing Basics

Objectives

14.1 Image Processing Notation and Data Formats

14.2 Image Histogram and Equalization

14.3 Image Level Adjustment and Contrast

14.4 Image Filtering Enhancement

14.5 Image Pseudo-Color Generation and Detection

14.6 Image Spectra

Signal Processing First Pdf

14.7 Image Compression by Discrete Cosine Transform

14.8 Creating a Video Sequence by Mixing Two Images

14.9 Video Signal Basics

14.10 Motion Estimation in Video

14.11 Summary

Appendix A. Introduction to the MATLAB Environment

A.1 Basic Commands and Syntax

A.2 MATLAB Arrays and Indexing

A.3 Plot Utilities: subplot, plot, stem, and stair

A.4 MATLAB Script Files

A.5 MATLAB Functions

Appendix B. Review of Analog Signal Processing Basics

B.1 Fourier Series and Fourier Transform

B.2 Laplace Transform

B.3 Poles, Zeros, Stability, Convolution, and Sinusoidal Steady-State Response

Appendix C. Normalized Butterworth and Chebyshev Functions

C.1 Normalized Butterworth Function

C.2 Normalized Chebyshev Function

Appendix D. Sinusoidal Steady-State Response of Digital Filters

D.1 Sinusoidal Steady-State Response

Appendix E. Finite Impulse Response Filter Design Equations by the Frequency Sampling Design Method

Appendix F. Wavelet Analysis and Synthesis Equations

F.1 Basic Properties

F.2 Analysis Equations

F.2 Wavelet Synthesis Equations

Appendix G. Some Useful Mathematical Formulas

Signal Processing First

Appendix 8. Answers to Selected Problems

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

Chapter 8

Chapter 9

Chapter 10

Chapter 11

Chapter 12

Chapter 13

Chapter 14

Appendix B

References

Index

Details

Lizhe Tan

Lizhe Tan is a professor in the Department of Electrical and Computer Engineering at Purdue University Northwest. He received his Ph.D. degree in Electrical Engineering from the University of New Mexico, Albuquerque, in 1992. Dr. Tan has extensively taught signals and systems, digital signal processing, analog and digital control systems, and communication systems for many years. He has published a number of refereed technical articles in journals, conference papers and book chapters in the areas of digital signal processing. He has authored and co-authored 4 textbooks, and holds a US patent. Dr. Tan is a senior member of the IEEE and has served as an associate editor for several engineering journals.

Professor, Electrical Engineering, Purdue University Northwest, IN, USA

Jean Jiang

Jean Jiang is an associate professor in the Department of Engineering Technology at Purdue University Northwest. She received her Ph.D. degree in Electrical Engineering from the University of New Mexico, Albuquerque, in 1992. Dr. Jiang has taught digital signal processing, control systems and communication systems for many years. She has published a number of refereed technical articles in journals, conference papers and book chapters in the area of digital signal processing, and co-authored 4 textbooks. Dr. Jiang is a senior member of the IEEE.

Engineering Technology, Purdue University Northwest, IN, USA

Ratings and Reviews

Digital Signal Processing, Second Edition enables electrical engineers and technicians in the fields of biomedical, computer, and electronics engineering to master the essential fundamentals of DSP principles and practice. Many instructive worked examples are used to illustrate the material, and the use of mathematics is minimized for easier grasp of concepts. As such, this title is also useful to undergraduates in electrical engineering, and as a reference for science students and practicing engineers.

The book goes beyond DSP theory, to show 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, u-law, ADPCM, and multi-rate DSP and over-sampling ADC.

New to this edition:

• MATLAB projects dealing with practical applications added throughout the book
• New chapter (chapter 13) covering sub-band coding and wavelet transforms, methods that have become popular in the DSP field
• New applications included in many chapters, including applications of DFT to seismic signals, electrocardiography data, and vibration signals
• All real-time C programs revised for the TMS320C6713 DSK

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Signal Processing First Torrent