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This book is intended to fill the gap between the "ideal precision" digital signal processing (DSP) that is widely taught, and the limited precision implementation skills that are commonly required in fixed-point processors and field programmable gate arrays (FPGAs). These skills are often neglected at the university level, particularly for undergraduates. We have attempted to create a resource both for a DSP elective course and for the practicing engineer with a need to understand fixed-point implementation. Although we assume a background in DSP, Chapter 2 contains a review of basic theory and Chapter 3 reviews random processes to support the noise model of quantization error. Chapter 4 details the binary arithmetic that underlies fixed-point processors and then introduces fractional format for binary numbers. Chapter 5 covers the noise model for quantization error and the effects of coefficient quantization in filters. Because of the numerical sensitivity of IIR filters, they are used extensively as an example system in both Chapters 5 and 6. Fortunately, the principles of dealing with limited precision can be applied to a wide variety of numerically sensitive systems, not just IIR filters. Chapter 6 discusses the problems of product roundoff error and various methods of scaling to avoid overflow. Chapter 7 discusses limit cycle effects and a few common methods for minimizing them. There are a number of simple exercises integrated into the text to allow you to test your understanding. Answers to the exercises are included in the footnotes. A number of MATLAB examples are provided in the text. They generally assume access to the Fixed-Point Toolbox. If you lack access to this software, consider either purchasing or requesting an evaluation license from The Mathworks. The code listed in the text and other helpful MATLAB code is also available at http: //www.morganclaypool.com/page/padgett and http: //www.rose-hulman.edu/padgett/fpsp. You will also find MATLAB exercises designed to demonstrate each of the four types of error discussed in Chapters 5 and 6. Simulink examples are also provided on the web site. Table of Contents: Getting Started / DSP Concepts / Random Processes and Noise / Fixed Point Numbers / Quantization Effects: Data and Coefficients / Quantization Effects - Round-Off Noise and Overflow / Limit Cycles
This book is intended to fill the gap between the ""ideal precision"" digital signal processing (DSP) that is widely taught, and the limited precision implementation skills that are commonly required in fixed-point processors and field programmable gate arrays (FPGAs). These skills are often neglected at the university level, particularly for undergraduates. We have attempted to create a resource both for a DSP elective course and for the practicing engineer with a need to understand fixed-point implementation. Although we assume a background in DSP, Chapter 2 contains a review of basic theory and Chapter 3 reviews random processes to support the noise model of quantization error. Chapter 4 details the binary arithmetic that underlies fixed-point processors and then introduces fractional format for binary numbers. Chapter 5 covers the noise model for quantization error and the effects of coefficient quantization in filters. Because of the numerical sensitivity of IIR filters, they are used extensively as an example system in both Chapters 5 and 6. Fortunately, the principles of dealing with limited precision can be applied to a wide variety of numerically sensitive systems, not just IIR filters. Chapter 6 discusses the problems of product roundoff error and various methods of scaling to avoid overflow. Chapter 7 discusses limit cycle effects and a few common methods for minimizing them. There are a number of simple exercises integrated into the text to allow you to test your understanding. Answers to the exercises are included in the footnotes. A number of MATLAB examples are provided in the text. They generally assume access to the Fixed-Point Toolbox. If you lack access to this software, consider either purchasing or requesting an evaluation license from The Mathworks. The code listed in the text and other helpful MATLAB code is also available at http://www.morganclaypool.com/page/padgett and http://www.rose-hulman.edu/padgett/fpsp. You will also find MATLAB exercises designed to demonstrate each of the four types of error discussed in Chapters 5 and 6. Simulink examples are also provided on the web site. Table of Contents: Getting Started / DSP Concepts / Random Processes and Noise / Fixed Point Numbers / Quantization Effects: Data and Coefficients / Quantization Effects - Round-Off Noise and Overflow / Limit Cycles
Digital Signal Processing has undergone enormous growth in usage/implementation in the last 20 years and many engineering schools are now offering real-time DSP courses in their undergraduate curricula. Our everyday lives involve the use of DSP systems in things such as cell phones and high-speed modems; Texas Instruments has introduced the TMS320C6000 DSP processor family to meet the high performance demands of today's signal processing applications.This book provides the know-how for the implementation and optimization of computationally intensive signal processing algorithms on the Texas Instruments family of TMS320C6000 DSP processors. It is organized in such a way that it can be used as the textbook for DSP lab courses offered at many engineering schools or as a self-study/reference for those familiar with DSP but not this family of processors.This book provides a restructured, modified, and condensed version of the information in more than twenty TI manuals so that one can learn real-time DSP implementations on the C6000 family in a structured course, within one semester. Each chapter is followed by an appropriate lab exercise to provide the hands-on lab material for implementing appropriate signal processing functions. - Each chapter is followed by an appropriate lab exercise - Provides the hands-on lab material for implementing appropriate signal processing functions
Digital Signal Processing 101: Everything You Need to Know to Get Started provides a basic tutorial on digital signal processing (DSP). Beginning with discussions of numerical representation and complex numbers and exponentials, it goes on to explain difficult concepts such as sampling, aliasing, imaginary numbers, and frequency response. It does so using easy-to-understand examples and a minimum of mathematics. In addition, there is an overview of the DSP functions and implementation used in several DSP-intensive fields or applications, from error correction to CDMA mobile communication to airborne radar systems. This book is intended for those who have absolutely no previous experience with DSP, but are comfortable with high-school-level math skills. It is also for those who work in or provide components for industries that are made possible by DSP. Sample industries include wireless mobile phone and infrastructure equipment, broadcast and cable video, DSL modems, satellite communications, medical imaging, audio, radar, sonar, surveillance, and electrical motor control. - Dismayed when presented with a mass of equations as an explanation of DSP? This is the book for you! - Clear examples and a non-mathematical approach gets you up to speed with DSP - Includes an overview of the DSP functions and implementation used in typical DSP-intensive applications, including error correction, CDMA mobile communication, and radar systems
This CD contains five appendices from the book and programs (MATLAB, Simulink, C, and TMS320C5000 assembly) with their associated data files.
Real-time Digital Signal Processing: Implementations and Applications has been completely updated and revised for the 2nd edition and remains the only book on DSP to provide an overview of DSP theory and programming with hands-on experiments using MATLAB, C and the newest fixed-point processors from Texas Instruments (TI).
Digital Design of Signal Processing Systems discusses a spectrum of architectures and methods for effective implementation of algorithms in hardware (HW). Encompassing all facets of the subject this book includes conversion of algorithms from floating-point to fixed-point format, parallel architectures for basic computational blocks, Verilog Hardware Description Language (HDL), SystemVerilog and coding guidelines for synthesis. The book also covers system level design of Multi Processor System on Chip (MPSoC); a consideration of different design methodologies including Network on Chip (NoC) and Kahn Process Network (KPN) based connectivity among processing elements. A special emphasis is placed on implementing streaming applications like a digital communication system in HW. Several novel architectures for implementing commonly used algorithms in signal processing are also revealed. With a comprehensive coverage of topics the book provides an appropriate mix of examples to illustrate the design methodology. Key Features: A practical guide to designing efficient digital systems, covering the complete spectrum of digital design from a digital signal processing perspective Provides a full account of HW building blocks and their architectures, while also elaborating effective use of embedded computational resources such as multipliers, adders and memories in FPGAs Covers a system level architecture using NoC and KPN for streaming applications, giving examples of structuring MATLAB code and its easy mapping in HW for these applications Explains state machine based and Micro-Program architectures with comprehensive case studies for mapping complex applications The techniques and examples discussed in this book are used in the award winning products from the Center for Advanced Research in Engineering (CARE). Software Defined Radio, 10 Gigabit VoIP monitoring system and Digital Surveillance equipment has respectively won APICTA (Asia Pacific Information and Communication Alliance) awards in 2010 for their unique and effective designs.
This textbook introduces readers to digital signal processing fundamentals using Arm Cortex-M based microcontrollers as demonstrator platforms. It covers foundational concepts, principles and techniques such as signals and systems, sampling, reconstruction and anti-aliasing, FIR and IIR filter design, transforms, and adaptive signal processing.
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