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A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing.
In this supplementary text, MATLAB is used as a computing tool to explore traditional DSP topics and solve problems to gain insight. This greatly expands the range and complexity of problems that students can effectively study in the course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, a fair amount of programming is required. Using interactive software such as MATLAB makes it possible to place more emphasis on learning new and difficult concepts than on programming algorithms. Interesting practical examples are discussed and useful problems are explored. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates and extends the chapters in the previous edition and includes two new chapters on MIMO systems, Correlation and Eigen analysis and independent component analysis. The wide range of topics covered in this book include Wiener filters, echo cancellation, channel equalisation, spectral estimation, detection and removal of impulsive and transient noise, interpolation of missing data segments, speech enhancement and noise/interference in mobile communication environments. This book provides a coherent and structured presentation of the theory and applications of statistical signal processing and noise reduction methods. Two new chapters on MIMO systems, correlation and Eigen analysis and independent component analysis Comprehensive coverage of advanced digital signal processing and noise reduction methods for communication and information processing systems Examples and applications in signal and information extraction from noisy data Comprehensive but accessible coverage of signal processing theory including probability models, Bayesian inference, hidden Markov models, adaptive filters and Linear prediction models Advanced Digital Signal Processing and Noise Reduction is an invaluable text for postgraduates, senior undergraduates and researchers in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be of interest to professional engineers in telecommunications and audio and signal processing industries and network planners and implementers in mobile and wireless communication communities.
Based on Sanjit Mitra’s extensive teaching and research experience, Digital Signal Processing, A Computer Based Approach, fourth edition, is written with the reader in mind. A key feature of this book is the extensive use of MATLAB-based examples that illustrate the program's powerful capability to solve signal processing problems. The book is intended for a course on digital signal processing for seniors or first-year graduate students. This highly popular book introduces the tools used in the analysis and design of discrete-time systems for signal processing. A number of changes have been made to the book’s content, based on reviewer and student comments.
This textbook offers a fresh approach to digital signal processing (DSP) that combines heuristic reasoning and physical appreciation with sound mathematical methods to illuminate DSP concepts and practices. It uses metaphors, analogies and creative explanations, along with examples and exercises to provide deep and intuitive insights into DSP concepts. Practical DSP requires hybrid systems including both discrete- and continuous-time components. This book follows a holistic approach and presents discrete-time processing as a seamless continuation of continuous-time signals and systems, beginning with a review of continuous-time signals and systems, frequency response, and filtering. The synergistic combination of continuous-time and discrete-time perspectives leads to a deeper appreciation and understanding of DSP concepts and practices. • For upper-level undergraduates • Illustrates concepts with 500 high-quality figures, more than 170 fully worked examples, and hundreds of end-of-chapter problems, more than 150 drill exercises, including complete and detailed solutions • Seamlessly integrates MATLAB throughout the text to enhance learning
Digital Signal Processing: A Computer-Based Approach is intended for a two-semester course on digital signal processing for seniors or first-year graduate students. The prerequisite for this book is a junior-level course in linear continuous-time and discrete-time systems, which is usually required in most universities. A key feature of this book is the extensive use of MATLAB-based examples that illustrate the program's powerful capability to solve signal processing problems. Practical examples and applications bring the theory to life. This popular book introduces the tools used in the analysis and design of discrete-time systems for signal processing.
The book is not an exposition on digital signal processing (DSP) but rather a treatise on digital filters. The material and coverage is comprehensive, presented in a consistent that first develops topics and subtopics in terms it their purpose, relationship to other core ideas, theoretical and conceptual framework, and finally instruction in the implementation of digital filter devices. Each major study is supported by Matlab-enabled activities and examples, with each Chapter culminating in a comprehensive design case study.
Nowadays, many aspects of electrical and electronic engineering are essentially applications of DSP. This is due to the focus on processing information in the form of digital signals, using certain DSP hardware designed to execute software. Fundamental topics in digital signal processing are introduced with theory, analytical tables, and applications with simulation tools. The book provides a collection of solved problems on digital signal processing and statistical signal processing. The solutions are based directly on the math-formulas given in extensive tables throughout the book, so the reader can solve practical problems on signal processing quickly and efficiently.
Ein Kompendium für Mediziner, Informatiker, Qualitätsmanager und Epidemiologen
Author: Roswitha Jehle,Johanna Christina Czeschik,Torsten Freund,Ernst Wellnhofer
Publisher: Walter de Gruyter GmbH & Co KG
Das kompakte Lehrbuch gibt einen umfassenden Überblick über die informatischen Grundlagen zur Signal-, Bild- und Datenverarbeitung sowie zu vernetzten Systemen. Es richtet sich an Ärzte, Studenten der Informatik und Medizininformatik, DRG-Beauftragte, Medizintechniker, Gerätebeauftragte und Leiter von Telemedizinprojekten. Das Buch deckt das Prüfungsgebiet der Zusatzbezeichnung Medizinische Informatik ab.
Wer die Methoden der digitalen Signalverarbeitung erlernen oder anwenden will, kommt ohne das weltweit bekannte, neu gefaßte Standardwerk "Oppenheim/Schafer" nicht aus. Die Beliebtheit des Buches beruht auf den didaktisch hervorragenden Einführungen, der umfassenden und tiefgreifenden Darstellung der Grundlagen, der kompetenten Berücksichtigung moderner Weiterentwicklungen und der Vielzahl verständnisfördernder Aufgaben.
Keeping pace with the expanding, ever more complex applications of DSP, this authoritative presentation of computational algorithms for statistical signal processing focuses on advanced topics ignored by other books on the subject. Algorithms for Convolution and DFT. Linear Prediction and Optimum Linear Filters. Least-Squares Methods for System Modeling and Filter Design. Adaptive Filters. Recursive Least-Squares Algorithms for Array Signal Processing. QRD-Based Fast Adaptive Filter Algorithms. Power Spectrum Estimation. Signal Analysis with Higher-Order Spectra. For Electrical Engineers, Computer Engineers, Computer Scientists, and Applied Mathematicians.
PREFACE In January 1978, I began the preface to the first edition of Digital Image Processing with the following statement: “The field of image processing has grown considerably during the past decade with the increased utilization of imagery in myriad applications coupled with improvements in the size, speed and cost effectiveness of digital computers and related signal processing technologies. Image processing has found a significant role in scientific, industrial, space and government applications.” In January 1991, in the preface to the second edition, I stated: “Thirteen years later as I write this preface to the second edition, I find the quoted statement still to be valid. The 1980s have been a decade of significant growth and maturity in this field. At the beginning of that decade, many image processing techniques were of academic interest only; their execution was too slow and too costly. Today, thanks to algorithmic and implementation advances, image processing has become a vital cost-effective technology in a host of applications.” In August 2000, in the preface to the third edition, I wrote: “Now, in this beginning of the twenty-first century, image processing has become a mature engineering discipline. But advances in the theoretical basis of image processing continue. Some of the reasons for this third edition of the book are to correct defects in the second edition, delete content of marginal interest, and add discussion of new, important topics. Another motivating factor is the inclusion of interactive, computer display xiv PREFACE imaging examples to illustrate image processing concepts. Finally, this third edition includes computer programming exercises to bolster its theoretical content. These exercises can be implemented using the Programmer’s Imaging Kernel System (PIKS) application program interface (API). PIKS is an International Standards Organization (ISO) standard library of image processing operators and associated utilities.” Again, for a fourth time, a new edition of Digital Image Processing is offered to the image processing community. Why? One reason is because advances in the theoretical aspects of image processing technology continue at a rapid rate. For example, in the year 2005, the IEEE Transactions on Image Processing published 2191 pages of research papers. The IEEE Transactions on Pattern Analysis and Machine Intelligence was in close second place in 2005 with 2002 published pages. Add to that the content of independent journals, such as the John Wiley & Sons International Journal of Imaging Systems and Technology plus numerous image processing technical conferences. There is an enormous amount of new image processing technology to be absorbed. I have tried to act as a publishing filter by culling through the image processing literature since the third edition was published in 2002, and then abstracting what I think are the most important contributions. Details follow. Another reason for publication of the fourth edition of Digital Image Processing is to make available, at no cost, the PIKS Scientific API for educational purposes and for industrial software development. The PIKS Scientific software is on a CD affixed to the back cover of this book. PIKS Scientific includes implementations of most of the high-level operators in this book. The book is intended to be an “industrial strength” introduction to digital image processing to be used as a text for an electrical engineering or computer science course on the subject. Also, it can be used as a reference manual for scientists who are engaged in image processing research, developers of image processing hardware and software systems, and practicing engineers and scientists who use image processing as a tool in their applications. Mathematical derivations are provided for most algorithms. The reader is assumed to have a basic background in linear system theory, vector space algebra and random processes. Proficiency in C language programming is necessary for execution of the image processing programming exercises using PIKS. The book is divided into six parts. The first three parts cover the basic technologies that are needed to support image processing applications. Part 1 contains three chapters concerned with the characterization of continuous images. Topics include the mathematical representation of continuous images, the psychophysical properties of human vision, and photometry and colorimetry. No substantial changes have been made to this fundamental material. In Part 2, image sampling and quantization techniques are explored along with the mathematical representation of discrete images. A new section on Color Image Sampling Systems, such as the Bayer color filter, has been added to Chapter 4. Part 3 discusses two-dimensional signal processing techniques, including general linear operators and unitary transforms such as the Fourier, Hadamard, Daubechies and Karhunen–Loeve transforms. The final chapter in Part 3 analyzes and compares PREFACE xv linear processing techniques implemented by direct convolution and Fourier domain filtering. The next two parts of the book cover the two principal application areas of image processing: Image Improvement and Image Analysis. Part 4 presents a discussion of image enhancement and restoration techniques, including restoration models, point and spatial restoration and geometrical image modification. Chapter 10 on Image Enhancement contains new material on Contrast Manipulation, Histogram Modification Noise Cleaning and Color Image Enhancement. Content on Blind Image Restoration and Multi-Plane Image Restoration has been added to Chapter 12, Image Restoration Techniques. A new section on Polar Coordinate Conversion has been included in the chapter on Geometrical Image Modification. Part 5, entitled Image Analysis, concentrates on the extraction of information from an image. Specific topics include morphological image processing, edge detection, image feature extraction, image segmentation, object shape analysis and object detection. Additional material on Structuring Element Decomposition has been included in the Morphological Image Processing chapter. The sections on First Order Derivative Edge Detection and Color Edge Detection in Chapter 15 have been augmented. Material has been added on Texture Features in Chapter 16. In the chapter on Image Segmentation, material has been added on Amplitude, Region, Boundary and Texture Segmentation. New content on Distance, Perimeter and Area Measurements has been added to the Shape Analysis chapter. A new section on Non-morphological Thinning and Skeletonizing has been included in the chapter. Finally, new material has been added on Template Matching and Image Registration in Chapter 19. Part 6 discusses the software implementation of image processing applications. This part describes the PIKS API and explains its use as a means of implementing image processing algorithms. Image processing programming exercises are included in Part 6. Throughout the first 19 chapters on the theoretical basis of image processing, upto- date references of papers judged to be of significance have been included as a guide for extended study. Although readers should find this book reasonably comprehensive, many important topics allied to the field of digital image processing have been omitted to limit the size and cost of the book. Among the most prominent omissions are the topics of pattern recognition, image reconstruction from projections, image understanding, image coding, scientific visualization and computer graphics. WILLIAM K. PRATT Los Altos, California
Introduce your students to image processing with the industry's most prized text For 40 years, Image Processing has been the foundational text for the study of digital image processing. The book is suited for students at the college senior and first-year graduate level with prior background in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. As in all earlier editions, the focus of this edition of the book is on fundamentals. The 4th Edition, which celebrates the book's 40th anniversary, is based on an extensive survey of faculty, students, and independent readers in 150 institutions from 30 countries. Their feedback led to expanded or new coverage of topics such as deep learning and deep neural networks, including convolutional neural nets, the scale-invariant feature transform (SIFT), maximally-stable extremal regions (MSERs), graph cuts, k-means clustering and superpixels, active contours (snakes and level sets), and exact histogram matching. Major improvements were made in reorganizing the material on image transforms into a more cohesive presentation, and in the discussion of spatial kernels and spatial filtering. Major revisions and additions were made to examples and homework exercises throughout the book. For the first time, we added MATLAB projects at the end of every chapter, and compiled support packages for you and your teacher containing, solutions, image databases, and sample code.
Author: John H.L. Hansen,Pinar Boyraz,Kazuya Takeda,Hüseyin Abut
Publisher: Springer Science & Business Media
Category: Technology & Engineering
Compiled from papers of the 4th Biennial Workshop on DSP (Digital Signal Processing) for In-Vehicle Systems and Safety this edited collection features world-class experts from diverse fields focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. Digital Signal Processing for In-Vehicle Systems and Safety presents new approaches on how to reduce driver inattention and prevent road accidents. The material addresses DSP technologies in adaptive automobiles, in-vehicle dialogue systems, human machine interfaces, video and audio processing, and in-vehicle speech systems. The volume also features recent advances in Smart-Car technology, coverage of autonomous vehicles that drive themselves, and information on multi-sensor fusion for driver ID and robust driver monitoring. Digital Signal Processing for In-Vehicle Systems and Safety is useful for engineering researchers, students, automotive manufacturers, government foundations and engineers working in the areas of control engineering, signal processing, audio-video processing, bio-mechanics, human factors and transportation engineering.
The demand for data traffic over mobile communication networks has substantially increased during the last decade. As a result, these mobile broadband devices spend the available spectrum fiercely, requiring the search for new technologies. In transmissions where the channel presents a frequency-selective behavior, multicarrier modulation (MCM) schemes have proven to be more efficient, in terms of spectral usage, than conventional modulations and spread spectrum techniques. The orthogonal frequency-division multiplexing (OFDM) is the most popular MCM method, since it not only increases spectral efficiency but also yields simple transceivers. All OFDM-based systems, including the single-carrier with frequency-division equalization (SC-FD), transmit redundancy in order to cope with the problem of interference among symbols. This book presents OFDM-inspired systems that are able to, at most, halve the amount of redundancy used by OFDM systems while keeping the computational complexity comparable. Such systems, herein called memoryless linear time-invariant (LTI) transceivers with reduced redundancy, require low-complexity arithmetical operations and fast algorithms. In addition, whenever the block transmitter and receiver have memory and/or are linear time-varying (LTV), it is possible to reduce the redundancy in the transmission even further, as also discussed in this book. For the transceivers with memory it is possible to eliminate the redundancy at the cost of making the channel equalization more difficult. Moreover, when time-varying block transceivers are also employed, then the amount of redundancy can be as low as a single symbol per block, regardless of the size of the channel memory. With the techniques presented in the book it is possible to address what lies beyond the use of OFDM-related solutions in broadband transmissions. Table of Contents: The Big Picture / Transmultiplexers / OFDM / Memoryless LTI Transceivers with Reduced Redundancy / FIR LTV Transceivers with Reduced Redundancy
A straightforward, easy-to-read introduction to the finite-difference time-domain (FDTD) method Finite-difference time-domain (FDTD) is one of the primary computational electrodynamics modeling techniques available. Since it is a time-domain method, FDTD solutions can cover a wide frequency range with a single simulation run and treat nonlinear material properties in a natural way. Written in a tutorial fashion, starting with the simplest programs and guiding the reader up from one-dimensional to the more complex, three-dimensional programs, this book provides a simple, yet comprehensive introduction to the most widely used method for electromagnetic simulation. This fully updated edition presents many new applications, including the FDTD method being used in the design and analysis of highly resonant radio frequency (RF) coils often used for MRI. Each chapter contains a concise explanation of an essential concept and instruction on its implementation into computer code. Projects that increase in complexity are included, ranging from simulations in free space to propagation in dispersive media. Additionally, the text offers downloadable MATLAB and C programming languages from the book support site (http://booksupport.wiley.com). Simple to read and classroom-tested, Electromagnetic Simulation Using the FDTD Method is a useful reference for practicing engineers as well as undergraduate and graduate engineering students.
Understand the RF and Digital Signal Processing Principles Driving Software-defined Radios! Software-defined radio (SDR) technology is a configurable, low cost, and power efficient solution for multimode and multistandard wireless designs. This book describes software-defined radio concepts and design principles from the perspective of RF and digital signal processing as performed within this system. After an introductory overview of essential SDR concepts, this book examines signal modulation techniques, RF and digital system analysis and requirements, Nyquist and oversampled data conversion techniques, and multirate digital signal processing.. KEY TOPICS •Modulation techniques Master analog and digital modulation schemes •RF system-design parameters Examine noise and link budget analysis and Non-linear signal analysis and design methodology •Essentials of baseband and bandpass sampling and gain control IF sampling architecture compared to traditional quadrature sampling, Nyquist zones, automatic gain control, and filtering •Nyquist sampling converter architectures Analysis and design of various Nyquist data converters •Oversampled data converter architectures Analysis and design of continuous-time and discrete-time Delta-Sigma converters •Multirate signal processing Gain knowledge of interpolation, decimation, and fractional data rate conversion *Offers readers a powerful set of analytical and design tools *Details real world designs *Comprehensive coverage makes this a must have in the RF/Wireless industry