K.C. Chang presents an integrated approach to digital design principles, processes, and implementations to help the reader design increasingly complex systems within shorter design cycles. Chang introduces digital design concepts, VHDL coding, VHDL simulation, synthesis commands, and strategies together.

"Digital Systems Design with VHDL and Synthesis" focuses on the ultimate product of the design cycle: the implementation of a digital design. Many of the design techniques and considerations illustrated in the text are examples of actual real-world designs.

Unique features of the book include the following:

• VHDL code explained line by line to capture the logic behind the design concepts
• Simulation waveforms, synthesized schematics, and results are shown, verified, and analyzed
• VHDL code is synthesized and commands and strategies are discussed
• Variations on the design techniques and common mistakes are addressed
• Demonstrated standard cell, gate array, and FPGA three design processes, each with a complete design case study
• Test bench, post-layout verification, and test vector generation processes are illustrated

Lamb waves are guided waves that propagate in thin plate or shell structures. There has been a clear increase of interest in using Lamb waves for identifying structural damage, entailing intensive research and development in this field over the past two decades. Now on the verge of maturity for diverse engineering applications, this emerging technique serves as an encouraging candidate for facilitating continuous and automated surveillance of the integrity of engineering structures in a cost-effective manner. In comparison with conventional nondestructive evaluation techniques such as ultrasonic scanning and radiography which have been well developed over half a century, damage identification using Lamb waves is in a stage of burgeoning development, presenting a number of technical challenges in application that need to be addressed and circumvented. It is these two aspects that have encouraged us to write this book, with the intention of consolidating the knowledge and know-how in the field of Lamb-wave-based damage identification, and of promoting widespread attention to mature application of this technique in the practical engineering sphere. This book provides a comprehensive description of key facets of damage identification technique using Lamb waves, based on the authors' knowledge, comprehension and experience, ranging from fundamental theory through case studies to engineering applications.

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

This book introduces readers to all the necessary components and knowledge to start being a vital part of the IoT revolution. The author discusses how to create smart-IoT solutions to help solve a variety of real problems. Coverage includes the most important aspects of IoT architecture, the various applications of IoT, and the enabling technologies for IoT. This book presents key IoT concepts and abstractions, while showcasing real case studies. The discussion also includes an analysis of IoT strengths, weaknesses, opportunities and threats. Readers will benefit from the in-depth introduction to internet of things concepts, along with discussion of IoT algorithms and architectures tradeoffs. Case studies include smart homes, smart agriculture, and smart automotive.

By studying applications in radar, telecommunications and digital image restoration, this monograph discusses signal processing techniques based on bispectral methods. Improved robustness against different forms of noise as well as preservation of phase information render this method a valuable alternative to common power-spectrum analysis used in radar object recognition, digital wireless communications, and jitter removal in images.

The use of synthetic aperture radar (SAR) represents a new era in remote sensing technology. A complete handbook for anyone who must design an SAR system capable of reliably producing high quality image data products, free from image artifacts and calibrated in terms of the target backscatter coefficient. Combines fundamentals underlying the SAR imaging process and the practical system engineering required to produce quality images from a real SAR system. Beginning with a broad overview of SAR technology, it goes on to examine SAR system capabilities and components and detail the techniques required for design and development of the SAR ground data system with emphasis on the correlation processing. Intended for SAR system engineers and researchers, it is generously illustrated for maximum clarity.

The subject of Signals and Systems is enormously complex, involving many concepts such as signals, mathematics and filter design that are woven together in an intricate manner. To cope with this scope and complexity, many Signals and Systems texts are often organized around the "numerical examples" of a system. With such organization, students can see through the complexity of Signals and Systems, they can learn about the distinct concepts and protocols in one part of the communication system while seeing the big picture of how all parts fit together. From a pedagogical perspective, our personal experience has been that such approach indeed works well. Based on the Authors extensive experience of teaching and research, the book is written with such a reader in mind. The Book is intended for a course on signals & systems at the senior undergraduate level and above. The authors consider all the requirements and tools used in analysis and design of discrete time systems for filter design and signal processing. Key features of the International Edition: * The extensive use of MATLAB based examples to illustrate how to solve the signals & systems problems. The textbook includes a wealth of problems with solutions. * Worked-out examples have been included to explain new and difficult concepts and to expose the reader to real-life signal processing problems. The inclusion of FIR and IIR filter design further enriches the contents of the book.

This book treats the topic of extending the adaptive filtering theory in the context of massive multichannel systems by taking into account a priori knowledge of the underlying system or signal. The starting point is exploiting the sparseness in acoustic multichannel system in order to solve the non-uniqueness problem with an efficient algorithm for adaptive filtering that does not require any modification of the loudspeaker signals. The book discusses in detail the derivation of general sparse representations of acoustic MIMO systems in signal or system dependent transform domains. Efficient adaptive filtering algorithms in the transform domains are presented and the relation between the signal- and the system-based sparse representations is emphasized. Furthermore, the book presents a novel approach to spatially preprocess the loudspeaker signals in a full-duplex communication system. The idea of the preprocessing is to prevent the echoes from being captured by the microphone array in order to support the AEC system. The preprocessing stage is given as an exemplarily application of a novel unified framework for the synthesis of sound figures. Finally, a multichannel system for the acoustic echo suppression is presented that can be used as a postprocessing stage for removing residual echoes. As first of its kind, it extracts the near-end signal from the microphone signal with a distortionless constraint and without requiring a double-talk detector.

The vision of a world in which privacy persists and security is ensured but the full potential of the technology is nevertheless tapped guides this work. It is argued that security and privacy can be ensured using technical safeguards if the whole RFID system is designed properly. The challenge is immense since many constraints exist for providing security and privacy in RFID systems: technically and economically but also ethically and socially. Not only security and privacy needs to be provided but the solutions also need to be inexpensive, practical, reliable, scalable, flexible, inter-organizational, and lasting.

After analyzing the problem area in detail, this work introduces a number of new concepts and protocols that provide security and ensure privacy in RFID systems by technical means. The classic RFID model is extended and considerations in new directions are taken. This leads to innovative solutions with advantageous characteristics. Finally, a comprehensive framework including required protocols for operation is proposed. It can be used within a global scope, supports inter-organizational cooperation and data sharing, and adheres to all the architectural guidelines derived in this work. Security and privacy is provided by technical means in an economic manner. Altogether, the goal of building scalable and efficient RFID systems on a global, inter-organizational scale without neglecting security and privacy has been achieved well.

This book combines textual and graphical programming to form a hybrid programming approach, enabling a more effective means of building and analyzing DSP systems. The hybrid programming approach allows the use of previously developed textual programming solutions to be integrated into LabVIEW's highly interactive and visual environment, providing an easier and quicker method for building DSP systems. This book will be an ideal introduction for engineers and students seeking to develop DSP systems in quick time.
Features
- The only DSP laboratory book that combines textual and graphical programming
- 12 lab experiments that incorporate C/MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature
- Lab experiments covering basic DSP implementation topics including sampling, digital filtering, fixed-point data representation, frequency domain processing
- Interesting applications using the hybrid programming approach, such as a software-defined radio system, a 4-QAM Modem, and a cochlear implant simulator
- CD providing all the lab codes
Nasser Kehtarnavaz is Professor of Electrical Engineering at University of Texas at Dallas. He has written numerous papers and five other books pertaining to signal and image processing, and regularly teaches digital signal processing laboratory courses, for which this book is intended. Among his many professional activities, he is Coeditor-in-Chief of Journal of Real-Time Image Processing, and Chair of the Dallas Chapter of the IEEE Signal Processing Society. Dr. Kehtarnavaz is a Fellow of SPIE, a Senior Member of IEEE, and a Professional Engineer.
* The only DSP project book thatcombines textual and graphical programming
* 12 Lab projects that incorporate MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature.
* Interesting applications such as the design of a cochlear implant simulator and a software-defined radio system.

Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate- or graduate-level understanding of mathematics-including familiarity with Fourier series, matrices, probability, and statistics-this Second Edition: Contains new chapters on convolution and the vector DFT, plane-wave propagation, and the BLUE and Kalman filters Expands the material on Fourier analysis to three new chapters to provide additional background information Presents real-world examples of applications that demonstrate how mathematics is used in remote sensing Featuring problems for use in the classroom or practice, Signal Processing: A Mathematical Approach, Second Edition covers topics such as Fourier series and transforms in one and several variables; applications to acoustic and electro-magnetic propagation models, transmission and emission tomography, and image reconstruction; sampling and the limited data problem; matrix methods, singular value decomposition, and data compression; optimization techniques in signal and image reconstruction from projections; autocorrelations and power spectra; high-resolution methods; detection and optimal filtering; and eigenvector-based methods for array processing and statistical filtering, time-frequency analysis, and wavelets.

Comprehensively covers protein subcellular localization from single-label prediction to multi-label prediction, and includes prediction strategies for virus, plant, and eukaryote species. Three machine learning tools are introduced to improve classification refinement, feature extraction, and dimensionality reduction.

An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts. Part I deals with the mathematical preliminaries: numerical linear algebra; system theory; stochastic processes; and Kalman filtering. Part II explains realization theory as applied to subspace identification. Stochastic realization results based on spectral factorization and Riccati equations, and on canonical correlation analysis for stationary processes are included. Part III demonstrates the closed-loop application of subspace identification methods. Subspace Methods for System Identification is an excellent reference for researchers and a useful text for tutors and graduate students involved in control and signal processing courses. It can be used for self-study and will be of interest to applied scientists or engineers wishing to use advanced methods in modeling and identification of complex systems.

Continuous-Time Systems is a description of linear, nonlinear, time-invariant, and time-varying electronic continuous-time systems. As an assemblage of physical or mathematical components organized and interacting to convert an input signal (also called excitation signal or driving force) to an output signal (also called response signal), an electronic system can be described using different methods offered by the modern systems theory. To make possible for readers to understand systems, the book systematically covers major foundations of the systems theory.

Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications provides fundamental background knowledge of convex optimization, while striking a balance between mathematical theory and applications in signal processing and communications. In addition to comprehensive proofs and perspective interpretations for core convex optimization theory, this book also provides many insightful figures, remarks, illustrative examples, and guided journeys from theory to cutting-edge research explorations, for efficient and in-depth learning, especially for engineering students and professionals. With the powerful convex optimization theory and tools, this book provides you with a new degree of freedom and the capability of solving challenging real-world scientific and engineering problems.

This volume comprises eight well-versed contributed chapters devoted to report the latest findings on the intelligent approaches to multimedia data analysis. Multimedia data is a combination of different discrete and continuous content forms like text, audio, images, videos, animations and interactional data. At least a single continuous media in the transmitted information generates multimedia information. Due to these different types of varieties, multimedia data present varied degrees of uncertainties and imprecision, which cannot be easy to deal by the conventional computing paradigm. Soft computing technologies are quite efficient to handle the imprecision and uncertainty of the multimedia data and they are flexible enough to process the real-world information. Proper analysis of multimedia data finds wide applications in medical diagnosis, video surveillance, text annotation etc. This volume is intended to be used as a reference by undergraduate and post graduate students of the disciplines of computer science, electronics and telecommunication, information science and electrical engineering. THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research fi ndings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the fi eld and create a broad knowledge about the most recent state of the art.

This book presents selected papers from the Sixteenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, in conjunction with the Thirteenth International Conference on Frontiers of Information Technology, Applications and Tools, held on November 5-7, 2020, in Ho Chi Minh City, Vietnam. It is divided into two volumes and discusses the latest research outcomes in the field of Information Technology (IT) including information hiding, multimedia signal processing, big data, data mining, bioinformatics, database, industrial and Internet of things, and their applications.

This is the second volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This second book focuses on recent developments in response to the demands of new digital technologies. It is divided into two parts: the first part includes four chapters on the decomposition and recovery of signals, with special emphasis on images. In turn, the second part includes three chapters and addresses important data-based actions, such as adaptive filtering, experimental modeling, and classification.

This book proceedings collects a number of papers presented at the International Conference on Sensing and Imaging, which was held at Guangxi University of Science and Technology from October 15-18, 2018. Sensing and imaging is an interdisciplinary field covering a variety of sciences and techniques such as optics, electricity, magnetism, heat, sound, and computing technologies. The field has diverse applications of interest such as image processing techniques.The results in the book bridge the gap between theory and applications, translating techniques into better products. The text will appeal to students, professionals and researchers alike.

This book describes a unique approach to bring robotic technology into elders' daily lives. Low cost components and low cost robotic assistants are effectively combined to offer high quality services to elders and people in need. The book presents in a comprehensive way how technology can be used for developing a new healthcare paradigm where high quality services are offered at home, thus reducing the ever-increasing hospitalization cost of the elders and the people with chronic diseases.

This book covers emerging trends in signal processing research and biomedical engineering, exploring the ways in which signal processing plays a vital role in applications ranging from medical electronics to data mining of electronic medical records. Topics covered include statistical modeling of electroencephalograph data for predicting or detecting seizure, stroke, or Parkinson's; machine learning methods and their application to biomedical problems, which is often poorly understood, even within the scientific community; signal analysis; medical imaging; and machine learning, data mining, and classification. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers interested in applications of signal processing, medicine, and biology.

This textbook provides engineering students with instruction on processing signals encountered in speech, music, and wireless communications using software or hardware by employing basic mathematical methods. The book starts with an overview of signal processing, introducing readers to the field. It goes on to give instruction in converting continuous time signals into digital signals and discusses various methods to process the digital signals, such as filtering. The author uses MATLAB throughout as a user-friendly software tool to perform various digital signal processing algorithms and to simulate real-time systems. Readers learn how to convert analog signals into digital signals; how to process these signals using software or hardware; and how to write algorithms to perform useful operations on the acquired signals such as filtering, detecting digitally modulated signals, correcting channel distortions, etc. Students are also shown how to convert MATLAB codes into firmware codes. Further, students will be able to apply the basic digital signal processing techniques in their workplace. The book is based on the author's popular online course at University of California, San Diego.

This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book's last chapter focuses on modulation, an example of the intentional use of non-stationary signals.

Computers are the foundation of the information age, but communication technology is the foundation of the foundation. Without the theories and practical applications of theory brought to us by the pioneers of communication, the computer age would perhaps have remained in the back office, hidden away as infrastructure like electricity or running water - critical to modern life, but not as transforming as the combination of communications and computing. The information age exploded once machines were endowed with the ability to talk among themselves. The Signal connects everything to everything else, in both communication, and in the metaphorical sense as the link between and among people. Features Identifies the key ideas underlying modern communications technology, and documents the contributions of its inventors Explores the signal in communication, and also in the metaphorical sense as the link between and among people Leads the reader through a journey from ancient number systems to Voyager II to radio and MP3s to quantum cryptography Includes coverage of "Signals from Hell," including memes and "fake news" on the Internet Looks to the future of communication, with emergent 5G

Many new DCT-like transforms have been proposed since the first edition of this book. For example, the integer DCT that yields integer transform coefficients, the directional DCT to take advantage of several directions of the image and the steerable DCT. The advent of higher dimensional frames such as UHDTV and 4K-TV demand for small and large transform blocks to encode small or large similar areas respectively in an efficient way. Therefore, a new updated book on DCT, adapted to the modern days, considering the new advances in this area and targeted for students, researchers and the industry is a necessity.