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.

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.

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.

"Multiscale Signal Analysis and Modeling" presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory.

Identification of Time-Varying Processes offers a comprehensive treatment of the key issue in adaptive systems: tracking of time-varying system parameters. Time-varying identification techniques facilitate many challenging applications in different areas including telecommunications (channel equalization, predictive coding of signals, adaptive noise reduction and echo cancellation) and automatic control (adaptive control and failure detection). The processes also assist signal processing in areas such as adaptive noise reduction, prediction of time series, restoration of archive audio recordings and spectrum estimation. Includes:
* All three major approaches to time-varying identification: local estimation, the basis functions approach and the method based on Kalman filtering/smoothing.
* Analysis and comparison of tracking capabilities of different time-varying identification schemes.
* Discussion of all aspects of time-varying identification such as assessment of the estimation memory, estimation bandwidth and numerical stability of different identification algorithms and optimization of adaptive filters.
* Presentation of selected practical applications of time-varying process identification.
Essential reading for adaptive signal processing engineers, researchers, lecturers and senior electrical engineering and computer science students in telecommunications and signal processing.

Provides technical and scientific descriptions of potential approaches used to achieve indoor positioning, ranging from sensor networks to more advanced radio-based systems This book presents a large technical overview of various approaches to achieve indoor positioning. These approaches cover those based on sensors, cameras, satellites, and other radio-based methods. The book also discusses the simplification of certain implementations, describing ways for the reader to design solutions that respect specifications and follow established techniques. Descriptions of the main techniques used for positioning, including angle measurement, distance measurements, Doppler measurements, and inertial measurements are also given. Indoor Positioning: Technologies and Performance starts with overviews of the first age of navigation, the link between time and space, the radio age, the first terrestrial positioning systems, and the era of artificial satellites. It then introduces readers to the subject of indoor positioning, as well as positioning techniques and their associated difficulties. Proximity technologies like bar codes, image recognition, Near Field Communication (NFC), and QR codes are covered--as are room restricted and building range technologies. The book examines wide area indoor positioning as well as world wide indoor technologies like High-Sensitivity and Assisted GNSS, and covers maps and mapping. It closes with the author's vision of the future in which the practice of indoor positioning is perfected across all technologies. This text: Explores aspects of indoor positioning from both theoretical and practical points of view Describes advantages and drawbacks of various approaches to positioning Provides examples of design solutions that respect specifications of tested techniques Covers infra-red sensors, lasers, Lidar, RFID, UWB, Bluetooth, Image SLAM, LiFi, WiFi, indoor GNSS, and more Indoor Positioning is an ideal guide for technical engineers, industrial and application developers, and students studying wireless communications and signal processing.

Analysis, design, and realization of digital filters have experienced major developments since the 1970s, and have now become an integral part of the theory and practice in the field of contemporary digital signal processing. Digital Filter Design and Realization is written to present an up-to-date and comprehensive account of the analysis, design, and realization of digital filters. It is intended to be used as a text for graduate students as well as a reference book for practitioners in the field. Prerequisites for this book include basic knowledge of calculus, linear algebra, signal analysis, and linear system theory. Technical topics discussed in the book include: Discrete-Time Systems and z-Transformation Stability and Coefficient Sensitivity State-Space Models FIR Digital Filter Design Frequency-Domain Digital Filter Design Time-Domain Digital Filter Design Interpolated and Frequency-Response-Masking FIR Digital Filter Design Composite Digital Filter Design Finite Word Length Effects Coefficient Sensitivity Analysis and Minimization Error Spectrum Shaping Roundoff Noise Analysis and Minimization Generalized Transposed Direct-Form II Block-State Realization

There is an increasing tendency to integrate optical communication with wireless communication to satisfy continuously emerging (new) data communication demands. Thus, optical-wireless-integrated access networks and transmission systems, as well as LED-based visible light communication are attracting ever increasing research interest. Digital signal processing (DSP) is one new technology for optical transmission. As such this book is designed to pave the way to the better understanding of the deployment of DSP in optical fiber communication systems.Digital Signal Processing for High-Speed Optical Communication covers a wide area of DSP topics in optical communications, and describes state-of-the-art digital signal processing techniques for high-speed optical communication. In this book, numerous advanced digital signal processing techniques aiming at the promotion of the capacity increase and performance improvement of optical or optical-wireless communication systems and networks are presented and explained. Coverage includes new technologies, optical filter with MLSE, and new pre-coding and pre-equalization applicable to single-carrier and multi-carrier, direct-detection and coherent-detection optical commutation systems and networks.

Compressed Sensing in Li-Fi and Wi-Fi Networks features coverage of the first applications in optical telecommunications and wireless. After extensive development of basic theory, many techniques are presented, such as non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and the use of graphical models. The book can be used as a comprehensive manual for teaching and research in courses covering advanced signal processing, efficient data processing algorithms, and telecommunications. After a thorough review of the basic theory of compressed sensing, many mathematical techniques are presented, including advanced signal modeling, Nyquist sub-sampling of analog signals, the non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and the use of graphical models.

This textbook gives a fresh approach to an introductory course in signal processing. Its unique feature is to alternate chapters on continuous-time (analog) and discrete-time (digital) signal processing concepts in a parallel and synchronized manner. This presentation style helps readers to realize and understand the close relationships between continuous and discrete time signal processing, and lays a solid foundation for the study of practical applications such as the analysis and design of analog and digital filters.The compendium provides motivation and necessary mathematical rigor. It generalizes the Fourier transform to Laplace and Z transforms, applies these transforms to linear system analysis, covers the time and frequency-domain analysis of differential and difference equations, and presents practical applications of these techniques to convince readers of their usefulness. MATLAB (R) examples are provided throughout, and over 100 pages of solved homework problems are included in the appendix.

With the constant increase in applications involving image processing and multimedia procedures digital signal processing (DSP) is important for modern information engineering. One- and Multidimensional Signal Processing provides an introduction to the algorithmic basics of image and TV communication systems as well as for systems in automation and robotic applications using sensor based imaging techniques. This novel combination of both one- and multidimensional signal processing discusses the similarities between the two and aids the understanding of one theory over the other.
* Presents an applications-oriented approach to image processing including TV signal processing and discusses image scanning and the use of DSP procedures or digital filters
* Provides clear and comprehensive coverage of basic concepts such as spatial frequency, spatio-temporal signal processing and the spectral representation of motion and tracking of moving objects
* Features examples of applications including image pick-up and display as well as still image filtering and image sequence interpolation
* Introduces new design strategies for finite-impulse response (FIR) filters for image processing applciations using spatial and frequency design constraints
* Includes an introduction to nonlinear image processing techniques applying edge detection operators, morphological operators and rank order filters
Such a practical book will have wide-ranging appeal as a valuable resource for researchers and developers and as an ideal introductory text for senior undergraduate and postgraduate students.

1 Introduction.- 2 Continuous-Time Quadratic Guaranteed Cost Filtering.- 3 Discrete-Time Quadratic Guaranteed Cost Filtering.- 4 Continuous-Time Set-Valued State Estimation and Model Validation.- 5 Discrete-Time Set-Valued State Estimation.- 6 Robust State Estimation with Discrete and Continuous Measurements.- 7 Set-Valued State Estimation with Structured Uncertainty.- 8 Robust H? Filtering with Structured Uncertainty.- 9 Robust Fixed Order H? Filtering.- 10 Set-Valued State Estimation for Nonlinear Uncertain Systems.- 11 Robust Filtering Applied to Induction Motor Control.- References.

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random processes and signal modelling are discussed with basic communication theory estimation and detection. MATLAB simulations are included for each concept with output of the program with case studies and project ideas. The chapters progressively introduce and explain the concepts of random signals and cover multiple applications for signal processing. The book is designed to cater to a wide audience starting from the undergraduates (electronics, electrical, instrumentation, computer, and telecommunication engineering) to the researchers working in the pertinent fields. Key Features: * Aimed at random signal processing with parametric signal processing-using appropriate segment size. * Covers speech, image, medical images, EEG and ECG signal processing. * Reviews optimal detection and estimation. * Discusses parametric modeling and signal processing in transform domain. * Includes MATLAB codes and relevant exercises, case studies and solved examples including multiple choice questions

The considerable growth of RFID is currently accompanied by the development of numerous identification technologies that complement those already available while seeking to answer new problems. Chipless RFID is one example. The goal is to both significantly reduce the price of the tag and increase the amount of information it contains, in order to compete with the barcode while retaining the benefits of a flexible reading approach based on radio communication. To solve the problem of the number of bits, this book describes the possibility of coding the information at the level of the overall shape of the RCS of the tag, which would facilitate reaching very large quantities. The design of the tags then returns to the resolution of the inverse problem of the electromagnetic signature. The proposed design methodology regularizes the problem by decomposing the signature on a basis of elementary patterns whose signature is chosen in advance.