This book presents essential algorithms for the image processing pipeline of photo-printers and accompanying software tools, offering an exposition of multiple image enhancement algorithms, smart aspect-ratio changing techniques for borderless printing and approaches for non-standard printing modes. All the techniques described are content-adaptive and operate in an automatic mode thanks to machine learning reasoning or ingenious heuristics. The first part includes algorithms, for example, red-eye correction and compression artefacts reduction, that can be applied in any photo processing application, while the second part focuses specifically on printing devices, e.g. eco-friendly and anaglyph printing. The majority of the techniques presented have a low computational complexity because they were initially designed for integration in system-on-chip. The book reflects the authors' practical experience in algorithm development for industrial R&D.

This book focuses on optical fiber sensing and structural health monitoring technologies. It provides detailed information on the basic theory of F-P optical fiber sensors, fiber Bragg grating sensors, fiber laser grating sensors and fully distributed optical fiber sensors. Drawing on the authors' research achievements and many years of practical experience in the field of engineering structure health monitoring, the book elaborates on the structural principle, design and manufacture of optical fiber sensors and monitoring technologies, and briefly describes advances made with regard to multiple engineering structures.

This thesis proposes machine learning methods for understanding scenes via behaviour analysis and online anomaly detection in video. The book introduces novel Bayesian topic models for detection of events that are different from typical activities and a novel framework for change point detection for identifying sudden behavioural changes. Behaviour analysis and anomaly detection are key components of intelligent vision systems. Anomaly detection can be considered from two perspectives: abnormal events can be defined as those that violate typical activities or as a sudden change in behaviour. Topic modelling and change-point detection methodologies, respectively, are employed to achieve these objectives. The thesis starts with the development of learning algorithms for a dynamic topic model, which extract topics that represent typical activities of a scene. These typical activities are used in a normality measure in anomaly detection decision-making. The book also proposes a novel anomaly localisation procedure. In the first topic model presented, a number of topics should be specified in advance. A novel dynamic nonparametric hierarchical Dirichlet process topic model is then developed where the number of topics is determined from data. Batch and online inference algorithms are developed. The latter part of the thesis considers behaviour analysis and anomaly detection within the change-point detection methodology. A novel general framework for change-point detection is introduced. Gaussian process time series data is considered. Statistical hypothesis tests are proposed for both offline and online data processing and multiple change point detection are proposed and theoretical properties of the tests are derived. The thesis is accompanied by open-source toolboxes that can be used by researchers and engineers.

This book chiefly addresses the analysis and design of geosynchronous synthetic aperture radar (GEO SAR) systems, focusing on the algorithms, analysis, methods used to compensate for ionospheric influences, and validation experiments for Global Navigation Satellite Systems (GNSS). Further, it investigates special problems in the GEO SAR context, such as curved trajectories, the Earth's rotation, the 'non-stop-and-go' model, high-order Doppler parameters, temporal-variant ionospheric errors etc. These studies can also be extended to SAR with very high resolution and long integration time. Given the breadth and depth of its coverage, scientists and engineers in SAR and advanced graduate students in related areas will greatly benefit from this book.

This book provides a comprehensive overview of how fractal analytics can lead to the extraction of interesting features from the complex electroencephalograph (EEG) signals generated by Hindustani classical music. It particularly focuses on how the brain responses to the emotional attributes of Hindustani classical music that have been long been a source of discussion for musicologists and psychologists. Using robust scientific techniques that are capable of looking into the most intricate dynamics of the complex EEG signals, it deciphers the human brain's response to different ragas of Hindustani classical music, shedding new light on what happens inside the performer's brain when they are mentally composing the imagery of a particular raga. It also explores the much- debated issue in the musical fraternity of whether there are any universal cues in music that make it identifiable for people throughout the world, and if so, what are the neural correlates associated with the universal cues? This book is of interest to researchers and scholars of music and the brain, nonlinear science, music cognition, music signal processing and music information retrieval. In addition, researchers in the field of nonlinear biomedical signal processing and music signal analysis benefit from this book.

This book comprises a collection of papers by international experts, presented at the International Conference on NextGen Electronic Technologies (ICNETS2-2017). ICNETS2 encompassed six symposia covering all aspects of electronics and communications engineering domains, including relevant nano/micro materials and devices. Featuring the latest research on computational signal processing and analysis, the book is useful to researchers, professionals, and students working in the core areas of electronics and their applications, especially signal processing, embedded systems, and networking.

The book includes extended versions of selected papers discussed and presented at the 5th International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2018) held in Kolkata, India on February 9-11, 2018. The symposium was organized by the University of Calcutta's Department of Computer Science & Engineering and A. K. Choudhury School of Information Technology, and the International partners were Ca Foscari University of Venice, Italy and Bialystok University of Technology, Poland. Reflect the symposium's sessions, the book discusses topics such as biometrics, image processing, pattern recognition, algorithms, cloud computing, wireless sensor networks and security systems.

The book presents theory and algorithms for secure networked inference in the presence of Byzantines. It derives fundamental limits of networked inference in the presence of Byzantine data and designs robust strategies to ensure reliable performance for several practical network architectures. In particular, it addresses inference (or learning) processes such as detection, estimation or classification, and parallel, hierarchical, and fully decentralized (peer-to-peer) system architectures. Furthermore, it discusses a number of new directions and heuristics to tackle the problem of design complexity in these practical network architectures for inference.

This book brings together work on Turkish natural language and speech processing over the last 25 years, covering numerous fundamental tasks ranging from morphological processing and language modeling, to full-fledged deep parsing and machine translation, as well as computational resources developed along the way to enable most of this work. Owing to its complex morphology and free constituent order, Turkish has proved to be a fascinating language for natural language and speech processing research and applications. After an overview of the aspects of Turkish that make it challenging for natural language and speech processing tasks, this book discusses in detail the main tasks and applications of Turkish natural language and speech processing. A compendium of the work on Turkish natural language and speech processing, it is a valuable reference for new researchers considering computational work on Turkish, as well as a one-stop resource for commercial and research institutions planning to develop applications for Turkish. It also serves as a blueprint for similar work on other Turkic languages such as Azeri, Turkmen and Uzbek.

This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis. The first section of the book covers single channel source separation based on non-negative matrix factorization (NMF). After an introduction to the technique, two further chapters describe separation of known sources using non-negative spectrogram factorization, and temporal NMF models. In section two, NMF methods are extended to multi-channel source separation. Section three introduces deep neural network (DNN) techniques, with chapters on multichannel and single channel separation, and a further chapter on DNN based mask estimation for monaural speech separation. In section four, sparse component analysis (SCA) is discussed, with chapters on source separation using audio directional statistics modelling, multi-microphone MMSE-based techniques and diffusion map methods. The book brings together leading researchers to provide tutorial-like and in-depth treatments on major audio source separation topics, with the objective of becoming the definitive source for a comprehensive, authoritative, and accessible treatment. This book is written for graduate students and researchers who are interested in audio source separation techniques based on NMF, DNN and SCA.

This unique text/reference presents a fresh look at nonlinear processing through nonlinear eigenvalue analysis, highlighting how one-homogeneous convex functionals can induce nonlinear operators that can be analyzed within an eigenvalue framework. The text opens with an introduction to the mathematical background, together with a summary of classical variational algorithms for vision. This is followed by a focus on the foundations and applications of the new multi-scale representation based on non-linear eigenproblems. The book then concludes with a discussion of new numerical techniques for finding nonlinear eigenfunctions, and promising research directions beyond the convex case. Topics and features: introduces the classical Fourier transform and its associated operator and energy, and asks how these concepts can be generalized in the nonlinear case; reviews the basic mathematical notion, briefly outlining the use of variational and flow-based methods to solve image-processing and computer vision algorithms; describes the properties of the total variation (TV) functional, and how the concept of nonlinear eigenfunctions relate to convex functionals; provides a spectral framework for one-homogeneous functionals, and applies this framework for denoising, texture processing and image fusion; proposes novel ways to solve the nonlinear eigenvalue problem using special flows that converge to eigenfunctions; examines graph-based and nonlocal methods, for which a TV eigenvalue analysis gives rise to strong segmentation, clustering and classification algorithms; presents an approach to generalizing the nonlinear spectral concept beyond the convex case, based on pixel decay analysis; discusses relations to other branches of image processing, such as wavelets and dictionary based methods. This original work offers fascinating new insights into established signal processing techniques, integrating deep mathematical concepts from a range of different fields, which will be of great interest to all researchers involved with image processing and computer vision applications, as well as computations for more general scientific problems.

This book provides a reference guide for researchers, scientists and industrialists working in the area of soft computing, and highlights the latest advances in and applications of soft computing techniques in multidisciplinary areas. Gathering papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2016), which was held in Jaipur, Rajasthan, India, on December 28-30, 2016, it focuses on applying soft computing to solve real-life problems arising in various domains, from medical and healthcare to supply chain management, image processing and cryptanalysis. The term soft computing represents an umbrella term for computational techniques like fuzzy logic, neural networks and nature inspired algorithms. In the past few decades, there has been an exponential rise in the application of soft computing techniques to address complex and intricate problems in diverse spheres of life. The versatility of these techniques has made them a favourite among scientists and researchers alike.

This book presents cutting-edge research on various ways to bridge the semantic gap in image and video analysis. The respective chapters address different stages of image processing, revealing that the first step is a future extraction, the second is a segmentation process, the third is object recognition, and the fourth and last involve the semantic interpretation of the image. The semantic gap is a challenging area of research, and describes the difference between low-level features extracted from the image and the high-level semantic meanings that people can derive from the image. The result greatly depends on lower level vision techniques, such as feature selection, segmentation, object recognition, and so on. The use of deep models has freed humans from manually selecting and extracting the set of features. Deep learning does this automatically, developing more abstract features at the successive levels. The book offers a valuable resource for researchers, practitioners, students and professors in Computer Engineering, Computer Science and related fields whose work involves images, video analysis, image interpretation and so on.

The book presents innovative scientific research works by academics, research scholars and students, presented at the 2017 International Conference on Energy, Materials and Information Technology at Amity University Jharkhand, India. It includes contributions on system solutions based on soft computing techniques, and covers innovative soft computing techniques and tools with advanced applications. A major focus of the book is on presenting interdisciplinary problems and how they can be solved using information technology, together with innovative connections to other disciplines. It also includes papers on cloud computing and WSN-related real-time research.

This two-volume book presents outcomes of the 7th International Conference on Soft Computing for Problem Solving, SocProS 2017. This conference is a joint technical collaboration between the Soft Computing Research Society, Liverpool Hope University (UK), the Indian Institute of Technology Roorkee, the South Asian University New Delhi and the National Institute of Technology Silchar, and brings together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to select potential future directions The book presents the latest advances and innovations in the interdisciplinary areas of soft computing, including original research papers in the areas including, but not limited to, algorithms (artificial immune systems, artificial neural networks, genetic algorithms, genetic programming, and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). It is a valuable resource for both young and experienced researchers dealing with complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.

Atrial Fibrillation from an Engineering Perspective provides an up-to-date overview of techniques developed for acquisition, modeling, and analysis of noninvasive, bioelectrical signals reflecting this common arrhythmia. Special emphasis is put on emerging technologies for monitoring of atrial fibrillation in connection with ischemic stroke, interventional ablation procedures, and pharmacological treatment, applications which all depend on the availability of techniques for detecting and characterizing episodes of paroxysmal atrial fibrillation. Detectors exploring both rhythm and morphology are described, as well as detectors confined to rhythm and better suited for low power implementation. A wide variety of approaches to modeling and characterization of atrial activity are described, emanating from a statistical and deterministic starting points. This book is suitable for graduate students, researchers, and engineers who want a comprehensive treatise of atrial fibrillation from an engineering perspective. It may be used for self-study, as a supplement to courses in signal processing, or as a modern monograph by researchers in the field of atrial fibrillation.

This book describes the latest advances in pulse signal analysis and their applications in classification and diagnosis. First, it provides a comprehensive introduction to useful techniques for pulse signal acquisition based on different kinds of pulse sensors together with the optimized acquisition scheme. It then presents a number of preprocessing and feature extraction methods, as well as case studies of the classification methods used. Lastly it discusses some promising directions for the future study and clinical applications of pulse signal analysis. The book is a valuable resource for researchers, professionals and postgraduate students working in the field of pulse diagnosis, signal processing, pattern recognition and biometrics. It is also useful for those involved in interdisciplinary research.

Comprehensive in scope, this book covers the latest progresses of theories, technologies and applications of LEDs based on III-V semiconductor materials, such as basic material physics, key device issues (homoepitaxy and heteroepitaxy of the materials on different substrates, quantum efficiency and novel structures, and more), packaging, and system integration. The authors describe the latest developments of LEDs with spectra coverage from ultra-violet (UV) to the entire visible light wavelength. The major aspects of LEDs, such as material growth, chip structure, packaging, and reliability are covered, as well as emerging and novel applications beyond the general and conventional lightings. This book, written by leading authorities in the field, is indispensable reading for researchers and students working with semiconductors, optoelectronics, and optics. Addresses novel LED applications such as LEDs for healthcare and wellbeing, horticulture, and animal breeding; Editor and chapter authors are global leading experts from the scientific and industry communities, and their latest research findings and achievements are included; Foreword by Hiroshi Amano, one of the 2014 winners of the Nobel Prize in Physics for his work on light-emitting diodes.

Artificial Intelligence (AI) is penetrating in all sciences as a multidisciplinary approach. However, adopting the theory of AI including computer vision and computer audition to urban intellectual space, is always difficult for architecture and urban planners. This book overcomes this challenge through a conceptual framework by merging computer vision and audition to urban studies based on a series of workshops called Remorph, conducted by Tehran Urban Innovation Center (TUIC).

The book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Information System Design and Intelligent Applications (INDIA 2018), which was held at the Universite des Mascareignes, Mauritius from July 19 to 21, 2018. It covers a wide range of topics in computer science and information technology, from image processing, database applications and data mining, to grid and cloud computing, bioinformatics and many more. The intelligent tools discussed, e.g. swarm intelligence, artificial intelligence, evolutionary algorithms, and bio-inspired algorithms, are currently being applied to solve challenging problems in various domains.

This book is a collection of tutorial-like chapters on all core topics of signals and systems and the electronic circuits. All the topics dealt with in the book are parts of the core syllabi of standard programs in Electrical Engineering, Electrical and Computer Engineering, and Electronics and Telecommunication Engineering domains. This book is intended to serve as a secondary reader or supplementary text for core courses in the area of signals and systems, electronic circuits, and analog and digital signal processing. When studying or teaching a particular topic, the students and instructors of such courses would find it interesting and worthwhile to study the related tutorial chapter in this book in order to enhance their understanding of the fundamentals, simplification of procedures, alternative approaches and relation to other associated topics. In addition, the book can also be used as a primary or secondary text in short-term or refresher courses, and as a self-study guide for professionals wishing to gain a comprehensive review of the signals and systems domain.

This book presents state-of-the-art techniques for radiation hardened high-resolution Time-to-Digital converters and low noise frequency synthesizers. Throughout the book, advanced degradation mechanisms and error sources are discussed and several ways to prevent such errors are presented. An overview of the prerequisite physics of nuclear interactions is given that has been compiled in an easy to understand chapter. The book is structured in a way that different hardening techniques and solutions are supported by theory and experimental data with their various tradeoffs. Based on leading-edge research, conducted in collaboration between KU Leuven and CERN, the European Center for Nuclear Research Describes in detail advanced techniques to harden circuits against ionizing radiation Provides a practical way to learn and understand radiation effects in time-based circuits Includes an introduction to the underlying physics, circuit design, and advanced techniques accompanied with experimental data

This book deals with the topic of biomechanical biofeedback systems and applications that are primarily aimed at motor learning in sports and rehabilitation. It gives a comprehensive tutorial of the concepts, architectures, operation, and exemplary applications of biomechanical biofeedback systems. A special section is dedicated to various constraints in designing biomechanical biofeedback systems. The book also describes the technologies needed for the adequate operation of biofeedback systems, such as motion tracking, communication, processing, and sensor technologies. In regard to technologies, the emphasis is on the assurance of the requirements of the real-time system operation. The application focus is on the usage in sport and rehabilitation, particularly in the field of accelerated motor learning and injury prevention. We include several examples of operational (real-time) biofeedback applications in golf, skiing, and swimming. The book is in the first place intended for the professional audience, researchers, and scientists in the fields connected to the topics of this book.

This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing.

The book is a compilation of best papers presented at International Conference on Recent Advancement in Computer and Communication (ICRAC 2017) organized by IMPLab Research and Innovation Foundation, Bhopal, India. The book covers all aspects of computers and communication techniques including pervasive computing, distributed computing, cloud computing, sensor and adhoc network, image, text and speech processing, pattern recognition and pattern analysis, digital signal processing, digital electronics, telecommunication technologies, robotics, VLSI technologies, embedded system, satellite communication, digital signal processing, and digital communication. The papers included are original research works of experts from industry, government centers and academic institutions; experienced in engineering, design and research.