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Books > Computing & IT > Applications of computing > Signal processing
This book includes selected peer-reviewed papers presented at the International Conference on Computing and Communication Networks (ICCCN 2021), held at Manchester Metropolitan University, United Kingdom, during 19-20 November 2021. The book covers topics of network and computing technologies, artificial intelligence and machine learning, security and privacy, communication systems, cyber physical systems, data analytics, cyber security for Industry 4.0, and smart and sustainable environmental systems.
The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal processing techniques that can be imagined. To support this claim, an overview of classical kernel machine learning approaches is presented, and their advantages and limitations are explained. Following a detailed explanation of the basic building blocks of deep neural networks from a biological and algorithmic point of view, the latest tools such as attention, normalization, Transformer, BERT, GPT-3, and others are described. Here, too, the focus is on the fact that in these heuristic approaches, there is an important, beautiful geometric structure behind the intuition that enables a systematic understanding. A unified geometric analysis to understand the working mechanism of deep learning from high-dimensional geometry is offered. Then, different forms of generative models like GAN, VAE, normalizing flows, optimal transport, and so on are described from a unified geometric perspective, showing that they actually come from statistical distance-minimization problems. Because this book contains up-to-date information from both a practical and theoretical point of view, it can be used as an advanced deep learning textbook in universities or as a reference source for researchers interested in acquiring the latest deep learning algorithms and their underlying principles. In addition, the book has been prepared for a codeshare course for both engineering and mathematics students, thus much of the content is interdisciplinary and will appeal to students from both disciplines.
This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. It mainly focuses on visual exploration of these data by a human analyst, relying on a 2D or 3D scatter plot display obtained through Dimensionality Reduction. Performing diagnosis of an energy system requires identifying relations between observed monitoring variables and the associated internal state of the system. Dimensionality reduction, which allows to represent visually a multidimensional dataset, constitutes a promising tool to help domain experts to analyse these relations. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field. In particular, it presents the new unsupervised technique ASKI and the supervised methods ClassNeRV and ClassJSE. Moreover, MING, a new approach for local map quality evaluation is also introduced. These methods are then applied to the representation of expert-designed fault indicators for smart-buildings, I-V curves for photovoltaic systems and acoustic signals for Li-ion batteries.
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 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.
"An excellent introductory book" (Review of the First Edition in the International Journal of Electrical Engineering Education) "…it will serve as a reference book in this area for a long time" (Review of Revised Edition in Zentralblatt für Mathematik (Germany)) Firmly established over the last decade as the essential introductory Digital Signal Processing (DSP) text, this second edition reflects the growing importance of random digital signals and random DSP in the undergraduate syllabus by including two new chapters. The authors’ practical, problem-solving approach to DSP continues in this new material, which is packed up by additional worked examples and computer programs. The book now features:
This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural networks (ANN). It explores an innovative approach to automatic circuit sizing where ANNs learn patterns from previously optimized design solutions. In opposition to classical optimization-based sizing strategies, where computational intelligence techniques are used to iterate over the map from devices' sizes to circuits' performances provided by design equations or circuit simulations, ANNs are shown to be capable of solving analog IC sizing as a direct map from specifications to the devices' sizes. Two separate ANN architectures are proposed: a Regression-only model and a Classification and Regression model. The goal of the Regression-only model is to learn design patterns from the studied circuits, using circuit's performances as input features and devices' sizes as target outputs. This model can size a circuit given its specifications for a single topology. The Classification and Regression model has the same capabilities of the previous model, but it can also select the most appropriate circuit topology and its respective sizing given the target specification. The proposed methodology was implemented and tested on two analog circuit topologies.
This book is a collection of high-quality peer reviewed contributions from the academicians, researchers, practitioners, and industry professionals, accepted in the International Conference on Advances in Data Computing, Communication and Security (I3CS2021) organized by the Department of Electronics and Communication Engineering in collaboration with the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India during 08-10 Sep 2021. The fast pace of advancing technologies and growing expectations of the next-generation requires that the researchers must continuously reinvent themselves through new investigations and development of the new products. The theme of this conference is devised as "Embracing Innovations" for the next-generation data computing and secure communication system.
This book is a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2020), held at Technical University of Sofia, Sofia, Bulgaria, during 09-11 July 2020. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge data mining, watermarking, hiding and encryption of MD images, MD image processing in robot systems, tensor-based data processing, 3D and multi-view visualization, forensic analysis systems for MD images and many more.
The book presents high-quality papers from the Fourth International Conference on Microelectronics and Telecommunication Engineering (ICMETE 2021). It discusses the latest technological trends and advances in major research areas such as microelectronics, wireless communications, optical communication, signal processing, image processing, big data, cloud computing, artificial intelligence and sensor network applications. This book includes the contributions of national and international scientists, researchers, and engineers from both academia and the industry. The contents of this volume will be useful to researchers, professionals, and students alike.
This book collects selected papers from the 7th Conference on Signal and Information Processing, Networking and Computers held in Rizhao, China, on September 21-23, 2020. The 7th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) was held in Rizhao, China, on September 21-23, 2020.
This book gathers the proceedings of the 7th International Conference on Advancements of Medicine and Health Care through Technology, held virtually on 13 - 15 October 2020, from Cluj-Napoca, Romania. It reports on both theoretical and practical developments fostering the use of cutting-edge technology in clinical settings, telemedicine, and biological research. Chapters mainly deal with medical devices, measurements and instrumentation, medical imaging and biological signal processing and health care information systems. Further topics include modeling, simulation and biomechanics, as well as innovative (bio-)materials for biomedical applications. The conference, as well as the realization of this book, was supported by the Romanian Society for Medical Engineering and Biological Technology.
This book constitutes the proceedings of the 8th International Conference on Future Data and Security Engineering, FDSE 2021, which was supposed to be held in Ho Chi Minh City, Vietnam, in November 2021, but the conference was held virtually due to the COVID-19 pandemic. The 24 full papers presented together with 2 invited keynotes were carefully reviewed and selected from 168 submissions. The selected papers are organized into the following topical headings: Big Data Analytics and Distributed Systems; Advances in Machine Learning for Big Data Analytics; Industry 4.0 and Smart City: Data Analytics and Security; Blockchain and IoT Applications; Machine Learning and Artificial Intelligence for Security and Privacy; Emerging Data Management Systems and Applications.
This book makes application to the dynamics of arousal and distraction, and to other examples. A modified version of the Kadanoff picture of phase transitions in consciousness emerges from the Morse Function itself in a surprisingly standard manner, closely associated with the breaking of groupoid symmetries driven by fundamental equivalence class algebras. Although this is far indeed from the familiar world of physical theory, it should be possible, on the basis of the probability models developed in the book, to develop new statistical tools for the analysis of observational and empirical data regarding cognition and consciousness.
This book provides an interdisciplinary look at emerging trends in signal processing and biomedicine found at the intersection of healthcare, engineering, and computer science. It examines the vital role signal processing plays in enabling a new generation of technology based on big data, and looks at applications ranging from medical electronics to data mining of electronic medical records. Topics covered include analysis of medical images, machine learning, biomedical nanosensors, wireless technologies, and instrumentation and electrical stimulation. Biomedical Signal Processing: Innovation and Applications presents tutorials and examples of successful applications, and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology.
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. FEATURES Explains how applications of DSP can be implemented in certain programming environments designed for real time systems, ex. biomedical signal analysis and medical image processing. Pairs theory with basic concepts and supporting analytical tables. Includes an extensive collection of solved problems throughout the text. Fosters the ability to solve practical problems on signal processing without focusing on extended theory. Covers the modeling process and addresses broader fundamental issues.
This book features selected papers from the International Conference on Soft Computing for Security Applications (ICSCS 2021), held at Dhirajlal Gandhi College of Technology, Tamil Nadu, India, during June 2021. It covers recent advances in the field of soft computing techniques such as fuzzy logic, neural network, support vector machines, evolutionary computation, machine learning and probabilistic reasoning to solve various real-time challenges. The book presents innovative work by leading academics, researchers, and experts from industry.
The many intriguing examples on the application of mechatronics reinforce the excitement of this creative field of technology. As a collection they present a stimulating resource to developers of future mechatronics technology, and to educators searching for interesting examples. From structured-light measurement of the build-up of detritus on railway bogies and detection of uncracked spores of Chinese medicine to a practical tractor vision guidance system embedded in a smart-phone application, the practical applications of mechatronics and machine vision abound. Fruits are counted on the tree, pasture biomass is measured and a robot collects camel dung as a resource. 3D printing is in vogue, but papers here discuss the construction and strategy of the printer itself. The measurement and analysis of myoelectric muscle signals enable a prosthesis to be controlled and a feeding robot is used for patient care. An exoskeleton has both soft and rigid links and an optical sensor analyses the tissue into which a surgical needle is being inserted. These are some of the papers in this collection from the 26th annual conference on Mechatronics and Machine Vision in Practice, carefully selected to exclude papers that are merely theoretical and to highlight those that show practical verification. Papers have been contributed from China, New Zealand, the Philippines, Emirates, Germany and of course Australia.
While voice is widely used in speech recognition and speaker identification, its application in biomedical fields is much less common. This book systematically introduces the authors' research on voice analysis for biomedical applications, particularly pathological voice analysis. Firstly, it reviews the field to highlight the biomedical value of voice. It then offers a comprehensive overview of the workflow and aspects of pathological voice analysis, including voice acquisition systems, voice pitch estimation methods, glottal closure instant detection, feature extraction and learning, and the multi-audio fusion approaches. Lastly, it discusses the experimental results that have shown the superiority of these techniques. This book is useful to researchers, professionals and postgraduate students working in fields such as speech signal processing, pattern recognition, and biomedical engineering. It is also a valuable resource for those involved in interdisciplinary research.
This book provides an in-depth coverage of the most recent developments in the field of wireless underground communications, from both theoretical and practical perspectives. The authors identify technical challenges and discuss recent results related to improvements in wireless underground communications and soil sensing in Internet of Underground Things (IOUT). The book covers both existing network technologies and those currently in development in three major areas of SitS: wireless underground communications, subsurface sensing, and antennas in the soil medium. The authors explore novel applications of Internet of Underground Things in digital agriculture and autonomous irrigation management domains. The book is relevant to wireless researchers, academics, students, and decision agriculture professionals. The contents of the book are arranged in a comprehensive and easily accessible format. Focuses on fundamental issues of wireless underground communication and subsurface sensing; Includes advanced treatment of IOUT custom applications of variable-rate technologies in the field of decision agriculture, and covers protocol design and wireless underground channel modeling; Provides a detailed set of path loss, antenna, and wireless underground channel measurements in various novel Signals in the Soil (SitS) testbed settings.
This book discusses non-conventional digital signal processing based on direct processing of delta-sigma modulated bit-stream. The main attributes of low-pass delta-sigma analog-to-digital converters are: simple and inexpensive design, robustness of design to component tolerances, low-power consumption, high input impedance, high resolution (more than 20 bits) and possibility of direct arithmetic operation on its bit-stream. The author presents a number of theoretical and simulation results related to newly proposed linear and non-linear circuits such as delta-sigma adders, delta-sigma rectifiers, delta-sigma RMS and AGC circuits, delta-sigma frequency deviation meters, etc. The proposed circuits are not application limited and can be used in instrumentation, sensor application, bio-medical application, communications, etc. Presents novel linear and nonlinear circuits for direct processing of delta-sigma modulated bit-stream; The proposed circuits are supported by theoretical and simulation results; Recommends potential applications of the proposed circuits, and proposes ideas for further investigation.
This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means. Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader's area of interest, or read together to provide a comprehensive overview of the topic. Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autonomous vehicles, wireless technology, and historical conservation.
This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Third International Conference on Soft Computing and Signal Processing (ICSCSP 2020). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.
This book takes a deep dive into ubiquitous computing for applications in health, business, education, tourism, and transportation. The rich interdisciplinary contents of the book appeal to readers from diverse disciplines who aspire to create new and innovative research initiatives and applications in ubiquitous computing. Topics include condition monitoring and diagnostics; multi-objective optimization in design, multi-objective optimization of machining parameters, and more. The book benefits researchers, advanced students, as well as practitioners interested in applications of ubiquitous computing. Features practical, tested applications in ubiquitous computing Includes applications such as health, business, education, electronics, tourism, and transportation Applicable to researchers, academics, students, and professionals
This book presents the selected peer-reviewed papers from the International Conference on Communication Systems and Networks (ComNet) 2019. Highlighting the latest findings, ideas, developments and applications in all areas of advanced communication systems and networking, it covers a variety of topics, including next-generation wireless technologies such as 5G, new hardware platforms, antenna design, applications of artificial intelligence (AI), signal processing and optimization techniques. Given its scope, this book can be useful for beginners, researchers and professionals working in wireless communication and networks, and other allied fields. |
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