Machine Learning Techniques For Automatic Modulation Classification

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Automatic Modulation Classification

Author : Zhechen Zhu
Publisher : John Wiley & Sons
ISBN 13 : 1118906519
Total Pages : 204 pages
Book Rating : 4.1/5 (189 download)

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Book Synopsis Automatic Modulation Classification by : Zhechen Zhu

Download or read book Automatic Modulation Classification written by Zhechen Zhu and published by John Wiley & Sons. This book was released on 2014-12-15 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic Modulation Classification (AMC) has been a key technology in many military, security, and civilian telecommunication applications for decades. In military and security applications, modulation often serves as another level of encryption; in modern civilian applications, multiple modulation types can be employed by a signal transmitter to control the data rate and link reliability. This book offers comprehensive documentation of AMC models, algorithms and implementations for successful modulation recognition. It provides an invaluable theoretical and numerical comparison of AMC algorithms, as well as guidance on state-of-the-art classification designs with specific military and civilian applications in mind. Key Features: Provides an important collection of AMC algorithms in five major categories, from likelihood-based classifiers and distribution-test-based classifiers to feature-based classifiers, machine learning assisted classifiers and blind modulation classifiers Lists detailed implementation for each algorithm based on a unified theoretical background and a comprehensive theoretical and numerical performance comparison Gives clear guidance for the design of specific automatic modulation classifiers for different practical applications in both civilian and military communication systems Includes a MATLAB toolbox on a companion website offering the implementation of a selection of methods discussed in the book

Automatic Modulation Recognition of Communication Signals

Author : Elsayed Azzouz
Publisher : Springer Science & Business Media
ISBN 13 : 9780792397960
Total Pages : 242 pages
Book Rating : 4.3/5 (979 download)

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Book Synopsis Automatic Modulation Recognition of Communication Signals by : Elsayed Azzouz

Download or read book Automatic Modulation Recognition of Communication Signals written by Elsayed Azzouz and published by Springer Science & Business Media. This book was released on 1996-11-30 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a critical review of automatic modulation recognition. This includes techniques for recognising digitally modulated signals. The book also gives comprehensive treatment of using artificial neural networks for recognising modulation types. Automatic Modulation Recognition of Communications Signals is the first comprehensive book on automatic modulation recognition. It is essential reading for researchers and practising engineers in the field. It is also a valuable text for an advanced course on the subject.

2021 55th Annual Conference on Information Sciences and Systems (CISS)

Author : IEEE Staff
Publisher :
ISBN 13 : 9781665448444
Total Pages : pages
Book Rating : 4.4/5 (484 download)

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Book Synopsis 2021 55th Annual Conference on Information Sciences and Systems (CISS) by : IEEE Staff

Download or read book 2021 55th Annual Conference on Information Sciences and Systems (CISS) written by IEEE Staff and published by . This book was released on 2021-03-24 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of the conference is broad Research in a wide variety of disciplines relating to the use and science of information is of interest

Machine Learning for Future Wireless Communications

Author : Fa-Long Luo
Publisher : John Wiley & Sons
ISBN 13 : 1119562252
Total Pages : 490 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Machine Learning for Future Wireless Communications by : Fa-Long Luo

Download or read book Machine Learning for Future Wireless Communications written by Fa-Long Luo and published by John Wiley & Sons. This book was released on 2020-02-10 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Mobile Multimedia Communications

Author : Jinbo Xiong
Publisher : Springer Nature
ISBN 13 : 3030898148
Total Pages : 899 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Mobile Multimedia Communications by : Jinbo Xiong

Download or read book Mobile Multimedia Communications written by Jinbo Xiong and published by Springer Nature. This book was released on 2021-11-02 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 14th International Conference on Mobile Multimedia Communications, Mobimedia 2021, held in July 2021. Due to COVID-19 pandemic the conference was held virtually. The 66 revised full papers presented were carefully selected from 166 submissions. The papers are organized in topical sections as follows: Internet of Things and Wireless Communications Communication; Strategy Optimization and Task Scheduling Oral Presentations; Privacy Computing Technology; Cyberspace Security and Access control; Neural Networks and Feature Learning Task Classification and Prediction; Object Recognition and Detection.

Automatic Modulation Classification

Author : Zhechen Zhu
Publisher : John Wiley & Sons
ISBN 13 : 1118906497
Total Pages : 204 pages
Book Rating : 4.1/5 (189 download)

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Book Synopsis Automatic Modulation Classification by : Zhechen Zhu

Download or read book Automatic Modulation Classification written by Zhechen Zhu and published by John Wiley & Sons. This book was released on 2015-02-16 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic Modulation Classification (AMC) has been a key technology in many military, security, and civilian telecommunication applications for decades. In military and security applications, modulation often serves as another level of encryption; in modern civilian applications, multiple modulation types can be employed by a signal transmitter to control the data rate and link reliability. This book offers comprehensive documentation of AMC models, algorithms and implementations for successful modulation recognition. It provides an invaluable theoretical and numerical comparison of AMC algorithms, as well as guidance on state-of-the-art classification designs with specific military and civilian applications in mind. Key Features: Provides an important collection of AMC algorithms in five major categories, from likelihood-based classifiers and distribution-test-based classifiers to feature-based classifiers, machine learning assisted classifiers and blind modulation classifiers Lists detailed implementation for each algorithm based on a unified theoretical background and a comprehensive theoretical and numerical performance comparison Gives clear guidance for the design of specific automatic modulation classifiers for different practical applications in both civilian and military communication systems Includes a MATLAB toolbox on a companion website offering the implementation of a selection of methods discussed in the book

An Introduction to Machine Learning

Author : Gopinath Rebala
Publisher : Springer
ISBN 13 : 3030157296
Total Pages : 275 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis An Introduction to Machine Learning by : Gopinath Rebala

Download or read book An Introduction to Machine Learning written by Gopinath Rebala and published by Springer. This book was released on 2019-05-07 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Just like electricity, Machine Learning will revolutionize our life in many ways – some of which are not even conceivable today. This book provides a thorough conceptual understanding of Machine Learning techniques and algorithms. Many of the mathematical concepts are explained in an intuitive manner. The book starts with an overview of machine learning and the underlying Mathematical and Statistical concepts before moving onto machine learning topics. It gradually builds up the depth, covering many of the present day machine learning algorithms, ending in Deep Learning and Reinforcement Learning algorithms. The book also covers some of the popular Machine Learning applications. The material in this book is agnostic to any specific programming language or hardware so that readers can try these concepts on whichever platforms they are already familiar with. Offers a comprehensive introduction to Machine Learning, while not assuming any prior knowledge of the topic; Provides a complete overview of available techniques and algorithms in conceptual terms, covering various application domains of machine learning; Not tied to any specific software language or hardware implementation.

Handbook of Intelligent Computing and Optimization for Sustainable Development

Author : Mukhdeep Singh Manshahia
Publisher : John Wiley & Sons
ISBN 13 : 1119792622
Total Pages : 944 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Handbook of Intelligent Computing and Optimization for Sustainable Development by : Mukhdeep Singh Manshahia

Download or read book Handbook of Intelligent Computing and Optimization for Sustainable Development written by Mukhdeep Singh Manshahia and published by John Wiley & Sons. This book was released on 2022-02-11 with total page 944 pages. Available in PDF, EPUB and Kindle. Book excerpt: HANDBOOK OF INTELLIGENT COMPUTING AND OPTIMIZATION FOR SUSTAINABLE DEVELOPMENT This book provides a comprehensive overview of the latest breakthroughs and recent progress in sustainable intelligent computing technologies, applications, and optimization techniques across various industries. Optimization has received enormous attention along with the rapidly increasing use of communication technology and the development of user-friendly software and artificial intelligence. In almost all human activities, there is a desire to deliver the highest possible results with the least amount of effort. Moreover, optimization is a very well-known area with a vast number of applications, from route finding problems to medical treatment, construction, finance, accounting, engineering, and maintenance schedules in plants. As far as optimization of real-world problems is concerned, understanding the nature of the problem and grouping it in a proper class may help the designer employ proper techniques which can solve the problem efficiently. Many intelligent optimization techniques can find optimal solutions without the use of objective function and are less prone to local conditions. The 41 chapters comprising the Handbook of Intelligent Computing and Optimization for Sustainable Development by subject specialists, represent diverse disciplines such as mathematics and computer science, electrical and electronics engineering, neuroscience and cognitive sciences, medicine, and social sciences, and provide the reader with an integrated understanding of the importance that intelligent computing has in the sustainable development of current societies. It discusses the emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative intelligent techniques in a variety of sectors, including IoT, manufacturing, optimization, and healthcare. Audience It is a pivotal reference source for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in the field of artificial intelligence in the areas of Internet of Things, renewable energy, optimization, and smart cities.

Machine Learning for Audio, Image and Video Analysis

Author : Francesco Camastra
Publisher : Springer
ISBN 13 : 144716735X
Total Pages : 564 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Machine Learning for Audio, Image and Video Analysis by : Francesco Camastra

Download or read book Machine Learning for Audio, Image and Video Analysis written by Francesco Camastra and published by Springer. This book was released on 2015-07-21 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.

2021 International Conference on Information and Communication Technology Convergence (ICTC)

Author : IEEE Staff
Publisher :
ISBN 13 : 9781665423847
Total Pages : pages
Book Rating : 4.4/5 (238 download)

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Book Synopsis 2021 International Conference on Information and Communication Technology Convergence (ICTC) by : IEEE Staff

Download or read book 2021 International Conference on Information and Communication Technology Convergence (ICTC) written by IEEE Staff and published by . This book was released on 2021-10-20 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: There have been a lot of trials to apply information and communication technology (ICT) to other industrial sectors such as green convergence, smart screen & appliances, next generation broadcasting & media, mobile convergence networks, and other ICT convergence applications and services, all under the name of ICT convergence ICTC is a unique global premier event for researchers, industry professionals, and academics, which aims at interacting with and disseminating information on the latest developments in the emerging industrial convergence centered around information and communication technologies More specifically, it will address challenges with realizing ICT convergence over the various industrial sectors, including the infrastructures and applications in wireless & mobile communication, smart devices & consumer appliances, mobile cloud computing, green communication, healthcare and bioinformatics, Internet of Things (IoT), M2M, Security, and intelligent transportation

Engineering Applications of Neural Networks

Author : John Macintyre
Publisher : Springer
ISBN 13 : 3030202577
Total Pages : 554 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Engineering Applications of Neural Networks by : John Macintyre

Download or read book Engineering Applications of Neural Networks written by John Macintyre and published by Springer. This book was released on 2019-05-14 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019. The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop.

Machine Learning Models and Algorithms for Big Data Classification

Author : Shan Suthaharan
Publisher : Springer
ISBN 13 : 1489976418
Total Pages : 364 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Machine Learning Models and Algorithms for Big Data Classification by : Shan Suthaharan

Download or read book Machine Learning Models and Algorithms for Big Data Classification written by Shan Suthaharan and published by Springer. This book was released on 2015-10-20 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.

Deep Learning Techniques for Biomedical and Health Informatics

Author : Basant Agarwal
Publisher : Academic Press
ISBN 13 : 0128190620
Total Pages : 370 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Deep Learning Techniques for Biomedical and Health Informatics by : Basant Agarwal

Download or read book Deep Learning Techniques for Biomedical and Health Informatics written by Basant Agarwal and published by Academic Press. This book was released on 2020-01-14 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. - Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring - Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making - Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

Advances in VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems

Author : Shubhakar Kalya
Publisher : Springer Nature
ISBN 13 : 9811604436
Total Pages : 457 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Advances in VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems by : Shubhakar Kalya

Download or read book Advances in VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems written by Shubhakar Kalya and published by Springer Nature. This book was released on 2021-04-10 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises select peer-reviewed papers from the International Conference on VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems (VSPICE-2020). The book provides insights into various aspects of the emerging fields in the areas Electronics and Communication Engineering as a holistic approach. The various topics covered in this book include VLSI, embedded systems, signal processing, communication, power electronics and internet of things. This book mainly focuses on the most recent innovations, trends, concerns and practical challenges and their solutions. This book will be useful for academicians, professionals and researchers in the area of electronics and communications and electrical engineering.

Learning Deep Architectures for AI

Author : Yoshua Bengio
Publisher : Now Publishers Inc
ISBN 13 : 1601982941
Total Pages : 145 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Learning Deep Architectures for AI by : Yoshua Bengio

Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.

Advances in Information and Communication

Author : Kohei Arai
Publisher : Springer Nature
ISBN 13 : 3030394425
Total Pages : 943 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Advances in Information and Communication by : Kohei Arai

Download or read book Advances in Information and Communication written by Kohei Arai and published by Springer Nature. This book was released on 2020-02-13 with total page 943 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents high-quality research on the concepts and developments in the field of information and communication technologies, and their applications. It features 134 rigorously selected papers (including 10 poster papers) from the Future of Information and Communication Conference 2020 (FICC 2020), held in San Francisco, USA, from March 5 to 6, 2020, addressing state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of future research. Discussing various aspects of communication, data science, ambient intelligence, networking, computing, security and Internet of Things, the book offers researchers, scientists, industrial engineers and students valuable insights into the current research and next generation information science and communication technologies.

Automatic Speech Recognition

Author : Dong Yu
Publisher : Springer
ISBN 13 : 1447157796
Total Pages : 329 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Automatic Speech Recognition by : Dong Yu

Download or read book Automatic Speech Recognition written by Dong Yu and published by Springer. This book was released on 2014-11-11 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.