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Practical Deep Learning for Cloud, Mobile, and Edge

Practical Deep Learning for Cloud, Mobile, and Edge
  • Author : Anirudh Koul,Siddha Ganju,Meher Kasam
  • Publisher :Unknown
  • Release Date :2019-10-14
  • Total pages :620
  • ISBN : 9781492034834
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Summary : Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

Edge AI

Edge AI
  • Author : Xiaofei Wang,Yiwen Han,Victor C. M. Leung,Dusit Niyato,Xueqiang Yan,Xu Chen
  • Publisher :Unknown
  • Release Date :2020-10-23
  • Total pages :151
  • ISBN : 9811561850
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Summary : As an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing.

Edge AI

Edge AI
  • Author : Xiaofei Wang,Yiwen Han,Victor C. M. Leung,Dusit Niyato,Xueqiang Yan,Xu Chen
  • Publisher :Unknown
  • Release Date :2020-08-31
  • Total pages :149
  • ISBN : 9789811561863
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Summary : As an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing.

2020 IEEE International Conference on Smart Internet of Things (SmartIoT)

2020 IEEE International Conference on Smart Internet of Things (SmartIoT)
  • Author : IEEE Staff
  • Publisher :Unknown
  • Release Date :2020-08-14
  • Total pages :229
  • ISBN : 1728165156
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Summary : Internet of Things (IoT) plays an important role in the current and future generation of information, network, and communication developing and applications Smart IoT is an exciting emerging research field that has great potential to transform both our understanding of fundamental computer science principles and our standard of living IoT is being employed in more and more areas making Everything Smart , such as smart home, smart city, intelligent transportation, environment monitoring, security systems, and advanced manufacturing

TinyML

TinyML
  • Author : Pete Warden,Daniel Situnayake
  • Publisher :Unknown
  • Release Date :2019-12-16
  • Total pages :504
  • ISBN : 9781492052012
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Summary : Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size

Artificial Intelligence for Communications and Networks

Artificial Intelligence for Communications and Networks
  • Author : Shuai Han,Liang Ye,Weixiao Meng
  • Publisher :Unknown
  • Release Date :2019-07-04
  • Total pages :512
  • ISBN : 9783030229719
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Summary : This two-volume set LNICST 286-287 constitutes the post-conference proceedings of the First EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2019, held in Harbin, China, in May 2019. The 93 full papers were carefully reviewed and selected from 152 submissions. The papers are organized in topical sections on artificial intelligence, mobile network, deep learning, machine learning, wireless communication, cognitive radio, internet of things, big data, communication system, pattern recognition, channel model, beamforming, signal processing, 5G, mobile management, resource management, wireless position.

Artificial Intelligence and Security

Artificial Intelligence and Security
  • Author : Xingming Sun
  • Publisher :Unknown
  • Release Date :2021
  • Total pages :229
  • ISBN : 9783030578848
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Summary :

Artificial Intelligence Applications and Innovations

Artificial Intelligence Applications and Innovations
  • Author : John MacIntyre,Ilias Maglogiannis,Lazaros Iliadis,Elias Pimenidis
  • Publisher :Unknown
  • Release Date :2019-05-15
  • Total pages :244
  • ISBN : 9783030199098
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Summary : This book constitutes the refereed proceedings of two International Workshops held as parallel events of the 15th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2019, in Hersonissos, Crete, Greece, in May 2019: the 8th Mining Humanistic Data Workshop, MHDW 2019, and the 4th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2019. The 6 full papers and 4 short papers presented at MHDW 2019 were carefully reviewed and selected from 13 submissions; out of the 14 papers submitted to 5G-PINE 2019, 6 were accepted as full papers and 1 as short paper. The MHDW papers focus on the application of innovative as well as existing data matching, fusion and mining and knowledge discovery and management techniques (such as decision rules, decision trees, association rules, ontologies and alignments, clustering, filtering, learning, classifier systems, neural networks, support vector machines, preprocessing, post processing, feature selection, visualization techniques) to data derived from all areas of humanistic sciences, e.g., linguistic, historical, behavioral, psychological, artistic, musical, educational, social, and ubiquitous computing and bioinformatics. The papers presented at 5G-PINE focus on several innovative findings coming directly from modern European research in the area of modern 5G telecommunications infrastructures and related innovative services and cover a wide variety of technical and business aspects promoting options for growth and development.

Artificial Intelligence and Security

Artificial Intelligence and Security
  • Author : Xingming Sun,Jinwei Wang,Elisa Bertino
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :713
  • ISBN : 9789811580864
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Summary : The 3-volume set CCIS 1252 until CCIS 1254 constitutes the refereed proceedings of the 6th International Conference on Artificial Intelligence and Security, ICAIS 2020, which was held in Hohhot, China, in July 2020. The conference was formerly called "International Conference on Cloud Computing and Security" with the acronym ICCCS. The total of 178 full papers and 8 short papers presented in this 3-volume proceedings was carefully reviewed and selected from 1064 submissions. The papers were organized in topical sections as follows: Part I: artificial intelligence; Part II: artificial intelligence; Internet of things; information security; Part III: information security; big data and cloud computing; information processing.

Artificial Intelligence in China

Artificial Intelligence in China
  • Author : Qilian Liang,Wei Wang,Jiasong Mu,Xin Liu,Zhenyu Na,Bingcai Chen
  • Publisher :Unknown
  • Release Date :2020-01-31
  • Total pages :667
  • ISBN : 9789811501876
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Summary : This book brings together papers presented at the International Conference on Artificial Intelligence in China (ChinaAI) 2019, which provided a venue for disseminating the latest advances and discussing the interactions and links between the various subfields of AI. Addressing topics that cover virtually all aspects of AI and the latest developments in China, the book is chiefly intended for undergraduate and graduate students in Electrical Engineering, Computer Science, and Mathematics, for researchers and engineers from academia and industry, and for government employees (e.g. at the NSF, DOD, and DOE).

Artificial Intelligence and Deep Learning for Decision Makers

Artificial Intelligence and Deep Learning for Decision Makers
  • Author : Dr. Jagreet Kaur,Navdeep Singh Gill
  • Publisher :Unknown
  • Release Date :2019-12-28
  • Total pages :248
  • ISBN : 9789389328684
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Summary : Learn modern-day technologies from modern-day technical giants DESCRIPTION The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations. The first two chapters describe the introduction of the artificial intelligence and deep learning methods. In the first chapter, the concept of human thinking process, starting from the biochemical responses within the structure of neurons to the problem-solving steps through computational thinking skills are discussed. All chapters after the first two should be considered as the study of different technological and Artificial Intelligence giants of current age. These chapters are placed in a way that each chapter could be considered a separate study of a separate company, which includes the achievements of intelligent services currently provided by the company, discussion on the business model of the company towards the use of the deep learning technologies, the advancement of the web services which are incorporated with intelligent capability introduced by company, the efforts of the company in contributing to the development of the artificial intelligence and deep learning research. KEY FEATURES Real-world success and failure stories of artificial intelligence explained Understand concepts of artificial intelligence and deep learning methods Learn how to use artificial intelligence and deep learning methods Know how to prepare dataset and implement models using industry leading Python packages You’ll be able to apply and analyze the results produced by the models for prediction WHAT WILL YOU LEARN How to use the algorithms written in the Python programming language to design models and perform predictions in general datasets Understand use cases in different industries related to the implementation of artificial intelligence and deep learning methods Learn the use of potential ideas in artificial intelligence and deep learning methods to improve the operational processes or new products and how services can be produced based on the methods WHO THIS BOOK IS FOR This book is targeted to business and organization leaders, technology enthusiasts, professionals, and managers who seek knowledge of artificial intelligence and deep learning methods. Table of Contents Artificial Intelligence and Deep Learning Data Science for Business Analysis Decision Making Intelligent Computing Strategies By Google Cognitive Learning Services in IBM Watson Advancement web services by Baidu Improved Social Business by Facebook Personalized Intelligent Computing by Apple Cloud Computing Intelligent by Microsoft

Edge Intelligence in the Making

Edge Intelligence in the Making
  • Author : Sen Lin,Zhi Zhou,Zhaofeng Zhang,Xu Chen,Junshan Zhang
  • Publisher :Unknown
  • Release Date :2020-10-21
  • Total pages :233
  • ISBN : 9781681739915
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Summary : With the explosive growth of mobile computing and Internet of Things (IoT) applications, as exemplified by AR/VR, smart city, and video/audio surveillance, billions of mobile and IoT devices are being connected to the Internet, generating zillions of bytes of data at the network edge. Driven by this trend, there is an urgent need to push the frontiers of artificial intelligence (AI) to the network edge to fully unleash the potential of IoT big data. Indeed, the marriage of edge computing and AI has resulted in innovative solutions, namely edge intelligence or edge AI. Nevertheless, research and practice on this emerging inter-disciplinary field is still in its infancy stage. To facilitate the dissemination of the recent advances in edge intelligence in both academia and industry, this book conducts a comprehensive and detailed survey of the recent research efforts and also showcases the authors' own research progress on edge intelligence. Specifically, the book first reviews the background and present motivation for AI running at the network edge. Next, it provides an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning models toward training/inference at the network edge. To illustrate the research problems for edge intelligence, the book also showcases four of the authors' own research projects on edge intelligence, ranging from rigorous theoretical analysis to studies based on realistic implementation. Finally, it discusses the applications, marketplace, and future research opportunities of edge intelligence. This emerging interdisciplinary field offers many open problems and yet also tremendous opportunities, and this book only touches the tip of iceberg. Hopefully, this book will elicit escalating attention, stimulate fruitful discussions, and open new directions on edge intelligence.

Competing in the Age of AI

Competing in the Age of AI
  • Author : Marco Iansiti,Karim R. Lakhani
  • Publisher :Unknown
  • Release Date :2020-01-07
  • Total pages :288
  • ISBN : 9781633697638
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Summary : "a provocative new book" -- The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning--to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples--including many from the most powerful and innovative global, AI-driven competitors--and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.

Edge and Fog Analytics

Edge and Fog Analytics
  • Author : Abdallah Bari
  • Publisher :Unknown
  • Release Date :2018-09-20
  • Total pages :112
  • ISBN : 1723874108
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Summary : Edge and fog analytics are on the rise and expected to continue growing in coming years. The global edge analytics market is expected to see a significant growth rate with a substantial increase in investment aiming to improve the overall edge analytics. Today, edge and fog analytics are not only powered by machine learning (ML) and artificial intelligence (AI) but also by the expansion of cloud-to-edge range of ML/AI chips that are built-in to accommodate high-performance computing (HPC) requirements, in the vicinity of where data is produced.The Internet of Things (IoT) devices with their embedded processing capabilities using new tiny chips designed to run complex models at the edge, are more appealing for ML and AI applications. These chip-enhanced devices are directly connected to a wide range of sensors, such as iPhone sensors, meteorological and hydrological sensors, which are capturing large quantity of input data as streaming data. Edge and fog analytics, at the edges, reduce the latency between data capture and decision-making by acting immediately on streaming data, which may be required in critical remote operations.Both cloud and edge analytics will be supplementing each other in handling large-scale workloads and delivering data insights. The edge analytics handles a subset of data, which can be both processed and analysed at the edge with the results transmitted back to the local area network level, the fog, which in turn transmits the data into the cloud. This period, of the emerging cloud-to-edge ecosystem, is referred to as the "Cambrian Explosion" period, by analogy to the sudden appearance of all major animal body plans some 500 million years ago, leading to changes in earth's ecosystems.This new book is about this paradigm shift in the current analytics landscape where the edges and the fog are becoming the new interface for analytics insights and for hosting new artificial intelligence applications. According to Automation World: "Both edge analytics and fog analytics involve pushing intelligence and processing capabilities down closer to where the data originates."

Computing in Communication Networks

Computing in Communication Networks
  • Author : Frank Fitzek,Fabrizio Granelli,Patrick Seeling
  • Publisher :Unknown
  • Release Date :2020-05-20
  • Total pages :522
  • ISBN : 9780128209042
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Summary : Computing in Communication Networks: From Theory to Practice provides comprehensive details and practical implementation tactics on the novel concepts and enabling technologies at the core of the paradigm shift from store and forward (dumb) to compute and forward (intelligent) in future communication networks and systems. The book explains how to create virtualized large scale testbeds using well-established open source software, such as Mininet and Docker. It shows how and where to place disruptive techniques, such as machine learning, compressed sensing, or network coding in a newly built testbed. In addition, it presents a comprehensive overview of current standardization activities. Specific chapters explore upcoming communication networks that support verticals in transportation, industry, construction, agriculture, health care and energy grids, underlying concepts, such as network slicing and mobile edge cloud, enabling technologies, such as SDN/NFV/ ICN, disruptive innovations, such as network coding, compressed sensing and machine learning, how to build a virtualized network infrastructure testbed on one’s own computer, and more. Provides a uniquely comprehensive overview on the individual building blocks that comprise the concept of computing in future networks Gives practical hands-on activities to bridge theory and implementation Includes software and examples that are not only employed throughout the book, but also hosted on a dedicated website

Edge Computing

Edge Computing
  • Author : Fadi Al-Turjman
  • Publisher :Unknown
  • Release Date :2018-11-09
  • Total pages :188
  • ISBN : 9783319990613
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Summary : In this book, contributors provide insights into the latest developments of Edge Computing/Mobile Edge Computing, specifically in terms of communication protocols and related applications and architectures. The book provides help to Edge service providers, Edge service consumers, and Edge service developers interested in getting the latest knowledge in the area. The book includes relevant Edge Computing topics such as applications; architecture; services; inter-operability; data analytics; deployment and service; resource management; simulation and modeling; and security and privacy. Targeted readers include those from varying disciplines who are interested in designing and deploying Edge Computing. Features the latest research related to Edge Computing, from a variety of perspectives; Tackles Edge Computing in academia and industry, featuring a variety of new and innovative operational ideas; Provides a strong foundation for researchers to advance further in the Edge Computing domain.

Hands-On Artificial Intelligence for IoT

Hands-On Artificial Intelligence for IoT
  • Author : Amita Kapoor
  • Publisher :Unknown
  • Release Date :2019-01-31
  • Total pages :390
  • ISBN : 9781788832762
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Summary : Build smarter systems by combining artificial intelligence and the Internet of Things—two of the most talked about topics today Key Features Leverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT data Process IoT data and predict outcomes in real time to build smart IoT models Cover practical case studies on industrial IoT, smart cities, and home automation Book Description There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter. This book starts by covering the process of gathering and preprocessing IoT data gathered from distributed sources. You will learn different AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing to build smart IoT systems. You will also leverage the power of AI to handle real-time data coming from wearable devices. As you progress through the book, techniques for building models that work with different kinds of data generated and consumed by IoT devices such as time series, images, and audio will be covered. Useful case studies on four major application areas of IoT solutions are a key focal point of this book. In the concluding chapters, you will leverage the power of widely used Python libraries, TensorFlow and Keras, to build different kinds of smart AI models. By the end of this book, you will be able to build smart AI-powered IoT apps with confidence. What you will learn Apply different AI techniques including machine learning and deep learning using TensorFlow and Keras Access and process data from various distributed sources Perform supervised and unsupervised machine learning for IoT data Implement distributed processing of IoT data over Apache Spark using the MLLib and H2O.ai platforms Forecast time-series data using deep learning methods Implementing AI from case studies in Personal IoT, Industrial IoT, and Smart Cities Gain unique insights from data obtained from wearable devices and smart devices Who this book is for If you are a data science professional or a machine learning developer looking to build smart systems for IoT, Hands-On Artificial Intelligence for IoT is for you. If you want to learn how popular artificial intelligence (AI) techniques can be used in the Internet of Things domain, this book will also be of benefit. A basic understanding of machine learning concepts will be required to get the best out of this book.

Computer Information Systems and Industrial Management

Computer Information Systems and Industrial Management
  • Author : Khalid Saeed,Rituparna Chaki,Valentina Janev
  • Publisher :Unknown
  • Release Date :2019-10-07
  • Total pages :536
  • ISBN : 9783030289577
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Summary : This book constitutes the proceedings of the 18th International Conference on Computer Information Systems and Industrial Management Applications, CISIM 2019, held in Belgrade, Serbia, in September 2019. The 43 full papers presented together with 3 abstracts of keynotes were carefully reviewed and selected from 70 submissions. The main topics covered by the chapters in this book are biometrics, security systems, multimedia, classification and clustering, industrial management. Besides these, the reader will find interesting papers on computer information systems as applied to wireless networks, computer graphics, and intelligent systems. The papers are organized in the following topical sections: biometrics and pattern recognition applications; computer information systems; industrial management and other applications; machine learning and high performance computing; modelling and optimization; various aspects of computer security.

Blondie24

Blondie24
  • Author : David B. Fogel
  • Publisher :Unknown
  • Release Date :2002
  • Total pages :404
  • ISBN : 1558607838
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Summary : "Blondie24 tells the story of a computer that taught itself to play checkers far better than its creators ever could by emulating the principles of Darwinian evolution and discovering innovative ways to approach the game. In this year of 2001, as we remember Arthur C. Clarke's predictions, David Fogel dramatically demonstrates how evolutionary computation may enable humans to create a thinking machine far more readily than the techniques traditionally used in the study of artificial intelligence."--BOOK JACKET.

Machine Learning for Future Wireless Communications

Machine Learning for Future Wireless Communications
  • Author : Fa-Long Luo
  • Publisher :Unknown
  • Release Date :2020-02-10
  • Total pages :496
  • ISBN : 9781119562252
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Summary : 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.

Fog Computing in the Internet of Things

Fog Computing in the Internet of Things
  • Author : Amir M. Rahmani,Pasi Liljeberg,Jürgo-Sören Preden,Axel Jantsch
  • Publisher :Unknown
  • Release Date :2017-06-29
  • Total pages :172
  • ISBN : 9783319576398
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Summary : This book describes state-of-the-art approaches to Fog Computing, including the background of innovations achieved in recent years. Coverage includes various aspects of fog computing architectures for Internet of Things, driving reasons, variations and case studies. The authors discuss in detail key topics, such as meeting low latency and real-time requirements of applications, interoperability, federation and heterogeneous computing, energy efficiency and mobility, fog and cloud interplay, geo-distribution and location awareness, and case studies in healthcare and smart space applications.