Reinforcement Learning For Reconfigurable Intelligent Surfaces
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Reinforcement Learning For Reconfigurable Intelligent Surfaces
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Author : Alice Faisal
language : en
Publisher: Springer Nature
Release Date :
Reinforcement Learning For Reconfigurable Intelligent Surfaces written by Alice Faisal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Intelligent Reconfigurable Surfaces Irs For Prospective 6g Wireless Networks
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Author : Muhammad Ali Imran
language : en
Publisher: John Wiley & Sons
Release Date : 2022-12-13
Intelligent Reconfigurable Surfaces Irs For Prospective 6g Wireless Networks written by Muhammad Ali Imran and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-13 with Technology & Engineering categories.
Authoritative resource covering preliminary concepts and advanced concerns in the field of IRS and its role in 6G wireless systems Intelligent Reconfigurable Surfaces (IRS) for Prospective 6G Wireless Networks provides an in-depth treatment of the fundamental physics behind reconfigurable metasurfaces, also known as intelligent reflecting surfaces (IRS), and outlines the research roadmap towards their development as a low-complexity and energy-efficient solution aimed at turning the wireless environment into a software-defined entity. The text demonstrates IRS from different angles, including the underlying physics, hardware architecture, operating principles, and prototype designs. It enables readers to grasp the knowledge of the interplay of IRS and state-of-the-art technologies, examining the advantages, key principles, challenges, and potential use-cases. Practically, it equips readers with the fundamental knowledge of the operational principles of reconfigurable metasurfaces, resulting in its potential applications in various intelligent, autonomous future wireless communication technologies. To aid in reader comprehension, around 50 figures, tables, illustrations, and photographs to comprehensively present the material are also included. Edited by a team of highly qualified professionals in the field, sample topics covered in Intelligent Reconfigurable Surfaces (IRS) for Prospective 6G Wireless Networks are as follows: Evolution of antenna arrays design, introducing the fundamental principles of antenna theory and reviewing the stages of development of the field Beamforming design for IRS-assisted communications, discussing optimal IRS configuration in conjunction with overviewing novel beamforming designs Reconfigurable metasurfaces from physics to applications, discussing the working principles of tunable/reconfigurable metasurfaces and their capabilities and functionalities IRS hardware architectures, detailing the general hardware architecture of IRS and features related to the IRS’s main operational principle Wireless communication systems assisted by IRS, discussing channel characterization, system integration, and aspects related to the performance analysis and network optimization of state-of-the-art wireless applications. For students and engineers in wireless communications, microwave engineering, and radio hardware and design, Intelligent Reconfigurable Surfaces (IRS) for Prospective 6G Wireless Networks serves as an invaluable resource on the subject and is a useful course accompaniment for general Antenna Theory, Microwave Engineering, Electromagnetics courses.
Reinforcement Learning For Maritime Communications
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Author : Liang Xiao
language : en
Publisher: Springer Nature
Release Date : 2023-07-25
Reinforcement Learning For Maritime Communications written by Liang Xiao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-25 with Computers categories.
This book demonstrates that the reliable and secure communication performance of maritime communications can be significantly improved by using intelligent reflecting surface (IRS) aided communication, privacy-aware Internet of Things (IoT) communications, intelligent resource management and location privacy protection. In the IRS aided maritime communication system, the reflecting elements of IRS can be intelligently controlled to change the phase of signal, and finally enhance the received signal strength of maritime ships (or sensors) or jam maritime eavesdroppers illustrated in this book. The power and spectrum resource in maritime communications can be jointly optimized to guarantee the quality of service (i.e., security and reliability requirements), and reinforcement leaning is adopted to smartly choose the resource allocation strategy. Moreover, learning based privacy-aware offloading and location privacy protection are proposed to intelligently guarantee the privacy-preserving requirements of maritime ships or (sensors). Therefore, these communication schemes based on reinforcement learning algorithms can help maritime communication systems to improve the information security, especially in dynamic and complex maritime environments. This timely book also provides broad coverage of the maritime wireless communication issues, such as reliability, security, resource management, and privacy protection. Reinforcement learning based methods are applied to solve these issues. This book includes four rigorously refereed chapters from prominent international researchers working in this subject area. The material serves as a useful reference for researchers, graduate students. Practitioners seeking solutions to maritime wireless communication and security related issues will benefit from this book as well.
Machine Learning Algorithms For Signal And Image Processing
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Author : Deepika Ghai
language : en
Publisher: John Wiley & Sons
Release Date : 2022-11-18
Machine Learning Algorithms For Signal And Image Processing written by Deepika Ghai and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-18 with Technology & Engineering categories.
Machine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.
2021 Ieee International Conference On Communications Workshops Icc Workshops
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2021-06-14
2021 Ieee International Conference On Communications Workshops Icc Workshops written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-14 with categories.
IEEE ICC is one of the two flagship IEEE conferences in the field of communications Montreal is to host this conference in 2021 Each annual IEEE ICC conference typically attracts approximately 1,500 2,000 attendees, and will present over 1,000 research works over its duration As well as being an opportunity to share pioneering research ideas and developments, the conference is also an excellent networking and publicity event, giving the opportunity for businesses and clients to link together, and presenting the scope for companies to publicize themselves and their products among the leaders of communications industries from all over the world
Machine Learning And Intelligent Communication
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Author : Xiaolin Jiang
language : en
Publisher: Springer Nature
Release Date : 2023-04-08
Machine Learning And Intelligent Communication written by Xiaolin Jiang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-08 with Computers categories.
This book constitutes the refereed post-conference proceedings of the 7th International Conference on Machine Learning and Intelligent Computing which was held in October 2022 in Jinhua, China. Due to COVID-19 pandemic the conference was held virtually. The 16 full papers of MLICOM 2022 were selected from 41 submissions and are clustered in thematical issues on applications of neural network and deep learning; intelligent massive MIMO communications; machine learning algorithms and intelligent networks.
Intelligent Surfaces Empowered 6g Wireless Network
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Author : Qingqing Wu
language : en
Publisher: John Wiley & Sons
Release Date : 2023-12-27
Intelligent Surfaces Empowered 6g Wireless Network written by Qingqing Wu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-27 with Technology & Engineering categories.
INTELLIGENT SURFACES EMPOWERED 6G WIRELESS NETWORK Integrate intelligent surfaces into the wireless networks of the future. The next generation of wireless technology (6G) promises to transform wireless communication and human interconnectivity like never before. Intelligent surface, which adopts significant numbers of small reflective surfaces to reconfigure wireless connections and improve network performance, has recently been recognized as a critical component for enabling future 6G. The next phase of wireless technology demands engineers and researchers are familiar with this technology and are able to cope with the challenges. Intelligent Surfaces Empowered 6G Wireless Network provides a thorough overview of intelligent surface technologies and their applications in wireless networks and 6G. It includes an introduction to the fundamentals of intelligent surfaces, before moving to more advanced content for engineers who understand them and look to apply them in the 6G realm. Its detailed discussion of the challenges and opportunities posed by intelligent surfaces empowered wireless networks makes it the first work of its kind. Intelligent Surfaces Empowered 6G Wireless Network readers will also find: An editorial team including the original pioneers of intelligent surface technology. Detailed coverage of subjects including MIMO, terahertz, NOMA, energy harvesting, physical layer security, computing, sensing, machine learning, and more. Discussion of hardware design, signal processing techniques, and other critical aspects of IRS engineering. Intelligent Surfaces Empowered 6G Wireless Network is a must for students, researchers, and working engineers looking to understand this vital aspect of the coming 6G revolution.
Deep Reinforcement Learning For Wireless Networks
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Author : F. Richard Yu
language : en
Publisher: Springer
Release Date : 2019-01-17
Deep Reinforcement Learning For Wireless Networks written by F. Richard Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-17 with Technology & Engineering categories.
This Springerbrief presents a deep reinforcement learning approach to wireless systems to improve system performance. Particularly, deep reinforcement learning approach is used in cache-enabled opportunistic interference alignment wireless networks and mobile social networks. Simulation results with different network parameters are presented to show the effectiveness of the proposed scheme. There is a phenomenal burst of research activities in artificial intelligence, deep reinforcement learning and wireless systems. Deep reinforcement learning has been successfully used to solve many practical problems. For example, Google DeepMind adopts this method on several artificial intelligent projects with big data (e.g., AlphaGo), and gets quite good results.. Graduate students in electrical and computer engineering, as well as computer science will find this brief useful as a study guide. Researchers, engineers, computer scientists, programmers, and policy makers will also find this brief to be a useful tool.
Advances In Electromagnetics Empowered By Artificial Intelligence And Deep Learning
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Author : Sawyer D. Campbell
language : en
Publisher: John Wiley & Sons
Release Date : 2023-08-03
Advances In Electromagnetics Empowered By Artificial Intelligence And Deep Learning written by Sawyer D. Campbell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-03 with Technology & Engineering categories.
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The content of the book covers all-dielectric and metallodielectric optical metasurface deep learning-accelerated inverse-design, deep neural networks for inverse scattering, applications of deep learning for advanced antenna design, and other related topics. To aid in reader comprehension, each chapter contains 10-15 illustrations, including prototype photos, line graphs, and electric field plots. Contributed to by leading research groups in the field, sample topics covered in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning include: Optical and photonic design, including generative machine learning for photonic design and inverse design of electromagnetic systems RF and antenna design, including artificial neural networks for parametric electromagnetic modeling and optimization and analysis of uniform and non-uniform antenna arrays Inverse scattering, target classification, and other applications, including deep learning for high contrast inverse scattering of electrically large structures Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning is a must-have resource on the topic for university faculty, graduate students, and engineers within the fields of electromagnetics, wireless communications, antenna/RF design, and photonics, as well as researchers at large defense contractors and government laboratories.
The The Reinforcement Learning Workshop
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Author : Alessandro Palmas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-18
The The Reinforcement Learning Workshop written by Alessandro Palmas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Computers categories.
Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guide Key FeaturesUse TensorFlow to write reinforcement learning agents for performing challenging tasksLearn how to solve finite Markov decision problemsTrain models to understand popular video games like BreakoutBook Description Various intelligent applications such as video games, inventory management software, warehouse robots, and translation tools use reinforcement learning (RL) to make decisions and perform actions that maximize the probability of the desired outcome. This book will help you to get to grips with the techniques and the algorithms for implementing RL in your machine learning models. Starting with an introduction to RL, you’ll be guided through different RL environments and frameworks. You’ll learn how to implement your own custom environments and use OpenAI baselines to run RL algorithms. Once you’ve explored classic RL techniques such as Dynamic Programming, Monte Carlo, and TD Learning, you’ll understand when to apply the different deep learning methods in RL and advance to deep Q-learning. The book will even help you understand the different stages of machine-based problem-solving by using DARQN on a popular video game Breakout. Finally, you’ll find out when to use a policy-based method to tackle an RL problem. By the end of The Reinforcement Learning Workshop, you’ll be equipped with the knowledge and skills needed to solve challenging problems using reinforcement learning. What you will learnUse OpenAI Gym as a framework to implement RL environmentsFind out how to define and implement reward functionExplore Markov chain, Markov decision process, and the Bellman equationDistinguish between Dynamic Programming, Monte Carlo, and Temporal Difference LearningUnderstand the multi-armed bandit problem and explore various strategies to solve itBuild a deep Q model network for playing the video game BreakoutWho this book is for If you are a data scientist, machine learning enthusiast, or a Python developer who wants to learn basic to advanced deep reinforcement learning algorithms, this workshop is for you. A basic understanding of the Python language is necessary.