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Machine Learning for Future Wireless Communications, Fa–Long Luo


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Цена: 124550.00T
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Автор: Fa–Long Luo   (Луо Фа-Лонг)
Название:  Machine Learning for Future Wireless Communications
Перевод названия: Луо Фа-Лонг: Машинное обучение для беспроводной связи будущего
ISBN: 9781119562252
Издательство: Wiley
Классификация:




ISBN-10: 1119562252
Обложка/Формат: Hardcover
Страницы: 496
Вес: 1.10 кг.
Дата издания: 13.02.2020
Серия: Wiley - ieee
Язык: English
Размер: 185 x 262 x 26
Читательская аудитория: Professional & vocational
Ключевые слова: Electronics & communications engineering,Artificial intelligence
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание:

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.



Machine Learning with Spark and Python: Essential Techniques for Predictive Analytics

Автор: Michael Bowles
Название: Machine Learning with Spark and Python: Essential Techniques for Predictive Analytics
ISBN: 1119561930 ISBN-13(EAN): 9781119561934
Издательство: Wiley
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Цена: 40120.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Cambridge for DGB 2nd Edition is a four-level American English integrated skills series for the Upper Secondary public school market in Mexico. Its syllabus is strictly aligned to the national Direccion General del Bachillerato program. It is a series that offers teachers a hands-on and practical solution to teaching English in the classroom. It builds students` language skills from A1 to A2+ in the CEFR.

Quantum Machine Learning

Автор: Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Sourav De, Elizabeth Behrman, Susanta Chakraborti
Название: Quantum Machine Learning
ISBN: 311067064X ISBN-13(EAN): 9783110670646
Издательство: Walter de Gruyter
Цена: 136310.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. For example, the outcome of the measurement of a qubit could reveal the result of a binary classification task. While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices. The salient features of the book include: In depth analysis of the subject matter with mathematical discourse Video demonstration of each chapter for enabling the readers to have a good understanding of the chapter contents. Examples on real life applications. Illustrative diagrams Coding examples

An Introduction to Machine Learning

Автор: Miroslav Kubat
Название: An Introduction to Machine Learning
ISBN: 3319348868 ISBN-13(EAN): 9783319348865
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications.

Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks

Автор: Krishna Kant Singh, Akansha Singh, Korhan Cengiz,
Название: Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
ISBN: 1119640369 ISBN-13(EAN): 9781119640363
Издательство: Wiley
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Цена: 167850.00 T
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Описание:

Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.


Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Control and Signal Processing Applications for Mobile and Aerial Robotic Systems

Автор: Oleg Sergiyenko, Moises Rivas-Lopez, Wendy Flores-
Название: Control and Signal Processing Applications for Mobile and Aerial Robotic Systems
ISBN: 152259924X ISBN-13(EAN): 9781522599241
Издательство: Mare Nostrum (Eurospan)
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Цена: 188100.00 T
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Описание: As technology continues to develop, certain innovations are beginning to cover a wide range of applications, specifically mobile robotic systems. The boundaries between the various automation methods and their implementations are not strictly defined, with overlaps occurring. Specificity is required regarding the research and development of android systems and how they pertain to modern science. Control and Signal Processing Applications for Mobile and Aerial Robotic Systems is a pivotal reference source that provides vital research on the current state of control and signal processing of portable robotic designs. While highlighting topics such as digital systems, control theory, and mathematical methods, this publication explores original inquiry contributions and the instrumentation of mechanical systems in the industrial and scientific fields. This book is ideally designed for technicians, engineers, industry specialists, researchers, academicians, and students seeking current research on today's execution of mobile robotic schemes.

Machine Learning Applications: Emerging Trends

Автор: Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy
Название: Machine Learning Applications: Emerging Trends
ISBN: 3110608537 ISBN-13(EAN): 9783110608533
Издательство: Walter de Gruyter
Цена: 123910.00 T
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Описание:

The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.


Green and Software-defined Wireless Networks: From Theory to Practice

Автор: Chih-Lin I, Guanding Yu, Shuangfeng Han, Geoffrey
Название: Green and Software-defined Wireless Networks: From Theory to Practice
ISBN: 1108417329 ISBN-13(EAN): 9781108417327
Издательство: Cambridge Academ
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Цена: 97150.00 T
Наличие на складе: Поставка под заказ.
Описание: An expert treatment of the state-of-the-art in green and soft communications, covering theory, 5G physical layer design, network architecture, energy efficient resource management strategies, and applications of wireless big data and artificial intelligence to wireless network design. Ideal for graduate students, professionals and researchers.

5G Wireless Systems

Автор: Yang Yang; Jing Xu; Guang Shi; Cheng-Xiang Wang
Название: 5G Wireless Systems
ISBN: 3319871811 ISBN-13(EAN): 9783319871813
Издательство: Springer
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Цена: 149060.00 T
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Описание: This book focuses on key simulation and evaluation technologies for 5G systems. Based on the most recent research results from academia and industry, it describes the evaluation methodologies in depth for network and physical layer technologies. The evaluation methods are discussed in depth. It also covers the analysis of the 5G candidate technologies and the testing challenges, the evolution of the testing technologies, fading channel measurement and modeling, software simulations, software hardware cosimulation, field testing and other novel evaluation methods. The fifth-generation (5G) mobile communications system targets highly improved network performances in terms of the network capacity and the number of connections.Testing and evaluation technologies is widely recognized and plays important roles in the wireless technology developments, along with the research on basic theory and key technologies. The investigation and developments on the multi-level and comprehensive evaluations for 5G new technologies, provides important performance references for the 5G technology filtering and future standardizations. Students focused on telecommunications, electronic engineering, computer science or other related disciplines will find this book useful as a secondary text. Researchers and professionals working within these related fields will also find this book useful as a reference.

Machine Learning and Intelligent Communications

Автор: Xiangping Bryce Zhai; Bing Chen; Kun Zhu
Название: Machine Learning and Intelligent Communications
ISBN: 3030323870 ISBN-13(EAN): 9783030323875
Издательство: Springer
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Цена: 83850.00 T
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Описание: This volume constitutes the refereed post-conference proceedings of the Fourth International Conference on Machine Learning and Intelligent Communications, MLICOM 2019, held in Nanjing, China, in August 2019. The 65 revised full papers were carefully selected from 114 submissions. The papers are organized thematically in machine learning, intelligent positioning and navigation, intelligent multimedia processing and security, wireless mobile network and security, cognitive radio and intelligent networking, IoT, intelligent satellite communications and networking, green communication and intelligent networking, ad-hoc and sensor networks, resource allocation in wireless and cloud networks, signal processing in wireless and optical communications, and intelligent cooperative communications and networking.

Computational Intelligence for Machine Learning and Healthcare Informatics

Автор: Rajshree Srivastava, Pradeep Kumar Mallick, Siddha
Название: Computational Intelligence for Machine Learning and Healthcare Informatics
ISBN: 3110647826 ISBN-13(EAN): 9783110647822
Издательство: Walter de Gruyter
Цена: 136310.00 T
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Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS
By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

Machine Learning and Visual Perception

Автор: Baochang Zhang
Название: Machine Learning and Visual Perception
ISBN: 3110595532 ISBN-13(EAN): 9783110595536
Издательство: Walter de Gruyter
Цена: 61920.00 T
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Описание:

Machine Learning and Visual Perception provides an up-to-date overview on the topic, including the PAC model, decision tree, Bayesian learning, support vector machines, AdaBoost, compressive sensing and so on.Both classic and novel algorithms are introduced in classifier design, face recognition, deep learning, time series recognition, image classification, and object detection.



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