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Next-generation wireless networks me...

Comsa, Ioan-Sorin, (1984-)

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Next-generation wireless networks meet advanced machine learning applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Next-generation wireless networks meet advanced machine learning applications/ Ioan-Sorin Comsa and Ramona Trestian, editors.
其他作者:	Comsa, Ioan-Sorin,
出版者:	Hershey, Pennsylvania :IGI Global, : [2019],
面頁冊數:	1 online resource (xxii, 356 p.)
內容註:	Section 1. Machine learning evolution for wireless communications. Chapter 1. The role and applications of machine learning in future self-organizing cellular networks ; Chapter 2. Machine learning in radio resource scheduling ; Chapter 3. Machine learning for internet of things ; Chapter 4. A survey on routing protocols of wireless sensor networks: a reliable data transfer using multiple sink for disaster management ; Chapter 5. Review: effective solutions for challenges in cognitive radio networks ; Chapter 6. Overview of machine learning approaches for wireless communication ; Chapter 7. Machine learning in wireless communication: a Survey -- Section 2. Machine learning and artificial intelligence applications. Chapter 8. Guaranteeing user rates with reinforcement learning in 5g radio access networks ; Chapter 9. Online learning and heuristic algorithms for 5g cloud-RAN load balance ; Chapter 10. Machine learning-based subjective quality estimation for video streaming over wireless networks ; Chapter 11. Adaptive principal component analysis-based outliers detection through neighborhood voting in wireless sensor networks ; Chapter 12. Intelligent tracking and positioning of targets using passive sensing systems ; Chapter 13. Cheerbot: a step ahead of conventional chatbot.
標題:	Cognitive radio networks. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-7458-3
ISBN:	9781522574590 (e-book)

Next-generation wireless networks meet advanced machine learning applications
Next-generation wireless networks meet advanced machine learning applications[electronic resource] /Ioan-Sorin Comsa and Ramona Trestian, editors. - Hershey, Pennsylvania :IGI Global,[2019] - 1 online resource (xxii, 356 p.)

Includes bibliographical references and index.

Section 1. Machine learning evolution for wireless communications. Chapter 1. The role and applications of machine learning in future self-organizing cellular networks ; Chapter 2. Machine learning in radio resource scheduling ; Chapter 3. Machine learning for internet of things ; Chapter 4. A survey on routing protocols of wireless sensor networks: a reliable data transfer using multiple sink for disaster management ; Chapter 5. Review: effective solutions for challenges in cognitive radio networks ; Chapter 6. Overview of machine learning approaches for wireless communication ; Chapter 7. Machine learning in wireless communication: a Survey -- Section 2. Machine learning and artificial intelligence applications. Chapter 8. Guaranteeing user rates with reinforcement learning in 5g radio access networks ; Chapter 9. Online learning and heuristic algorithms for 5g cloud-RAN load balance ; Chapter 10. Machine learning-based subjective quality estimation for video streaming over wireless networks ; Chapter 11. Adaptive principal component analysis-based outliers detection through neighborhood voting in wireless sensor networks ; Chapter 12. Intelligent tracking and positioning of targets using passive sensing systems ; Chapter 13. Cheerbot: a step ahead of conventional chatbot.

Restricted to subscribers or individual electronic text purchasers.

"This book explores the latest trends in various technologies of next generation wireless networks. It looks into the use of machine learning techniques to model various technical problems of next-generation systems that will enable the dynamic optimization of system configuration"--Provided by publisher.

ISBN: 9781522574590 (e-book)Subjects--Topical Terms:

628882
Cognitive radio networks.

LC Class. No.: TK5103.4815 / .N49 2019e

Dewey Class. No.: 006.3/1

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245 0 0 $a Next-generation wireless networks meet advanced machine learning applications $h [electronic resource] / $c Ioan-Sorin Comsa and Ramona Trestian, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2019]
300 $a 1 online resource (xxii, 356 p.)
504 $a Includes bibliographical references and index.
505 0 $a Section 1. Machine learning evolution for wireless communications. Chapter 1. The role and applications of machine learning in future self-organizing cellular networks ; Chapter 2. Machine learning in radio resource scheduling ; Chapter 3. Machine learning for internet of things ; Chapter 4. A survey on routing protocols of wireless sensor networks: a reliable data transfer using multiple sink for disaster management ; Chapter 5. Review: effective solutions for challenges in cognitive radio networks ; Chapter 6. Overview of machine learning approaches for wireless communication ; Chapter 7. Machine learning in wireless communication: a Survey -- Section 2. Machine learning and artificial intelligence applications. Chapter 8. Guaranteeing user rates with reinforcement learning in 5g radio access networks ; Chapter 9. Online learning and heuristic algorithms for 5g cloud-RAN load balance ; Chapter 10. Machine learning-based subjective quality estimation for video streaming over wireless networks ; Chapter 11. Adaptive principal component analysis-based outliers detection through neighborhood voting in wireless sensor networks ; Chapter 12. Intelligent tracking and positioning of targets using passive sensing systems ; Chapter 13. Cheerbot: a step ahead of conventional chatbot.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book explores the latest trends in various technologies of next generation wireless networks. It looks into the use of machine learning techniques to model various technical problems of next-generation systems that will enable the dynamic optimization of system configuration"--Provided by publisher.
650 0 $a Cognitive radio networks. $3 628882
650 0 $a Wireless communication systems $x Automatic control. $3 3395436
650 0 $a Self-organizing systems. $3 556938
650 0 $a Machine learning. $3 533906
700 1 $a Comsa, Ioan-Sorin, $d 1984- $e editor. $3 3395434
700 1 $a Trestian, Ramona, $d 1983- $e editor. $3 3395435
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-7458-3