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005 20240523125542.0
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008 200730s2020 nju ob 001 0 eng d
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019 _a1225940022
_a1351594479
020 _a9781119640554
_q(electronic bk.)
020 _a1119640555
_q(electronic bk.)
020 _a9781119640578
020 _a1119640571
020 _z9781119640363
020 _z1119640369
024 8 _a9781119640363
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035 _a(OCoLC)1179144467
_z(OCoLC)1225940022
_z(OCoLC)1351594479
037 _aCL0501000172
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050 4 _aQA76.59
_b.M334 2020eb
082 0 4 _a006.3/1
_223
049 _aMAIN
245 0 0 _aMachine learning and cognitive computing for mobile communications and wireless networks /
_cedited by Krishna Kant Singh, KIET Group of Institutions, Delhi-NCR, Ghaziabad, India, Akansha Singh, Department of CSE, ASET, Amity University Uttar Pradesh, Noida, India, Korhan Cengiz, Electrical-Electronics Engineering Department, Trakya University, Edine, Turkey, and Dac-Nhuong Le, Faculty of Information Technology, Haiphong University, Vietnam.
264 1 _aHoboken, NJ, USA :
_bWiley-Scrivener,
_c2020.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
347 _atext file
_2rda
504 _aIncludes bibliographical references and index.
520 _a"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"--
_cProvided by publisher
588 0 _aPrint version record.
542 _fCopyright � 2020 by John Wiley & Sons
_g2020
590 _aJohn Wiley and Sons
_bWiley Online Library: Complete oBooks
650 0 _aMobile computing
_xTechnological innovations.
650 0 _aMachine learning.
650 0 _aSoft computing.
650 6 _aInformatique mobile
_xInnovations.
650 6 _aApprentissage automatique.
650 6 _aInformatique douce.
650 7 _aMachine learning
_2fast
650 7 _aSoft computing
_2fast
700 1 _aSingh, Krishna Kant
_q(Telecommunications professor),
_eeditor.
_1https://id.oclc.org/worldcat/entity/E39PCjGky6kMQ483JRwvk4jBKb
758 _ihas work:
_aMachine learning and cognitive computing for mobile communications and wireless networks (Text)
_1https://id.oclc.org/worldcat/entity/E39PCGD6JgH3YWxxjWHxpq87QC
_4https://id.oclc.org/worldcat/ontology/hasWork
776 0 8 _iPrint version:
_tMachine learning and cognitive computing for mobile communications and wireless networks.
_dHoboken, NJ, USA : Wiley-Scrivener, 2020
_z9781119640363
_w(DLC) 2020023352
_w(OCoLC)1157843811
856 4 0 _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781119640554
994 _a92
_bINLUM
999 _c12727
_d12727