Journal of Telecommunications and Information Technology, nr 4

kwartalni

Faculty of Engineering and Design. Research Review

STUDENTS AND ACADEMICS - This publication introduces you to the department or school and then each faculty member’s research areas, research applications, and their most recent activities. A comprehensive index can be found at the back of this publication to help guide you by specific areas of interest, as well as point out interdisciplinary topics and researchers. INDUSTRY LEADERS - This publication includes information regarding specific facilities, labs, and research areas of departments and schools as well as individual faculty members and researchers. A comprehensive index can be found at the back of this publication to help guide you by specific areas of interest, as well as point out interdisciplinary topics and researchers

2008-2009

Contains information on courses and class descriptions as well as campus resources at Collin College.https://digitalcommons.collin.edu/catalogs/1020/thumbnail.jp

2011-2012

Contains information on courses and class descriptions as well as campus resources at Collin College.https://digitalcommons.collin.edu/catalogs/1023/thumbnail.jp

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

2006-2007

Contains information on courses and class descriptions as well as campus resources at Collin College.https://digitalcommons.collin.edu/catalogs/1018/thumbnail.jp

2007-2008

Contains information on courses and class descriptions as well as campus resources at Collin College.https://digitalcommons.collin.edu/catalogs/1019/thumbnail.jp

2010-2011

Contains information on courses and class descriptions as well as campus resources at Collin College.https://digitalcommons.collin.edu/catalogs/1022/thumbnail.jp