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課程名稱 |
網路科學
Network Science |
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開課學期 |
102-2 |
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授課對象 |
電機資訊學院 電信工程學研究所 |
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授課教師 |
陳光禎 |
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課號 |
CommE5042 |
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課程識別碼 |
942EU0560 |
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班次 |
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學分 |
3 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期四2,3,4(9:10~12:10) |
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上課地點 |
博理114 |
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備註 |
總人數上限：60人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1022CommE5042_ |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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課程概述 |
1.Introduction to Networks
a)Technological networks such as Internet, communication networks, power grids, transportation networks, etc.
b)Information networks such as WWW, citations, etc.
c)Social networks and data mining
d)Biological networks
2.Introduction to Probability and Random Processes
3.Introduction to Mathematical Statistics
4.Random Graphs
5.Statistical Analysis of Networks
6.Models of Networks
a)ER Networks
b)Power Laws and Scale-free Networks
c)Small-World Networks
d)Random Geometry Graphs
e)Network Information Theory
7.Dynamics of Networks
a)Percolation
b)Search and Navigation
c)Epidemics
d)Information Cascading
e)Evolution of Networks and Graphs
f)Temporal Networks
8.Wireless Networks
a)Stochastic Geometry and Interference Analysis
b)Cognitive Radio Networks
c)Large Ad Hoc Networks
9.Social Networks
a)Community
b)Decision on Networks
c)Inference on Networked Data
d)Interaction Networks and Opinion Dynamics
e)Social Learning and Systems
10.E-Commerce and Economy
a)Voting and Consensus
b)Influence and Recommender Systems
c)Collective Behaviors and Intelligence
d)Game Theory over Networks
e)Market, Management, and Information
11.Biological Networks
a)System Biology
b)Ecology and Population Dynamics
c)Application to Wireless Communication Networks |
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課程目標 |
Although related research existed long time ago, network science has emerged as a major interdisciplinary science and technology since the pioneer papers published in Nature and Science in 1998-9. Based on mathematics (probability and statistics, random graphs) and statistical physics, network science has been proven to be useful in technological networks (e.g. Internet and the series of wireless networking papers in the IEEE journals), molecular/system biology, biochemical reactions, biology, ecology, multi-agent interaction networks, networked data analysis/mining, social networks, social systems and dynamics, network security and privacy, cyber-physical systems (e.g. smart electricity grids), epidemics, and economy.
This multi-disciplinary course intends to orient fundamental knowledge and applications of network science, and to facilitate students’ capability in the information society. The prerequisite of this course is Probability (undergraduate level after Calculus). However, the class note is self-contained to provide necessary background knowledge.
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課程要求 |
Grading
Homework 40%
Examination 30%
Term-Project 30%
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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參考書目 |
Textbook： Class note by instructor (draft manuscript of a book to be published)
Reference： [1] M.E.J. Newman, Networks: An Introduction, Oxford University Press, 2010.
[2] D. Easley, J. Kleinberg, Networks, Crowds, and Markets, Cambridge University Press, 2010.
[3] M. Newman, A.-L. Barabasi, D.J. Watts, The Structure and Dynamics of Networks, Princeton University Press, 2006.
[4] M.O. Jackson, Social and Economic Networks, Princeton University Press, 2010.
[5] J.D. Murry, Mathematical Biology, Vol. I An Introduction, 3rd ed., Springer, 2012.
[6] K.C. Chen, R. Prasad, Cognitive Radio Networks, Wiley, 2009.
[7] K.C. Chen, M. Chiang, H.V. Poor, “From Technological Networks to Social Networks”, IEEE Journal on Selected Areas in Communications, vol. 31, no. 9, pp. 548-572, September 2013.
Papers from Nature, Science, Cell, Physical Reviews Letters, Review of Modern Physics, SIAM Reviews, Physics Reports, Social Networks, Review of Economic Studies, Game and Economic Behavior, Nature Genetics, Proceeding of National Academy of Science, and IEEE and ACM journals.
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評量方式
(僅供參考) |
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