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課程名稱 |
腦理論
Brain Theory |
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開課學期 |
105-2 |
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授課對象 |
電機資訊學院 資訊工程學研究所 |
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授課教師 |
劉長遠 |
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課號 |
CSIE7434 |
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課程識別碼 |
922 U0100 |
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班次 |
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學分 |
3.0 |
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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 |
星期三7,8,9(14:20~17:20) |
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上課地點 |
資310 |
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備註 |
曾修類神經網路。
限學士班四年級以上 或 限碩士班以上
總人數上限：20人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1052CSIE7434_ |
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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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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
The syllabus spans the history of brain theory since its inception. Brain theory is the endeavor to understand mind (thinking, intellect) in terms of its design (how it is built, how it works). Subjects include: neurobiological modeling (Hebbian synapse and Hebbian learning; NMDA/LTE), perception, multilayer perceptron, neural networks, reinforcement leraning, self-organizing map and various associative memories. |
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課程目標 |
Brain theory is the endeavor to understand mind (thinking, intellect, 語言 視覺等) in terms of its design (how it is built, how it works). Subjects include: neurobiological modeling, pception and associative memory, computational mental process (as those by Longuet-Higgins, H.C.).
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課程要求 |
project, home assignments, exam |
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預期每週課後學習時數 |
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Office Hours |
另約時間 備註： 星期一下午 2:30pm in classroom 310 |
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指定閱讀 |
context loaded in website "http://red.csie.ntu.edu.tw/course_eng.html". |
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參考書目 |
部分參考書目如下其餘甚多資料會email給修課同學：
[1] Unsupervised Learning, H.B. Barlow, Neural Computation 1, 295-311 (1989)
[2] Finding Minimum Entropy Codes, H.B. Barlow, T.P. Kaushal, G.J. Mitchison, Neural Computation 1, 412-423(1989)
[3] Nonlinear Dimensionality reduction by locally linear embedding, Sam T. Roweis and Lawrence K. Saul, Science, vol. 290. 22 December 2000, 2323-2326
[4] The manifold ways of perception, H. Sebastian Seung and Daniel D. Lee,
Science, vol 290, 22 December, 2268-2269
[5] Minimization of Boolean complexity in human concept learning
Jacob Feldman, Nature, vol 407, 5 October 2000, 630-632
[6] Reinforcement learning: An introduction, by R.S. Sutton and A.G. Barto, 1998, MIT Press.
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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第1週 |
2/22 |
上課地點 310 教室
助教 陳仰恩 <boyenen@gmail.com>
introduction (以下進度皆為暫定 會隨時修改) |
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第2週 |
3/01 |
上課地點回到 310 教室
激素調控生成神經鍵 金絲鳥
McCulloch–Pitts neuron; perceptron; reviewing reinforcement learning |
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第3週 |
3/08 |
reinforcement learning + Hebbian learning
作業 RL, plot state space 結果 for 2 sets of random valuses in initial settings of Q V w v W_ij . |
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第4週 |
3/15 |
reinforcement learning + MPL ( NetTalk)
作業 RL, see class website.
Extended version of 作業 RL will be good for class project . |
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第5週 |
3/22 |
neocognitron + deep learning |
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第6週 |
3/29 |
pattern recognition "STD method" + deep learning
http://red.csie.ntu.edu.tw/hcr_std/usage.html
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第7週 |
4/05 |
no class 溫書假 |
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第8週 |
4/12 |
Hebbian learning + Hopfield model |
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第9週 |
4/19 |
Hopfield model + Hume conscious |
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第10週 |
4/26 |
Hopfield model + Edelman's value |
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第11週 |
5/03 |
Elman network |
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第12週 |
5/10 |
Elman network |
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第13週 |
5/17 |
self-organizing map |
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第14週 |
5/24 |
self-organizing map |
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第15週 |
5/31 |
applications |
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第16週 |
6/07 |
自習溫書 |
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第17週 |
6/14 |
寫心得報告
繳交學期報告project + 作業 |
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