Textbook reading seminar 2021
Zoom Meeting
- CM https://zoom.us/j/95100622133 (14:40, Wed)
- ML https://zoom.us/j/95330856753 (16:25, Fri)
- A group: Kumakura, Tsukada, Calist + B4
- B group: Miyake, Zhou, Pula, Li + B4
Channel Modeling (CM)
- 電気電子工学文献詳読I(M1)・II(M2)
- Textbook (Articles)
- 移動通信のチャネルモデルの進化について——第1 世代から第5 世代 のモデル——, 電子情報通信学会論文誌B Vol. J102–B No. 11 pp. 731–740, 2019.
- Channel modeling in the next generation mmWave Wi-Fi: IEEE 802.11ay standard, EuMW 2016
- QuaDRiGa: A 3-D Multi-Cell Channel Model With Time Evolution for Enabling Virtual Field Trials, IEEE Trans. Antennas Propag., Vol. 62, No. 6, June 2014.
- https://quadriga-channel-model.de/
- Semi-Deterministic Dynamic Millimeter-wave Channel Modeling Based on an Optimal Neural Network Approach, under review IEEE TAP
- Map-Based Channel Model for Evaluation of 5G Wireless Communication Systems, IEEE Trans. Antennas Propag., Vol.65, No.12, Dec. 2017.
- NIST Q-D Model, https://github.com/usnistgov/qd-realization/tree/master/docs
- S. Priebe, C. Jastrow, M. Jacob, T. Kleine-Ostmann, T. Schrader and T. Kürner, “Channel and Propagation Measurements at 300 GHz,” in IEEE Transactions on Antennas and Propagation, vol. 59, no. 5, pp. 1688-1698, May 2011, doi: 10.1109/TAP.2011.2122294.
- Y. -G. Lim, Y. J. Cho, M. S. Sim, Y. Kim, C. -B. Chae and R. A. Valenzuela, “Map-Based Millimeter-Wave Channel Models: An Overview, Data for B5G Evaluation and Machine Learning,” in IEEE Wireless Communications, vol. 27, no. 4, pp. 54-62, August 2020, doi: 10.1109/MWC.001.1900315.
- M. Lecci et al., “Quasi-Deterministic Channel Model for mmWaves: Mathematical Formalization and Validation,” GLOBECOM 2020 – 2020 IEEE Global Communications Conference, 2020, pp. 1-6, doi: 10.1109/GLOBECOM42002.2020.9322374.
- R. Sun and P. B. Papazian, “Time Stability of Untethered Electronic Switched MIMO Millimeter-Wave Channel Sounders,” in IEEE Access, vol. 8, pp. 21052-21062, 2020, doi: 10.1109/ACCESS.2020.2968355.
Date | Topic | Charge | On-site Attendee |
---|---|---|---|
6/2 | 1: Article 1 | Kumakura | A group |
6/9 | 2: Article 2 | Tsukada | A group |
6/23 | 3: Article 5 (1/2) | Kim | A group |
6/30 | 4: Article 5 (2/2) | Calist | A group |
7/7 | 5: Article 6 (1/2) | Kim | A group |
7/14 | 6: Article 7 (1/2) | Tsukada | A group |
7/21 | 7: Article 7 (2/2) | Kumakura | A group |
11/17 | 1: Article 11 | Kumakura | A group |
11/24 | 2: Article 10 | Tsukada | A group |
12/1 | 3: Article 9 | Calist | A group |
12/15 | 4: Article 8 | Takahashi, Suzuki | A group |
Machine Learning (ML)
- 電気電子工学文献詳読I(M1)・II(M2)
- Textbook (Articles)
- Time: 16:25-17:55, Fri
- Lecturers (M2/M1): Miyake, Zhou, Calist, Pula, Li
- Members (B4):
- Schedule
Date | Topic | Charge | On-site Attendee |
---|---|---|---|
6/4 | 1: Chapter 1, Chapter 2 (ADALINE) | Zhou | B group |
6/11 | 2: Chapter 3 (Logistic Regression, SVM, DT, KNN) | Miyake | B group |
6/18 | 3: Chapter 3 (SVM) | Pula | B group |
7/2 | 4: Chapter 3 (DT, KNN ) | Li | B group |
7/16 | 5: Chapter 4 (Preprocessing) | Zhou | B group |
8/6 | 6: Chapter 5 (Reduction) | Pula | B group |
11/19 | 1: Chapter 6 (Tuning) | Miyake | B group |
12/3 | 2: Chapter 7 (Ensemble) | Zhou | B group |
12/17 | 3: Chapter 10 (Regression) | Li | B group |
12/22 (Wed, 4th) | 4: Chapter 11 (Clustering) | Pula | B group |
12/24 | 5: Chapter 12 (Neural Network) | Wako, Ikegami, Kuwano | B group |
Python 環境構築
既にgitとかpythonをインストール済みの人がやると面倒なことになるかもしれないので気をつけてください.
パワーシェルを立ち上げてPSVersionを確認する.
PS> $PSVersionTable
PSVersionが5.0以上だったらScoopをインストールする.(PSVersionが5.0未満だったらパワーシェルの最新版をインストールしてから行うこと.)
PS> Set-ExecutionPolicy RemoteSigned -scope CurrentUser
PS> iex (new-object net.webclient).downloadstring('https://get.scoop.sh')
成功したら,gitのインストール
PS> scoop install git
次に,Pythonのインストール(Anacondaを使用)
PS> scoop bucket add extras
PS> scoop install anaconda3
最後に任意のディレクトリに教科書のソースコードをクローン
PS> mkdir Work # 任意のディレクトリ作成(不必要なら無視)
PS> cd Work # 任意のディレクトリに移動
PS> git clone https://github.com/rasbt/python-machine-learning-book.git # クローン
エラーとか出たら聞いてください.環境構築まだの人は↑を参考に各自やっておいてください.
・pythonがつかえる
・ソースコードをダウンロード(クローン)済み
になっている人はOKです.あと教科書(日本語版(第1版))は,「\\133.35.167.28\kimlab\users\lab\勉強会資料\ML\教科書」に置いたので各自見てください.
一応,自分で使う目的以外には使用しないでください.