Textbook reading seminar 2023

Channel Modeling (CM)

5/17Article 1, 2Calist1
6/14Article 3Takahashi1
6/21Article 4, 5Suzuki1
7/19Article 6Calist2
7/26Article 7Takahashi2
  • Articles (Fall, 2023)
    1. J. Gomez-Ponce, N. A. Abbasi, A. E. Willner, C. J. Zhang and A. F. Molisch, “Directionally Resolved Measurement and Modeling of THz Band Propagation Channels,” in IEEE Open Journal of Antennas and Propagation, vol. 3, pp. 663-686, 2022.
    2. S. Ju and T. S. Rappaport, “Simulating Motion – Incorporating Spatial Consistency into NYUSIM Channel Model,” 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), Chicago, IL, USA, 2018, pp. 1-6.
    3. S. Ju and T. S. Rappaport, “Millimeter-Wave Extended NYUSIM Channel Model for Spatial Consistency,” 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates, 2018.
    4. TBD
    5. TBD
    6. Z. Li, P. Wang, K. Liu and Z. Tian, “MimoLoc: Indoor Localization With Assistance of Microwave Reflection of Downlink Signal in Sub-6G MIMO Networks,” in IEEE Transactions on Microwave Theory and Techniques, doi: 10.1109/TMTT.2023.3314061.
10/25 (Wed, 5th)Article 1Takahashi3
11/10 (Fri, 4th)Article 2,3Suzuki2
11/24 (Fri, 4th)Article 4Calist3
12/13 (Wed, 5th)Article 5Suzuki3
12/20 (Wed, 5th)Article 6Koularp3

Machine Learning (ML)

  • Time: 16:25-17:55, Fri
  • Lecturers (M2/M1): Ikegami, Wako, Wang, Koularp
  • Schedule
5/31 (Wed, 5th)1: Chapter 1, Chapter 2 (ADALINE)Wang1
6/162: Chapter 3 (Logistic Regression, SVM, DT, KNN)Ikegami1
6/233: Chapter 4 (Preprocessing) Wako1
7/74: Chapter 5 (Reduction) Koularp1
7/215: Chapter 6 (Tuning) Wang2
11/10 (Fri. 5th)1: Chapter 7 (Ensemble)Ikegami2
11/22 (Wed. 5th)2: Chapter 10 (Regression)Wako2
11/24 (Fri. 5th)3: Chapter 11 (Clustering)Kourlarp2
12/15 (Fri. 5th)4: Chapter 12 (Neural Network)Wang3
12/22 (Fri. 5th)5: Chapter 12 (Neural Network)Ikegami3, Wako3 Wang3

Python 環境構築


PS> $PSVersionTable


PS> Set-ExecutionPolicy RemoteSigned -scope CurrentUser
PS> iex (new-object net.webclient).downloadstring('https://get.scoop.sh')


PS> scoop install git


PS> scoop bucket add extras
PS> scoop install anaconda3


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