| 課程編碼 Course Code | 中文課程名稱 Course Name (Chinese) | 英文課程名稱 Course Name (English) | 總學分數 Credits | 總時數 Hours |
|---|---|---|---|---|
| 3105152 | 資訊理論 | Information Theory | 3.0 | 3 |
| 中文概述 Chinese Description | 本課程將先從隨機變數的內容開始並主要介紹消息理論的基礎與應用。本課程的將涵蓋下列內容： (1) 熵值，相對性熵值與互訊息 (2) 漸近等分理論 (3) 隨機程序的熵速率 (4) 資料壓縮 (5) 消息理論與賭博 (6) 頻道容量 (7) 差別熵值 (8) 高斯通道 | |||
| 英文概述 English Description | This class starts from the review of random process and mainly provides an introduction to information theory. The following is a rough description of the material covered in this class. (1) Entropy, Relative Entropy, and Mutual information (2) Asymptotic equipartition theorem (3) Entropy rates of stochastic processes (4) Data compression (Huffman coding, Shannon codes, Kraft inequality, etc.) (5) Information theory and gambling (6) Channel Capacity (7) Differential entropy (8) Gaussian Channels | |||
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