隨機過程
Stochastic Processes
| 節 | 週一 |
|---|---|
5 13:20–14:10 | 隨機過程 ED219（光復） 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
Teach students key results (with proof) on stochastic processes and their applications in communication systems and signal processing.
Calculus, probability, signals and systems
無備註
教師未提供此項資料
Homework (includes computer programming) and class participation: 20% 1 Midterm Exam: 40% 1 Final Exam: 40%.
Chapter 9: General Concepts
9-1. Introduction, Autocorrelation 9-2. Systems with Stochastic Inputs 9-3. The Power Spectrum 9-4. Discrete-Time Stochastic Processes
Chapter 10: Random Walks and Other Applications
10-1. Random Walks and Brownian Motion
Chapter 11: Spectral Representation
11-1. Regular Processes, Factorization and Innovation 11-2. AR, MA, and ARMA processes 11-3.. Fourier Series and Karhunen-Loeve Expansions 11-4. Wold Decomposition
Chapter 12: Spectrum Estimation
12-1. Ergodicity 12-2. Spectrum Estimation (Data/Spectral Windows) 12-3. Lattice Filter, Levinson's Algorithm, System Identification of AR/MA/ARMA Processes
Chapter 13: Mean Square Estimation
13-1. Introduction, Orthogonality Principle 13-2. Prediction, Wiener-Hopf Equation, Proof of Wold Decomposition 13-3. Prediction and Filtering
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to Stochastic Processes (9-1) Note: After enrolling in the course, you will be able to download the lecture video file and slides from the E3 website. |
| 第 2 週 | Systems with Stochastic Inputs (9-2) Note: After enrolling in the course, you will be able to download the lecture video file and slides from the E3 website. |
| 第 3 週 | The Power Spectrum (9-3) |
| 第 4 週 | Discrete-Time Stochastic Processes (9-4) |
| 第 5 週 | Regular Processes Factorization and Innovations (11-1) |
| 第 6 週 | AR, MA, and ARMA processes (11-2) |
| 第 7 週 | AR, MA, and ARMA processes (11-2) |
| 第 8 週 | Fourier series and Karhunen-Loeve expansions (11-3) Random Walks, Wiener Process, and Brownian Motion (10-1) |
| 第 9 週 | Midterm Exam |
| 第 10 週 | Spectral representation of random processes, Wold Decomposition (11-4) |
| 第 11 週 | Ergodicity (12-1) |
| 第 12 週 | Mean Square Estimation and Orthogonality Principle (13-1) |
| 第 13 週 | Prediction, Solving Wiener-Hopf Equation for Regular Processes (13-2) |
| 第 14 週 | Prediction and Filtering (13-3) |
| 第 15 週 | Spectrum Estimation (12-2) System Identification of AR/MA/ARMA Processes (12-3) |
| 第 17 週 | Lattice Filters and Levinson's Algorithm (12-3) |
| 第 18 週 | Final Exam |
Probability, Random Variables and Stochastic Processes, 4th edition, Athanasios Papoulis and S. Unnikrishna Pillai, Mc Graw Hill, 2002.
- 地點
- ED730
- 時間
- 2EF
- 聯絡方式
- runghunggau@g2.nctu.edu.tw