一、課程說明(Course Description)
This is an advanced course of digital signal processing with special emphasis on
their biomedical applications.

二、指定用書(Text Books)
Richard Shiavi, Introduction to Applied Statistical Signal Analysis: Guide to
Biomedical and Electrical Engineering Applications, 3/e., Academic Press, 2007.

三、參考書籍(References)
1. Ali H. Sayed, “Fundamentals of Adaptive Filtering,” Wiley, 2003.
2. Todd Moon, Wynn Stirling , “Mathematical Methods and Algorithms for
Signal Processing,” Prentice Hall, 2000.
3. Monson H. Hayes, “Statistical Digital Signal Processing and Modeling,”
Wiley, 1996.
4. Simon Haykin, “Adaptive Filter Theory,” 4/e Prentice Hall 2001.
5. Simon Haykin, “Neural Networks and Learning Machines,” 3/e, Prentice
Hall, 2008.
6. Steven Kay, “Fundamentals of Statistical Signal Processing, Volume I:
Estimation Theory,” Prentice Hall, 1993.
7. Steven Kay, “Fundamentals of Statistical Signal Processing: Detection
Theory, Volume 2,” Prentice Hall, 1998.

四、教學方式(Teaching Method)
Lecture

五、教學進度(Syllabus)
Deterministic signal processing: Empirical Modeling and Approximation, Fourier
Analysis
Statistical Signal Processing: Probability Concepts and Signal Characteristics,
Random Processes and Signal Correlation, Random Signals, Linear Systems, and
Power Spectra, Spectral Analysis for Random Signals, Random Signal Modeling and
Modern Spectral Estimation, Theory and Application of Cross Correlation and
Coherence.
Other Advanced Topics (If time permitted)

六、成績考核(Evaluation)
1. Weekly homework (including computer programming): 50%
2. Midterm (Apr 11) and Final Exam (June 06): 25% + 25%