| | Standard Course Syllabus | Course Supervisor | Date of Approval |
| | Dept. of Electrical and Computer Engineering | Moses | 2/99 |
| | 800 | Stochastic Digital Signal Processing |
| | 2. | CATALOG DESCRIPTION |
| | Signal processing techniques for stochastic signals. Vector space methods, optimal filtering and prediction, parametric and |
| | nonparametric estimation; harmonic retrieval; applications. |
| | Quarters of Offering | Credits | | Level | Class Meeting |
| | Sp Qtr (odd years). | 3 | G | 3 cl. |
| | Course Prerequisites |
| | Prereq: 700 and 805. |
| | 3. | PREREQUISITES BY TOPIC |
| | Discrete-time signal and system analysis, deterministic digital signal processing, random variables and stochastic processes |
| | Courses that require this as a direct prerequisite |
| | none |
| | 4. | Text(s) and Other Course Materials | Author(s) | Publisher |
| | Spectral Analysis of Signals, 2005 | Stoica and Moses | Prentice-Hall |
| | References (supplemental reading) |
| | [1] M Hayes, Statistical Digital Signal Processing and Modeling, Wiley, 1996. |
| | [2] S. Kay, Modern Spectral Estimation, Prentice Hall, 1988. |
| | [3] L. Marple, Digital Spectral Analysis with Applications, Prentice Hall, 1987. |
| | [4] Box and Jenkins, Time Series Analysis, Forecasting and Control, Holden-Day, 1976. |
| | [5] Chatfield, The Analysis of Time Series, Chapman-Hall, 1984. |
| | [6] D. Childers, Modern Spectrum Analysis, IEEE Press, 1978. |
| | [7] S. Kesler, Modern Spectrum Analysis II, IEEE Press, 1986. |
| | [8] Kung, Whitehouse, and Kailath, VLSI and Modern Signal Processing, Prentice-Hall, 1985. |
| | [9] D. Luenberger, Optimization by Vector Space Methods, Wiley, 1969. |
| | [10] Orfanidis, Optimum Signal Processing, Macmillan, 1985. |
| | [11] Rabiner and Gold, Digital Signal Processing, Prentice Hall, 1975. |
| | 5. | COURSE OBJECTIVES |
| | 1. Students learn concepts and techniques in stochastic signal processing. (Criterion 3(a)) |
| | 2. Students learn to design stochastic DSP algorithms to meet desired needs. (Criterion 3(c)) |
| | 3. Students apply vector space methods to stochastic signal processing problems. (Criterion 3(a)) |
| | 4. Students learn to apply stochastic DSP concepts and techniques to contemporary applications. (Criterion 3(a),(e),(j)) |
| | 5. Students learn to use computer tools (such as Matlab) in developing and testing stochastic DSP algorithms. (Criterion |
| | 3(b),(k)) |
| | 6. | TOPICS AND (# OF LECTURES) |
| | Discrete-time random processes (3) |
| | Nonparametric and parametric spectral estimation (10) |
| | Filtering and prediction (3) |
| | Harmonic retrieval (4) |
| | Contemporary applications (10) |
| | 7. | CLASS MEETING PATTERN | (For example, "3cl." means 3 48-min classes per week.) |
| | 3 cl. |
| | Thursday, August 14, 2008 09:22 AM |
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