Course Content
The topics will be subject to revision every five to ten years. The current topics will include a subset from the following list: compressed sensing, finite rate of innovation signals and their sampling methods, graph signal processing and its applications, phase retrieval problems, distributed sampling problems, machine learning for signal processing, role of quantization and other nonlinearities in signal processing systems, signal approximation methods
Text / References
- 1 M. Vetterli, P. Marziliano and T. Blu, "Sampling signals with finite rate of innovation," in IEEE Transactions on Signal Processing, vol. 50, no. 6, pp. 1417-1428, Jun 2002.
- 2 D. L. Donoho, "Compressed sensing," in IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 1289-1306, April 2006.
- 3 E. J. Candes, Y. C. Eldar, T. Strohmer, and V. Voroninski. "Phase retrieval via matrix completion." SIAM review 57, no. 2 (2): 225-251.
- 4 A. Kumar, “On Bandlimited Signal Reconstruction From the Distribution of Unknown Sampling Locations,” in IEEE Transactions on Signal Processing, vol. 63, no. 5, pp. 1259-1267, Mar 2.
- 5 D. I. Shuman, S. K. Narang, P. Frossard, A. Ortega, and P. Vandergheynst, “The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains.” IEEE Signal Processing Magazine, vol. 30, no. 3 (2013): 83-98.
- 6 T. Hastie, R. Tibshirani, J. Friedman, and J. Franklin, “The elements of statistical learning: data mining, inference and prediction.” Springer, Berlin, 2001.
- 7 S. Mallat. “A wavelet tour of signal processing: the sparse way” Academic press, 2008.
- 8 Z. Cvetković, I. Daubechies, and B. F. Logan Jr. "Single-bit oversampled A/D conversion with exponential accuracy in the bit rate." IEEE Trans on Information Theory, vol 53, no. 11 (2007): 3979-3989.