IMAT

Papers

The following papers are published so far on IMAT and its applications in different domains:

1. Farokh Marvasti et al., "Sparse signal processing using iterative method with adaptive thresholding (IMAT), " 19th International Conference on Telecommunications (ICT 2012), pp. 1-6, April 2012. [PDF]
2. Farokh Marvasti et al., "A Unified Approach to Sparse Signal Processing, " EURASIP Journal on Advances in Signal Processing, 2012. [PDF]
3. M. Azghani, F. Marvasti, "Iterative Methods for Random Sampling and Compressed Sensing Recovery, " 10th International Conference on Sampling Theory and Applications (SAMPTA 2013), July 2013. [PDF]
4. A. Zandieh, A. Zareian, M. Azghani, and F. Marvasti, "Reconstruction of Sub-Nyquist Random Sampling for Sparse and Multi-Band Signals," Submitted to IEEE Transactions on Signal Processing, November 2014. [PDF]
5. M. Boloursaz, N. Salarieh, E. Shahrabi Farahani, and F. Marvasti, "Sparse Signal Reconstruction for Asynchronous Level Crossing A/Ds using the Iterative Method with Adaptive Thresholding (IMAT)," Submitted to IEEE Transactions on Instrumentation and Measurement, July 2016.
6. Masoumeh Azghani, Panagiotis Kosmas, and Farokh Marvasti, "Microwave Medical Imaging Based on Sparsity and an Iterative Method With Adaptive Thresholding," IEEE Transactions on Medical Imaging, vol. 34, no. 2, pp. 357-365. [PDF]
7. H. Zamani, H. Zayyani, and F. Marvasti, "An Iterative Dictionary Learning-based algorithm For DOA Estimation," IEEE Communications Letters, July, 2016. [PDF]
8. Ashkan Esmaeili, Ehsan Asadi, and Farokh Marvasti, "Iterative Null-space Projection Method of Adaptive Thresholding in Sparse Signal Recovery and Matrix Completion". [PDF]
9. A. Taimori, F. Marvasti, "Measurement-Adaptive Sparse Image Sampling and Recovery," Submitted to IEEE Transactions on Computational Imaging, 2017. [PDF]

Downloads

The following Codes illustrate IMAT performance in various applications:

1. Basic IMAT Algorithm for sparse image reconstruction from missing samples, by M. Boloursaz.
2. IMAT algorithm for random sampling recovery of sparse signals, by M. Azghani..
3. IMATI Algorithm for random sampling recovery of sparse signals.
4. IMATCS Algorithm for Compressed Sensing recovery of sparse signals.
5. Performance comparison between IMAT, OMP, LASSO, and Iterative algorithms for voice reconstruction from Level Crossing (LC) samples.
6. Application of IMAT for high resolution spectrum estimation in heart rate tracking from PPG signals. These codes ranked 8'th in the second ICASSP Signal Processing Cup!
7. Application of IMATGI in Sparsity Promoting Interpolation of Signals Defined on Graphs.
8. INPMAT algorithm.
9. Measurement-Adaptive Sampling Cellular Automaton Recovery (MASCAR) Algorithm.

Courses

Acknowledgements

Prof. F. Marvasti

ACRI Director

Dr. A. Amini

ACRI Member

Dr. M. Azghani

ACRI Member

Students:

• M. Boloursaz, PHD Candidate
• A. Zareian, BSc Student
• A. Zandieh, BSc Student

Former Contributors:

• R. Eghbali
• M. Soltanolkotabi
• A. Kazerooni
• A. Rashidinejad

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