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Information and System Group – Page 20 – INFONET

Laboratory life, Research

Information and System Group

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November 5, 2012

No	Date	Title	Speaker	Presentation	Discussion
1	2013-01-10	Statistical physics-based re construction in compressed sensing	Jaewook Kang	(pdf)
		In this report, the author introduces a expectation maximization (EM) based belief propagation algorithm (BP) for sparse recovery, named EM-BP. The algorithm have been mainly devised by Krzakala et al. from ParisTech in France. The properties of EM-BP are as given below:1) It is A low-computation approach to sparse recovery, 2) It works well without the prior knowledge of the signal, 3) It overcomes the l1 phase transition given by Donoho and Tanner under the noiseless setup, 4) It is further improved in conjunction with seeding matrices (or spatial coupling matrices). The main purpose of this report regenerates a precise description of EM-BP derivation from the reference paper. It might be very helpful for understanding of EM-BP algorithm, and an answer for such a question: How and why does the algorithm work ? Therefore, we will focus on the explanation of 1) and 2) in the properties, and just show the result of the paper with respect to that of 3) and 4).
2	2013-01-24	A fast approach for over-complete sparse decomposition based on smoothed L0 norm	Oliver	(PDF)	(PDF)
		This paper proposes a fast algorithm for overcomplete sparse decomposition.The algorithm is derived by directly minimizing the L0 norm after smoothening. Hence, the algorithm is named as smoothed L0 (SL0) algorithm. The authors demonstrate that their algorithm is 2-3 orders of magnitude faster than the state-of-the-art interior point solvers with same (or better) accuracy.

2012-December

No	Date	Title	Speaker	Presentation	Discussion
1	2012-12-13	Multiuser Cooperative Diversity Through Network Coding Based on Classical Coding Theory	Jintaek Seong	(pdf)
		To increase the diversity order of cooperative wireless communication systems without sacrificing the system’s rate, they propose the generalized dynamic-network code (GDNC). They showed that the problem of designing network codes that maximize the diversity order is related to that of designing optimal linear block codes, in the Hamming distance sense, over a nonbinary finite fields.

2012-November