비트 단위 사후 확률 최대화에 기반한 탐욕적 신호 복구 알고리즘

Alternative Title
Jeongmin Chae
Author(s)
채정민
Alternative Author(s)
Jeongmin Chae
Advisor
홍송남
Department
일반대학원 전자공학과
Publisher
The Graduate School, Ajou University
Publication Year
2020-02
Language
eng
Keyword
Compressive sensingsparse signal recoverysupport detection
Alternative Abstract
This dissertation proposed a novel greedy algorithm for the support recovery of a sparse signal from a small number of noisy measurements. In the proposed algorithm, a new support index is identified for each iteration based on bit-wise maximum a posteriori (B-MAP) detection. Bit-Wise MAP detection is optimal in the sense of detecting one of the remaining support indices, provided that all the detected indices in the previous iterations are correct. Despite its optimality, it requires an expensive complexity for computing the maximization metric, (i.e., a posteriori probability of each remaining support) due to the marginalization of high-dimensional sparse vectors. We address this problem by presenting a good proxy, named B-MAP proxy, on the maximization metric which is accurate enough to find the maximum index, rather than an exact probability. Moreover, it is easily evaluated only using vector correlations as in orthogonal matching pursuit (OMP), but using completely different proxy matrices for maximization. We have demonstrated that the proposed B-MAP detection provides a significant gain compared with the existing methods such as OMP and MAP-OMP while maintaining the same complexity. Subsequently, we construct an advanced greedy algorithm based on B-MAP proxy by leveraging the idea of compressive sampling matching pursuit (CoSaMP) and subspace pursuit (SP). Simulation result shows that we show that our B-MAP algorithm outperforms OMP and MAP-OMP under the frameworks of the advanced greedy algorithms.
URI
https://dspace.ajou.ac.kr/handle/2018.oak/19601
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Graduate School of Ajou University > Department of Electronic Engineering > 3. Theses(Master)
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