We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Forward-backward pursuit method for distributed compressed sensing.
- Authors
Zhang, Yujie; Qi, Rui; Zeng, Yanni
- Abstract
In this paper, a forward-backward pursuit method for distributed compressed sensing (DCSFBP) is proposed. In contrast to existing distributed compressed sensing (DCS), it is an adaptive iterative approach where each iteration consists of consecutive forward selection and backward removal stages. And it not needs sparsity as prior knowledge and multiple indices are identified at each iteration for recovery. These make it a potential candidate for many practical applications, when the sparsity of signals is not available. Numerical experiments, including recovery of random sparse signals with different nonzero coefficient distributions in many scenarios, in addition to the recovery of sparse image and the real-life electrocardiography (ECG) data, are conducted to demonstrate the validity and high performance of the proposed algorithm, as compared to other existing DCS algorithms.
- Subjects
COMPRESSED sensing; SIGNAL sampling; IRREGULAR sampling (Signal processing); ELECTROCARDIOGRAPHY; ELECTRODIAGNOSIS
- Publication
Multimedia Tools & Applications, 2017, Vol 76, Issue 20, p20587
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-016-3968-z