Results 1 to 10 of about 2,960,959 (361)
A Deterministic Construction of Projection matrix for Adaptive Trajectory Compression [PDF]
arXiv, 2013 Compressive Sensing, which offers exact reconstruction of sparse signal from a small number of measurements, has tremendous potential for trajectory compression. In order to optimize the compression, trajectory compression algorithms need to adapt compression ratio subject to the compressibility of the trajectory.
arxiv
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012 In this paper we present a novel compressed sensing (CS) algorithm for the recovery of compressible, possibly time-varying, signal from a sequence of noisy observations. The newly derived scheme is based on the acclaimed unscented Kalman filter (UKF), and is essentially self reliant in the sense that no peripheral optimization or CS algorithm is ...
Carmi, Avishy Y. +2 more
openaire +3 more sources
Adaptive Beamforming Based on Compressed Sensing with Smoothed l0 Norm
International Journal of Antennas and Propagation, 2015 An adaptive beamforming based on compressed sensing with smoothed l0 norm for large-scale sparse receiving array is proposed in this paper. Because of the spatial sparsity of the arriving signal, compressed sensing is applied to sample received signals ...
Yubing Han, Jian Wang
doaj +1 more source
Image Compression Based on Compressive Sensing: End-to-End Comparison with JPEG [PDF]
IEEE Transactions on Multimedia 2020, 2017 We present an end-to-end image compression system based on compressive sensing. The presented system integrates the conventional scheme of compressive sampling and reconstruction with quantization and entropy coding. The compression performance, in terms of decoded image quality versus data rate, is shown to be comparable with JPEG and significantly ...
arxiv
Implementation of a Cross-Layer Sensing Medium-Access Control Scheme
Sensors, 2017 In this paper, compressed sensing (CS) theory is utilized in a medium-access control (MAC) scheme for wireless sensor networks (WSNs). We propose a new, cross-layer compressed sensing medium-access control (CL CS-MAC) scheme, combining the physical layer
Yishan Su +4 more
doaj +1 more source
A Cooperative Spectrum Sensing Scheme Based on Compressive Sensing for Cognitive Radio Networks [PDF]
International Journal of Digital Information and Wireless
Communications (IJDIWC), ISSN: 2225-658X (Online); ISSN 2412-6551, 2019, 2019 In this paper, a cooperative spectrum sensing scheme based on compressive sensing is proposed. In this scheme, secondary users (SUs) are organized in clusters. In each cluster, SUs forward their compressed signals to the cluster head. Then, the cluster heads report the local sensing data to the fusion center to make the final decision.
arxiv
Compressed Sensing and Redundant Dictionaries [PDF]
, 2008 Holger Rauhut +2 more
openalex +1 more source
Near-Optimal Adaptive Compressed Sensing [PDF]
arXiv, 2013 This paper proposes a simple adaptive sensing and group testing algorithm for sparse signal recovery. The algorithm, termed Compressive Adaptive Sense and Search (CASS), is shown to be near-optimal in that it succeeds at the lowest possible signal-to-noise-ratio (SNR) levels, improving on previous work in adaptive compressed sensing.
arxiv
Compressed sensing over the Grassmann manifold: A unified analytical framework [PDF]
, 2008 Weiyu Xu, Babak Hassibi
openalex +1 more source
Sparsification of Matrices and Compressed Sensing [PDF]
arXiv, 2015 Compressed sensing is a signal processing technique whereby the limits imposed by the Shannon--Nyquist theorem can be exceeded provided certain conditions are imposed on the signal. Such conditions occur in many real-world scenarios, and compressed sensing has emerging applications in medical imaging, big data, and statistics.
arxiv