Multi-channel deep networks for block-based image compressive sensing
Incorporating deep neural networks in image compressive sensing (CS) receives intensive
attentions in multimedia technology and applications recently. As deep network approaches …
attentions in multimedia technology and applications recently. As deep network approaches …
Recognition-oriented image compressive sensing with deep learning
A number of image compressive sensing (CS) algorithms were proposed in the past two
decades, aiming at yielding recovered images with the best possible visual effect. However …
decades, aiming at yielding recovered images with the best possible visual effect. However …
A fast threshold OMP based on self-learning dictionary for propeller signal reconstruction
YC Song, FY Wu, YY Ni, K Yang - Ocean Engineering, 2023 - Elsevier
The acquisition of propeller signals can be applied to localization and fault diagnosis, etc.
However, recording a large amount of propeller signals results in higher costs. Compressive …
However, recording a large amount of propeller signals results in higher costs. Compressive …
[图书][B] Sparse optimization theory and methods
YB Zhao - 2018 - taylorfrancis.com
Seeking sparse solutions of underdetermined linear systems is required in many areas of
engineering and science such as signal and image processing. The efficient sparse …
engineering and science such as signal and image processing. The efficient sparse …
Energy-efficient mapping and scheduling for DVS enabled distributed embedded systems
MT Schmitz, BM Al-Hashimi… - Proceedings 2002 Design …, 2002 - ieeexplore.ieee.org
In this paper, we present an efficient two-step iterative synthesis approach for distributed
embedded systems containing dynamic voltage scalable processing elements (DVS-PEs) …
embedded systems containing dynamic voltage scalable processing elements (DVS-PEs) …
Compressive sensing based distributed data storage for mobile crowdsensing
Mobile crowdsensing systems typically operate centralized cloud storage management, and
the environment data sensed by the participants are usually uploaded to certain central …
the environment data sensed by the participants are usually uploaded to certain central …
Stopping criteria for distributed data storage in compressive CrowdSensing systems
X Liu, S Zhou, J Peng, W Zhang… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Distributed data storage (DDS) in mobile crowdsensing (MCS) systems has recently gained
popularity. Data should be briefly saved on participants' mobile devices before being …
popularity. Data should be briefly saved on participants' mobile devices before being …
An automatic threshold OMP algorithm based on QR decomposition for magnetic resonance image reconstruction
YY Ni, FY Wu, HZ Yang - Circuits, Systems, and Signal Processing, 2024 - Springer
In magnetic resonance (MR) image reconstruction, the orthogonal matching pursuit (OMP) is
widely recognized for its simplicity and competitive performance. However, OMP designs a …
widely recognized for its simplicity and competitive performance. However, OMP designs a …
Optimal compressive spectrum sensing based on sparsity order estimation in wideband cognitive radios
Y Luo, J Dang, Z Song - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
There are several advantages of compressive sensing (CS) technologies for spectrum
sensing in wideband cognitive radios (CRs), especially in reducing the sampling rate …
sensing in wideband cognitive radios (CRs), especially in reducing the sampling rate …
A blind stopping condition for orthogonal matching pursuit with applications to compressive sensing radar
Orthogonal matching pursuit (OMP) is a popular greedy algorithm because of its simplicity
and low computational cost. In the application of OMP, one of the most important issue is to …
and low computational cost. In the application of OMP, one of the most important issue is to …