Compressed Sampling in Shift-Invariant Spaces Associated With FrFT
IEEE Access, 2021 Shift-invariant and sampling spaces play a vital role in the fields of signal processing and image processing. In this paper, we extend the generalized shift-invariant and sampling subspaces from the traditional sampling spaces to the compressed sampling,
Haoran Zhao, Lei Zhang, Liyan Qiao
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Endmember extraction and abundance estimation algorithm based on double-compressed sampling [PDF]
Scientific ReportsBased on double-compressed sampling, a hyperspectral spectral unmixing algorithm (SU_DCS) is proposed, which could directly complete the endmember extraction and abundance estimation.
Li Wang, Yang Bi, Wei Wang, Junfang Li
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Low-Complexity Adaptive Sampling of Block Compressed Sensing Based on Distortion Minimization
Sensors, 2022 Block compressed sensing (BCS) is suitable for image sampling and compression in resource-constrained applications. Adaptive sampling methods can effectively improve the rate-distortion performance of BCS.
Qunlin Chen, Derong Chen, Jiulu Gong
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Utilization of Compressed Sampling for PAPR Reduction in OFDM IEEE-802.11a System
Journal of Communications Software and Systems, 2021 Being spectrally efficient, easily implemented, and highly immune to selective channel imperfections and multipath fading, the Orthogonal Frequency Division Multiplexing (OFDM) can provide a sufficiently robust and high data rate modulation technique for
Hussein Al-Moukhles
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A Modulated Wideband Converter Model Based on Linear Algebra and Its Application to Fast Calibration
Sensors, 2022 In the context of cognitive radio, smart cities and Internet-of-Things, the need for advanced radio spectrum monitoring becomes crucial. However, surveillance of a wide frequency band without using extremely expensive high sampling rate devices is a ...
Gilles Burel +2 more
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Distributed Compressed Sensing of Hyperspectral Images According to Spectral Library Matching
IEEE Access, 2021 The ever-increasing resolution puts tremendous pressure to the onboard hyperspectral imaging system. Compressed sensing technology is one of the important ways to solve this problem.
Hua Xiao, Zhongliang Wang, Xueying Cui
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Leaf Classification for Crop Pests and Diseases in the Compressed Domain
Sensors, 2022 Crop pests and diseases have been the main cause of reduced food production and have seriously affected food security. Therefore, it is very urgent and important to solve the pest problem efficiently and accurately.
Jing Hua, Tuan Zhu, Jizhong Liu
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A Block-Wise random sampling approach: Compressed sensing problem [PDF]
Journal of Artificial Intelligence and Data Mining, 2015 The focus of this paper is to consider the compressed sensing problem. It is stated that the compressed sensing theory, under certain conditions, helps relax the Nyquist sampling theory and takes smaller samples. One of the important tasks in this theory
V. Abolghasemi, S. Ferdowsi, S. Sanei
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Sampling and Reconstruction Jointly Optimized Model Unfolding Network for Single-Pixel Imaging
Photonics, 2023 In recent years, extensive research has shown that deep learning-based compressed image reconstruction algorithms can achieve faster and better high-quality reconstruction for single-pixel imaging, and that reconstruction quality can be further improved ...
Qiurong Yan +4 more
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Research on LFM signal parameter estimation method based on Gabor transform to improve MWC system
AIP Advances, 2023 The “compressed sensing” theory is the foundation for the compressed sampling system’s design. In addition to the sparse representation and observation matrix, more studies in compressed sensing theory focus on signal reconstruction and recovery.
Shuo Meng, Chen Meng, Cheng Wang
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