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Feedback Acquisition and Reconstruction of Spectrum-Sparse Signals by Predictive Level Comparisons
[article]
2017
arXiv
pre-print
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In this letter, we propose a sparsity promoting feedback acquisition and reconstruction scheme for sensing, encoding and subsequent reconstruction of spectrally sparse signals. ...
Utilizing the estimated spectral components, a level signal is predicted and sign measurements of the prediction error are acquired. ...
We proposed a sparsity promoting reconstruction algorithm to predict comparison levels in a feedback loop to facilitate more efficient 1-bit measurements of the input signal. ...
arXiv:1711.09658v1
fatcat:h6jcsykzz5ce5lfgkfp4gtps5a
Sparse Representation for Wireless Communications: A Compressive Sensing Approach
2018
IEEE Signal Processing Magazine
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2018 pre-print arXiv:1801.08206v1 fatcat:fgvd7rk2kraq7j5grey3th3zveOther Versions
With the help of the sparsity property, CS is able to enhance the spectrum efficiency and energy efficiency for the fifth generation (5G) networks and Internet of Things (IoT) networks. ...
collection in IoT networks, and channel estimation and feedback in massive MIMO systems. ...
[32] have proposed to reconstruct the autocorrelation of the compressed signal to provide an estimate of the signal spectrum by utilizing the sparsity property of the edge spectrum, in which the CS ...
doi:10.1109/msp.2018.2789521
fatcat:wamvxn7kebavtjroau4ksfbwea
Multitrack Compressed Sensing for Faster Hyperspectral Imaging
2021
Sensors
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Multitrack non-adaptive CS (sparse recovery) is most robust against Poisson noise at the expense of longer reconstruction times. ...
Here, we develop improved CS approaches for HSI, based on parallelized multitrack acquisition of multiple spectra per shot. ...
After the subsampling process, the original signal x is reconstructed from the measurements y by methods such as sparse recovery. ...
doi:10.3390/s21155034
fatcat:a6xtptdxsnhdlmkmmwcmpakjvy
AQuRate: MRAM-based Stochastic Oscillator for Adaptive Quantization Rate Sampling of Sparse Signals
[article]
2019
arXiv
pre-print
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However, most of these recent advances involving novel sampling techniques have been proposed without considering hardware and signal constraints. ...
Recently, the promising aspects of compressive sensing have inspired new circuit-level approaches for their efficient realization within the literature. ...
Additionally, a major challenge in spectrum sensing is that in most cases, the sparse components of the signal are spread over a wide-band spectrum and need to be acquired without prior knowledge of their ...
arXiv:1903.00971v2
fatcat:hquwlow2jfcvpmy2yscofuyq4y
Theory and Implementation of an Analog-to-Information Converter using Random Demodulation
2007
2007 IEEE International Symposium on Circuits and Systems
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The new theory of compressive sensing enables direct analog-to-information conversion of compressible signals at sub-Nyquist acquisition rates. ...
The architecture is particularly apropos for wideband signals that are sparse in the time-frequency plane. ...
The spectrum of the reconstructed AM signal is shown in Figure 5 (f). ...
doi:10.1109/iscas.2007.378360
dblp:conf/iscas/LaskaKDRBM07
fatcat:gyelwnwajbchjbypmv5jhq7o4i
Dual-modality endoscopic probe for tissue surface shape reconstruction and hyperspectral imaging enabled by deep neural networks
2018
Medical Image Analysis
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and the sparse hyperspectral signals, at approximately 2 FPS. ...
Furthermore, since data acquisition in both modes can be accomplished in one snapshot, operation of this system in clinical applications is minimally affected by tissue surface movement and deformation ...
Acknowledgements This work was funded by ERC 242991 and an Imperial College Confidence in Concept award. Jianyu Lin was supported by IGHI scholarship. ...
doi:10.1016/j.media.2018.06.004
pmid:29933116
fatcat:js3wsbruazgp3npo6tcwukgtxi
Improvement of the compression ratio of vibratory signals by double pass DWHT
2020
Indian Journal of Science and Technology
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Methods/Statistical analysis: In this work, we compress and decompress the vibration signals formed by variations of the amplitudes vibration of a ball bearing. ...
However, this bleaching of vibratory signals both in the temporal and frequency domain, followed by good quantization precision, allowed to cancel this error. ...
Premanand and Sheeba compressed vibration signals by using extremum sampling method, this method is based on level-crossing sampling (6) . ...
doi:10.17485/ijst/v13i30.924
fatcat:7hcvavun65cy3lklptioyynbhy
Compression of ECG Signal Based on Compressive Sensing and the Extraction of Significant Features
2015
International Journal of Communications, Network and System Sciences
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CS provides a new approach concerned with signal compression and recovery by exploiting the fact that ECG signal can be reconstructed by acquiring a relatively small number of samples in the "sparse" domains ...
The performance of the proposed algorithm, in terms of the reconstructed signal quality and compression ratio, is evaluated by adopting DWT spatial domain basis applied to ECG records extracted from the ...
After the acquisition process, an estimate of the signal is obtained by a reconstruction algorithm. ...
doi:10.4236/ijcns.2015.85013
fatcat:wepjh7ehaffjrgflkktuxsdgpq
An Efficient Seismic Data Acquisition Based on Compressed Sensing Architecture with Generative Adversarial Networks
2019
IEEE Access
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reduces the energy cost by means of data collection from N(N + 1)/2 to N 2 /16. ...
However, due to the bottleneck on data transmission and the limitation of energy storage, it is hard to conduct large seismic data acquisition in a real-time way. ...
Second, the main idea and structure of the reconstruction algorithm are introduced in a high-level view. ...
doi:10.1109/access.2019.2932476
fatcat:gfudguyzvncnlizzl7xnmg74sm
Compressive Sensing in Image/Video Compression: Sampling, Coding, Reconstruction, and Codec Optimization
2024
Information
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We delve into the fundamental principles of CS, highlighting its ability to efficiently capture and represent sparse signals. ...
Reconstruction algorithms play a pivotal role in CS, and this article reviews state-of-the-art methods, ensuring a high-fidelity reconstruction of visual information. ...
Acknowledgments: The authors are grateful to JSPS KAKENHI Grant Number JP22K12101 for the support of this research. ...
doi:10.3390/info15020075
fatcat:os3rimewt5agfem3hunt5mihbm
Potential of compressed sensing in quantitative MR imaging of cancer
2013
Cancer Imaging
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With custom CS acquisition and reconstruction strategies, one can quickly obtain a small subset of the full data and then iteratively reconstruct images that are consistent with the acquired data and sparse ...
We finally illustrate applications of the technique by describing examples of CS in dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI. ...
We thank Ms Donna Butler, Ms Leslie McIntosh, and Mr David Pennell for expert technical assistance.
Conflict of interest The authors declare that they have no conflicts of interest. ...
doi:10.1102/1470-7330.2013.0041
pmid:24434808
pmcid:PMC3893904
fatcat:gawyr7c575htzfhot67ywrhwxa
Neural integration and segregation revealed by a joint time-vertex connectome spectral analysis
[article]
2022
bioRxiv
pre-print
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Brain oscillations are produced by the coordinated activity of large groups of neurons and different rhythms are thought to reflect different modes of information processing. ...
Crucially, the estimated contribution of the integration and segregation mechanisms predicts performance in a behavioral task, demonstrating the neurophysiological relevance of this new framework. ...
The authors also would like to thank Mikkel Schöttner and Hugo Fluhr for their useful comments. ...
doi:10.1101/2022.07.26.501543
fatcat:sv77of6igjfztb2376omjxdnlq
A New Optimized Recurrent Feedback Deep Convolutional Neural Net for Image Super Resolution
2019
International journal of recent technology and engineering
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This new layer maintains permissible error threshold in the acquired signal and tries to improve the signal by feeding back latest reconstructed frame. ...
It can be achieved by cost effective software solution like super resolution reconstruction of an image. ...
The authors would also like to thank to their affiliated institutes for continuous technical support and guidance. ...
doi:10.35940/ijrte.c6255.098319
fatcat:apo4l5kev5bw3lhlmwollgrw2a
Compressed Sensing of Extracellular Neurophysiology Signals: A Review
2021
Frontiers in Neuroscience
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signal reconstruction algorithms. ...
We will present a comprehensive review on the CS-based neural recording system architecture, the CS encoder hardware exploration and implementation, the sparse representation of neural signals, and the ...
AUTHOR CONTRIBUTIONS Both authors contributed to manuscript planning, literature review and writing, and read and approved the submitted version. ...
doi:10.3389/fnins.2021.682063
pmid:34512238
pmcid:PMC8427310
fatcat:lgq6frhjfnhipmiziu7alrq2qu
Low-cost, sub-micron resolution, wide-field computational microscopy using opensource hardware
[article]
2018
biorxiv/medrxiv
pre-print
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. 3D models and assembly instructions of our microscope are made available for open source use. ...
Conventional approaches to low-cost microscopy are fundamentally restricted, however, to modest field of view (FOV) and/or resolution. ...
Jonathan Taylor for his feedback on the manuscript. This research was funded by Engineering and Physical Sciences Research Council (EPSRC) under the grant EP/L016753/1. ...
doi:10.1101/460055
fatcat:yolh2ssgj5eihl3d2wrapqlys4
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