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[1]
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Anomaly Detection Based on Discrete Wavelet Transformation for Insider Threat Classification
Computer Systems Science and Engineering,
2023
DOI:10.32604/csse.2023.034589
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[2]
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An Efficient Spectrum Sensing Model In Cognitive Radio Network Using Compressive Sensing And Interference Temperature Model
2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC),
2022
DOI:10.1109/IIHC55949.2022.10060442
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[3]
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Image Compression Techniques in Wireless Sensor Networks: A Survey and Comparison
IEEE Access,
2022
DOI:10.1109/ACCESS.2022.3195891
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[4]
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Convex Optimization Algorithms for Sparse Signal Reconstruction
2020 9th Mediterranean Conference on Embedded Computing (MECO),
2020
DOI:10.1109/MECO49872.2020.9134243
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[5]
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Anomaly Detection in Edge Nodes using Sparsity Profile
2020 IEEE International Conference on Big Data (Big Data),
2020
DOI:10.1109/BigData50022.2020.9377757
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[6]
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Understanding Bit-Error Trade-off of Transform-based Lossy Compression on Electrocardiogram Signals
2020 IEEE International Conference on Big Data (Big Data),
2020
DOI:10.1109/BigData50022.2020.9378343
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[7]
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Sparse Signal Recovery Through Regularized Orthogonal Matching Pursuit for WSNs Applications
2019 6th International Conference on Signal Processing and Integrated Networks (SPIN),
2019
DOI:10.1109/SPIN.2019.8711716
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[8]
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Performance comparison of sparsifying basis functions for compressive speech enhancement
International Journal of Speech Technology,
2019
DOI:10.1007/s10772-019-09622-9
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[9]
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Chebyshev Vandermonde-like Measurement Matrix Based Compressive Spectrum Sensing
2019 IEEE International Conference on Electro Information Technology (EIT),
2019
DOI:10.1109/EIT.2019.8834261
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[10]
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Efficient Data Collection and Accurate Travel Time Estimation in a Connected Vehicle Environment Via Real-Time Compressive Sensing
Journal of Big Data Analytics in Transportation,
2019
DOI:10.1007/s42421-019-00009-5
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[11]
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New Bernoulli And Gaussian Sensing Matrices For Cluster Structured Sparse Signals
2019 IEEE Wireless Communications and Networking Conference (WCNC),
2019
DOI:10.1109/WCNC.2019.8885798
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[12]
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AD2: Improving Quality of IoT Data through Compressive Anomaly Detection
2019 IEEE International Conference on Big Data (Big Data),
2019
DOI:10.1109/BigData47090.2019.9005533
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[13]
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Blind Compressive Sensing forCooperative Cognitive Radio with Semi-Orthognal Regular Parity Check Matrix and l2-Minimization
2019 International Conference on Information and Communications Technology (ICOIACT),
2019
DOI:10.1109/ICOIACT46704.2019.8938517
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[14]
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A performance comparison of measurement matrices in compressive sensing
International Journal of Communication Systems,
2018
DOI:10.1002/dac.3576
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[15]
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On the measurement uncertainties of THz imaging systems based on compressive sampling
Measurement,
2018
DOI:10.1016/j.measurement.2017.10.030
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[16]
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A performance comparison of measurement matrices in compressive sensing
International Journal of Communication Systems,
2018
DOI:10.1002/dac.3576
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[17]
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Detection Efficiency of Signal with Unknown Non-Power Parameter Using Algorithms Based on the Compressive Sensing Theory
Radioelectronics and Communications Systems,
2018
DOI:10.3103/S0735272718080046
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[18]
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A Bat-Inspired Sparse Recovery Algorithm for Compressed Sensing
Computational Intelligence and Neuroscience,
2018
DOI:10.1155/2018/1365747
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[19]
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Measurement Matrix for Sparse Internet Data based Compressive Sampling
2018 22nd International Computer Science and Engineering Conference (ICSEC),
2018
DOI:10.1109/ICSEC.2018.8712812
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[20]
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Designing manufacturable filters for a 16-band plenoptic camera using differential evolution
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII,
2017
DOI:10.1117/12.2262574
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[21]
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Understanding the impact of lossy compressions on IoT smart farm analytics
2017 IEEE International Conference on Big Data (Big Data),
2017
DOI:10.1109/BigData.2017.8258504
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[22]
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Sub-Nyquist wideband spectrum sensing based on random demodulation in cognitive radio
2017 12th International Conference on Computer Engineering and Systems (ICCES),
2017
DOI:10.1109/ICCES.2017.8275398
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[23]
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Selecting an Optimized COTS Filter Set for Multispectral Plenoptic Sensing
2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),
2017
DOI:10.1109/CVPRW.2017.42
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[24]
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Lossy compression on IoT big data by exploiting spatiotemporal correlation
2017 IEEE High Performance Extreme Computing Conference (HPEC),
2017
DOI:10.1109/HPEC.2017.8091030
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[25]
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New constructions of Bernoulli and Gaussian sensing matrices for compressive sensing
2017 International Conference on Wireless Networks and Mobile Communications (WINCOM),
2017
DOI:10.1109/WINCOM.2017.8238160
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