Search Results - Sparse network coding

When Multipath QUIC Meets Model Predictive Control and Band Sparse Network Coding: A Novel Multipathing Solution for Video Streaming Over Heterogeneous Wireless Networks

Authors: Yuanlong Cao Haopeng Zhang Ming Jiang et al.

Source: IEEE Transactions on Broadcasting. 71:756-773

Research on robustness maintenance for sparse network coding based mobile edge caching network

Authors: YIN Jun XIA Xinran ZHANG Dengyin et al.

Source: 物联网学报, Vol 9, Pp 214-222 (2025)

Subject Terms: T58.6-58.62, network coding, robustness, Information technology, Management information systems, MEC network, recovery algorithm, T58.5-58.64

Access URL: https://doaj.org/article/ae401c9e7ec4451986538914369ce73c

Bison: A Binary Sparse Network Coding Based Contents Sharing Scheme for D2D-Enabled Mobile Edge Caching Network

Authors: Cheng Peng Jun Yin Lei Wang et al.

Source: IEEE Transactions on Mobile Computing. 24:677-695

Sparse coding generates efficient representations for autoassociative memories

Authors: Zhao, Yazhou Yun, Zeyu Olshausen, Bruno et al.

Source: Proceedings of the Annual Meeting of the Cognitive Science Society. 47

Subject Terms: Memory, Computational neuroscience, Neural Networks

File Description: application/pdf

Access URL: https://escholarship.org/uc/item/5zm5g496
https://escholarship.org/content/qt5zm5g496/qt5zm5g496.pdf

An Analytical Model for Rank Distribution in Sparse Network Coding

Authors: Hadi Sehat Peyman Pahlevani

Source: Sehat, H & Pahlevani, P 2019, 'An Analytical Model for Rank Distribution in Sparse Network Coding', IEEE Communications Letters, vol. 23, no. 4, 8631177, pp. 556-559. https://doi.org/10.1109/LCOMM.2019.2896626

Subject Terms: 0203 mechanical engineering, Sparse random linear network coding, 0202 electrical engineering, electronic engineering, information engineering, network coding, 02 engineering and technology, rank of sparse matrix

Access URL: https://vbn.aau.dk/da/publications/62b35d1b-c9f5-4be0-9a8d-a97f2c2d6b22
http://www.scopus.com/inward/record.url?scp=85064561773&partnerID=8YFLogxK
https://doi.org/10.1109/LCOMM.2019.2896626
https://ieeexplore.ieee.org/document/8631177
https://dblp.uni-trier.de/db/journals/icl/icl23.html#SehatP19

Selectivity and robustness of sparse coding networks.

Authors: Paiton, Dylan Frye, Charles Lundquist, Sheng et al.

Source: Journal of Vision. 20(12)

Subject Terms: Humans, Models, Neurological, Neural Networks, Computer, Neurons, Nonlinear Dynamics, Stochastic Processes, Unsupervised Machine Learning, Visual Perception

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Access URL: https://escholarship.org/uc/item/434161bb
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On the Partial Decoding Delay of Sparse Network Coding

Authors: Amir Zarei Peyman Pahlevani Mansoor Davoodi

Source: Zarei, A, Pahlevani, P & Davoodi, M 2018, 'On the Partial Decoding Delay of Sparse Network Coding', IEEE Communications Letters, vol. 22, no. 8, 8364597, pp. 1668-1671. https://doi.org/10.1109/LCOMM.2018.2840139

Subject Terms: Markov chain model, Random linear network coding, sparse network coding, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Access URL: https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/11250/2652879/4/Zarei.pdf
https://vbn.aau.dk/da/publications/3a0723ff-22fd-483c-81d6-8c74c2626552
http://www.scopus.com/inward/record.url?scp=85047630540&partnerID=8YFLogxK
https://doi.org/10.1109/LCOMM.2018.2840139
https://ieeexplore.ieee.org/document/8364597
http://ieeexplore.ieee.org/document/8364597
https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/2652879
http://dblp.uni-trier.de/db/journals/icl/icl22.html#ZareiPD18
https://dblp.uni-trier.de/db/journals/icl/icl22.html#ZareiPD18

Performance and complexity of tunable sparse network coding with gradual growing tuning functions over wireless networks

Authors: Garrido, Pablo Sørensen, Chres Wiant Roetter, Daniel Enrique Lucani et al.

Contributors: Garrido, Pablo Sørensen, Chres Wiant Roetter, Daniel Enrique Lucani et al.

Source: IEEE 27th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2016, Valencia, 2145-2150
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)
Garrido, P, Sørensen, C W, Roetter, D E L & Aguero, R 2016, Performance and Complexity of Tunable Sparse Network Coding with Gradual Growing Tuning Functions over Wireless Networks. in Personal, Indoor, and Mobile Radio Communications (PIMRC), 2016 IEEE 27th Annual International Symposium on. IEEE (Institute of Electrical and Electronics Engineers), I E E E International Symposium Personal, Indoor and Mobile Radio Communications, IEEE 27th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications-(PIMRC), Valencia, Spain, 04/09/2016. https://doi.org/10.1109/PIMRC.2016.7794915
Garrido, P, Sørensen, C W, Roetter, D E L & Aguero, R 2016, Performance and Complexity of Tunable Sparse Network Coding with Gradual Growing Tuning Functions over Wireless Networks . in Personal, Indoor, and Mobile Radio Communications (PIMRC), 2016 IEEE 27th Annual International Symposium on . IEEE (Institute of Electrical and Electronics Engineers), I E E E International Symposium Personal, Indoor and Mobile Radio Communications, IEEE 27th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications-(PIMRC), Valencia, Spain, 04/09/2016 . https://doi.org/10.1109/PIMRC.2016.7794915

Subject Terms: Sparse Matrices, Wireless Networks, 0203 mechanical engineering, TSNC, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Random Linear Coding, Simulation

Access URL: https://repositorio.unican.es/xmlui/bitstream/10902/11189/1/PerformanceandComplexityofTunable.pdf
http://hdl.handle.net/10902/11189
http://ieeexplore.ieee.org/document/7794915/
https://dblp.uni-trier.de/db/conf/pimrc/pimrc2016.html#GarridoSLA16
http://vbn.aau.dk/da/publications/performance-and-complexity-of-tunable-sparse-network-coding-with-gradual-growing-tuning-functions-over-wireless-networks(72032b0d-d431-4353-9a99-fd6fba267538).html
https://vbn.aau.dk/da/publications/performance-and-complexity-of-tunable-sparse-network-coding-with-gradual-growing-tuning-functions-over-wireless-networks(72032b0d-d431-4353-9a99-fd6fba267538).html
http://dblp.uni-trier.de/db/conf/pimrc/pimrc2016.html#GarridoSLA16
https://repositorio.unican.es/xmlui/bitstream/10902/11189/1/PerformanceandComplexityofTunable.pdf

Markov Chain Model for the Decoding Probability of Sparse Network Coding

Authors: Garrido Ortiz, Pablo Lucani, Daniel E. Agüero Calvo, Ramón et al.

Contributors: Garrido Ortiz, Pablo Lucani, Daniel E. Agüero Calvo, Ramón et al.

Source: IEEE Transactions on Communications, 2017, 65(4), 1675-1685
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)
Garrido, P, Roetter, D E L & Aguero, R 2017, 'Markov Chain Model for the Decoding Probability of Sparse Network Coding', I E E E Transactions on Communications, vol. 65, no. 4, pp. 1675-1685. https://doi.org/10.1109/TCOMM.2017.2657621
Garrido, P, Roetter, D E L & Aguero, R 2017, ' Markov Chain Model for the Decoding Probability of Sparse Network Coding ', I E E E Transactions on Communications, vol. 65, no. 4, pp. 1675-1685 . https://doi.org/10.1109/TCOMM.2017.2657621

Subject Terms: Computer Science - Networking and Internet Architecture, Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Absorbing Markov chain, Network coding, Random codes, Sparse matrices, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://repositorio.unican.es/xmlui/bitstream/10902/12932/1/MarkovChainModel.pdf
http://arxiv.org/abs/1607.05037
http://hdl.handle.net/10902/12932
https://arxiv.org/pdf/1607.05037.pdf
https://doi.org/10.1109/TCOMM.2017.2657621
https://vbn.aau.dk/da/publications/a395d559-feeb-4b01-aa43-124656caa020
https://ieeexplore.ieee.org/document/7831490
https://repositorio.unican.es/xmlui/bitstream/10902/12932/1/MarkovChainModel.pdf
https://arxiv.org/abs/1607.05037
https://dblp.uni-trier.de/db/journals/tcom/tcom65.html#GarridoLA17
http://ieeexplore.ieee.org/document/7831490
https://eksperter.aau.dk/en/publications/markov-chain-model-for-the-decoding-probability-of-sparse-network
https://hdl.handle.net/10902/12932

Analysis and Optimization of Sparse Random Linear Network Coding for Reliable Multicast Services

Authors: Andrea Tassi Ioannis Chatzigeorgiou Daniel E. Lucani

Source: Tassi, A, Chatzigeorgiou, I & Roetter, D E L 2016, 'Analysis and Optimization of Sparse Random Linear Network Coding for Reliable Multicast Services', I E E E Transactions on Communications, vol. 64, no. 1, pp. 285-299. https://doi.org/10.1109/TCOMM.2015.2503398
Tassi, A, Chatzigeorgiou, I & Lucani, D 2016, 'Analysis and Optimization of Sparse Random Linear Network Coding for Reliable Multicast Services', IEEE Transactions on Communications, vol. 64, no. 1, pp. 285-299. https://doi.org/10.1109/TCOMM.2015.2503398

Subject Terms: Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, 2. Zero hunger, ultra-reliable communications, Computer Science - Performance, Sparse network coding, Computer Science - Information Theory, Information Theory (cs.IT), mobile communication, resource allocation, 02 engineering and technology, LTE-A, Multimedia (cs.MM), Computer Science - Networking and Internet Architecture, Performance (cs.PF), 13. Climate action, eMBMS, green communications, 0202 electrical engineering, electronic engineering, information engineering, multicast communication, Computer Science - Multimedia

File Description: application/pdf

Access URL: https://eprints.lancs.ac.uk/id/eprint/77623/1/TCOM_TPS_15_0358_CameraReady.pdf
http://arxiv.org/abs/1511.05892
https://research-information.bris.ac.uk/en/publications/af55c936-a6b9-46de-8cf9-ee483e33acfa
https://hdl.handle.net/1983/af55c936-a6b9-46de-8cf9-ee483e33acfa
https://eprints.lancs.ac.uk/id/eprint/77623/

Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networks

Authors: Kymn, Christopher J. Mazelet, Sonia Ng, Annabel et al.

Source: 2024 IEEE Neuro Inspired Computational Elements Conference, NICE 2024 - Proceedings.

Subject Terms: Convolution, Factorization, Network coding, Vectors, Combinatorial search, Computing-in-superposition, Feature representation, Hyperdimensional computing, Resonator network, Sparse coding, Vector factorizations, Vector symbolic architecture, Visual scene, Visual scene understanding, Resonators

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-74865

Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks

Authors: Poli, Daniele Thiagarajan, Srikanth DeMarse, Thomas B et al.

Subject Terms: Biological Psychology, Biomedical and Clinical Sciences, Neurosciences, Psychology, Neurodegenerative, Neurological, Animals, CA3 Region, Hippocampal, Cells, Cultured, Dentate Gyrus, Evoked Potentials, Machine Learning, Microelectrodes, Models, Neurological, Nerve Net, Neurons, Rats, hippocampus, CA3, DG, network, micro-electrode array, neural code, decoding, machine learning, Biological psychology

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Access URL: https://escholarship.org/uc/item/4c78k95r
https://escholarship.org/content/qt4c78k95r/qt4c78k95r.pdf

Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms

Authors: Xie, Jianwen Douglas, Pamela K Wu, Ying Nian et al.

Source: Journal of Neuroscience Methods. 282

Subject Terms: 32 Biomedical and Clinical Sciences (for-2020), 3209 Neurosciences (for-2020), Clinical Research (rcdc), Machine Learning and Artificial Intelligence (rcdc), Neurosciences (rcdc), Biomedical Imaging (rcdc), Bioengineering (rcdc), Algorithms (mesh), Auditory Perception (mesh), Brain (mesh), Brain Mapping (mesh), Cerebrovascular Circulation (mesh), Humans (mesh), Magnetic Resonance Imaging (mesh), Motion Perception (mesh), Neural Pathways (mesh), Neuropsychological Tests (mesh), Oxygen (mesh), Rest (mesh), FMRI, Classification, ICA, NMF, K-SVD, L1 Regularized Learning, Independent component analysis, Brain (mesh), Neural Pathways (mesh), Humans (mesh), Oxygen (mesh), Magnetic Resonance Imaging (mesh), Brain Mapping (mesh), Auditory Perception (mesh), Motion Perception (mesh), Neuropsychological Tests (mesh), Cerebrovascular Circulation (mesh), Algorithms (mesh), Rest (mesh), Artifacts, Classification, FMRI, ICA, Image processing, Independent component analysis, K-SVD, L1 Regularized Learning, Machine learning, NMF, Negative BOLD signal, Non-negative matrix factorization, Pattern recognition, Random forests, Sparsity, Support vector machines, Algorithms (mesh), Auditory Perception (mesh), Brain (mesh), Brain Mapping (mesh), Cerebrovascular Circulation (mesh), Humans (mesh), Magnetic Resonance Imaging (mesh), Motion Perception (mesh), Neural Pathways (mesh), Neuropsychological Tests (mesh), Oxygen (mesh), Rest (mesh), 1109 Neurosciences (for), 1701 Psychology (for), 1702 Cognitive Sciences (for), Neurology & Neurosurgery (science-metrix), 3209 Neurosciences (for-2020)

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An Analytical Model for Sparse Network Codes: Field Size Considerations

Authors: Amir Zarei Peyman Pahlevani Daniel E. Lucani

Source: Zarei, A, Pahlevani, P & Lucani, D E 2020, 'An Analytical Model for Sparse Network Codes : Field Size Considerations', IEEE Communications Letters, vol. 24, no. 4, 8957070, pp. 729-733. https://doi.org/10.1109/LCOMM.2020.2965928
Zarei, A, Pahlevani, P & Lucani, D E 2020, ' An Analytical Model for Sparse Network Codes : Field Size Considerations ', IEEE Communications Letters, vol. 24, no. 4, 8957070, pp. 729-733 . https://doi.org/10.1109/LCOMM.2020.2965928
Zarei, A, Pahlevani, P & Lucani Rötter, D E 2020, 'An Analytical Model for Sparse Network Codes : Field Size Considerations', I E E E Communications Letters, vol. 24, no. 4, 8957070, pp. 729-733. https://doi.org/10.1109/LCOMM.2020.2965928

Subject Terms: Sparse network coding, Random linear network coding, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Average decoding delay per packet

Access URL: https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/11250/2652876/4/Zarei.pdf
https://vbn.aau.dk/da/publications/76ac3e6f-b87d-49fa-9ba9-1949ffaa04b7
http://www.scopus.com/inward/record.url?scp=85083267656&partnerID=8YFLogxK
https://doi.org/10.1109/LCOMM.2020.2965928
https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/2652876
https://ieeexplore.ieee.org/document/8957070
https://dblp.uni-trier.de/db/journals/icl/icl24.html#ZareiPL20
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https://pure.au.dk/portal/en/publications/223a9f0c-2f30-4a6b-9cb4-14b9aa7a1046
https://ieeexplore.ieee.org/abstract/document/8957070
https://doi.org/10.1109/LCOMM.2020.2965928

Efficient Coastal Communications with Sparse Network Coding

Authors: Jiangzhou Wang Shibing Zhang Jue Wang et al.

Source: IEEE Network. 32:122-128

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 14. Life underwater

Access URL: http://ieeexplore.ieee.org/document/8315207
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8315207
https://dblp.uni-trier.de/db/journals/network/network32.html#LiWZBW18

Sparse random linear network coding for data compression in WSNs

Authors: Li, Wenjie Bassi, Francesca Kieffer, Michel

Contributors: Li, Wenjie Bassi, Francesca Kieffer, Michel

Source: 2016 IEEE International Symposium on Information Theory (ISIT). :2729-2733

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT], 02 engineering and technology

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Access URL: https://hal.archives-ouvertes.fr/hal-01327498/file/srlnc_wenjie.pdf
https://hal.science/hal-01327498v1
https://hal.science/hal-01327498v1/document
https://doi.org/10.1109/isit.2016.7541795
https://hal.archives-ouvertes.fr/hal-01327498
https://dblp.uni-trier.de/db/conf/isit/isit2016.html#LiBK16
https://hal.archives-ouvertes.fr/hal-01327498/document
https://hal-centralesupelec.archives-ouvertes.fr/hal-01327498

How to Tune Sparse Network Coding over Wireless Links

Authors: Pablo Garrido Daniel E. Lucani Ramón Agüero

Source: 2017 IEEE Wireless Communications and Networking Conference (WCNC). :1-6

Subject Terms: 0203 mechanical engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/7925561/
https://vbn.aau.dk/da/publications/how-to-tune-sparse-network-coding-over-wireless-links(eb77118c-0752-45a4-b067-caef1c84059d).html
https://eksperter.aau.dk/da/publications/how-to-tune-sparse-network-coding-over-wireless-links
https://dblp.uni-trier.de/db/conf/wcnc/wcnc2017.html#0002LA17
https://doi.org/10.1109/WCNC.2017.7925561

基于稀疏网络编码的移动边缘缓存网络稳健性维持方法研究. (Chinese)

Alternate Title: Research on robustness maintenance for sparse network coding based mobile edge caching network. (English)

Authors: 殷俊 夏欣然 张登银 et al.

Source: Chinese Journal on Internet of Things / Wulianwang Xuebao; Jun2025, Vol. 9 Issue 2, p214-222, 9p

Subject Terms: MATHEMATICAL models, HEURISTIC algorithms, ENERGY consumption, ALGORITHMS, PROBLEM solving, CACHE memory

Tunable sparse network coding for multicast networks

Authors: Feizi, Soheil Roetter, Daniel Enrique Lucani Sørensen, Chres Wiant et al.

Source: Feizi, S, Roetter, D E L, Sørensen, C W, Makhdoumi, A & Medard, M 2014, Tunable Sparse Network Coding for Multicast Networks. in Network Coding (NetCod), 2014 International Symposium on. IEEE (Institute of Electrical and Electronics Engineers), 2014 International Symposium on Network Coding, pp. 1-6, 2014 International Symposium on Network Coding, Aalborg Oest, Denmark, 27/06/2014. https://doi.org/10.1109/NETCOD.2014.6892129

Subject Terms: 2. Zero hunger, 0203 mechanical engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6892129
https://vbn.aau.dk/da/publications/95e6685f-842d-4adc-a8f2-37341f37b10b
https://doi.org/10.1109/NETCOD.2014.6892129
https://www.rle.mit.edu/ncrc/wp-content/uploads/2014/10/tunable-sparse.pdf
https://eksperter.aau.dk/da/publications/tunable-sparse-network-coding-for-multicast-networks
https://ieeexplore.ieee.org/document/6892129/
https://doi.org/10.1109/NETCOD.2014.6892129
http://ieeexplore.ieee.org/document/6892129/
https://vbn.aau.dk/en/publications/tunable-sparse-network-coding-for-multicast-networks

Secure sparse network coding for reliable routing in large scale DTMN

Authors: Tarik Chanyour Mostafa Belkasmi Rachid Saadane

Source: 2015 Third International Workshop on RFID And Adaptive Wireless Sensor Networks (RAWSN). :57-62

Subject Terms: 0203 mechanical engineering, 9. Industry and infrastructure, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/7173280/