연구동향 분석
박사

(A) study on finite field compressive sensing framework for network coding

Ganzorig Gankhuyag 2020년

논문상세정보
인용/피인용
' (A) study on finite field compressive sensing framework for network coding' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Network coding
  • all-or-nothing property
  • all-or-nothing 문제
  • compressive sensing
  • finite field
  • finite field optimization
  • greedy optimization
  • sparse matrices
  • 네트워크 코딩
  • 압축센싱
  • 유한 핀드 최적화
  • 탐욕 최적화
  • 회소 행렬
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
102 0

0.0%

' (A) study on finite field compressive sensing framework for network coding' 의 참고문헌

  • ¡°Xors in the air : practical wireless networkCoding ,
    vol . 36 , no . 4 . ACM ,pp . 243 ? 254 [2006]
  • ¡°The simplest solution to an underdetermined system of linear equations ,
  • ¡°The rank of sparse random matrices over finite fields , ¡± Random Structures and algorithms ,
    vol . 10 , no . 4 , pp . 407 ? 420 [1997]
  • ¡°Sparse image recovery usingCompressed sensing over finite alphabets
    pp . 1287 ? 1291 [2014]
  • ¡°Sparse and redundant representation modeling ? what next ? ¡± Signal Processing Letters
    vol . 19 , no . 12 , pp . 922 ? 928 [2012]
  • ¡°Singularity probability analysis for sparse random linear networkCoding , ¡± inCommunications ( ICC )
    pp . 1 ? 5 . [2011]
  • ¡°Robustness vs. efficiency in sensor networks , ¡± in Proceedings of the 4th international symposium on Information processing in sensor networks
    [2005]
  • ¡°Robust uncertainty principles : Exact signal reconstruction from highly incomplete frequency information , ¡± Information Theory
    vol . 52 , no . 2 , pp . 489 ? 509 [2006]
  • ¡°Remote dataChecking for networkCoding-based distributed storage systems
    pp . 31 ? 42 [2010]
  • ¡°R2 : Random push with random networkCoding in live peer-to-peer streaming , ¡± Selected Areas inCommunications
    vol . 25 , no . 9 , pp . 1655 ? 1666 [2007]
  • ¡°Polynomial time algorithms for multicast networkCodeConstruction ,
    vol . 51 , no . 6 , pp .
  • ¡°On theCompressed measurements over finite fields : Sparse or dense sampling
    [2012]
  • ¡°On the rank of random matrices
    vol . 16 , no . 2 , pp . 209 ? 232 [2000]
  • ¡°On the distribution of rank of a random matrix over a finite field , ¡± Random Structures and Algorithms
    vol . 17 , no . 3-4 , pp . 197 ? 212 [2000]
  • ¡°On practical networkCoding for wireless environments , ¡± inCommunications , 2006 International Zurich Seminar on
    pp . 84 ? 85 . [2006]
  • ¡°On practical design for joint distributed source and networkCoding , ¡± Information Theory
    vol . 55 , no . 4 , pp . 1709 ? 1720 [2009]
  • ¡°NetworkCoding theory : single sources , ¡±Communications and Information Theory
    vol . 2 , no . 4 , pp . 241 ? 329 [2005]
  • ¡°NetworkCoding meets tcp , ¡± in INFOCOM 2009
    pp . 280 ? 288 [2009]
  • ¡°NetworkCoding for the internet and wireless networks
    vol . 24 , no . 5 , p. 77 [2007]
  • ¡°Network information flow , ¡± Information Theory
    vol . 46 , no . 4 , pp . 1204 ? 1216 [2000]
  • ¡°Netcompress :Coupling networkCoding andCompressed sensing for efficient dataCommunication in wireless sensor networks , ¡± in Signal Processing Systems
    pp . 356 ? 361 [2010]
  • ¡°Message passing algorithms forCompressed sensing : I. motivation andConstruction , ¡± in Information Theory ( ITW 2010 ,Cairo )
    pp . 1 ? 5 . [2010]
  • ¡°Linear networkCoding , ¡± Information Theory
    vol . 49 , no . 2 , pp . 371 ? 381 [2003]
  • ¡°Linear networkCodes : A unified framework for source ,Channel , and 88networkCoding , ¡± DIMACS Series in Discrete Mathematics and TheoreticalComputer Science
    vol . 66 , pp . 197 ? 216 [2004]
  • ¡°Joint decoding of multipledescription network-coded data , ¡± in NetworkCoding ( NetCod )
    pp . 1 ? 6 . [2011]
  • ¡°Information exchange in wireless networks with networkCoding and physical-layer broadcast
    [2005]
  • ¡°Improved approximate decoding based on position information matrix , ¡± inComputers andCommunications ( ISCC )
    pp . 000 114 ? 000 118 .
  • ¡°Improved approximate decoding based on position information matrix , ¡± inComputers andCommunications ( ISCC )
    pp . 000 114 ? 000 118 [2012]
  • ¡°How practical is networkCoding ?
    pp . 274 ? 278 . [2006]
  • ¡°ErrorControl for networkCoding , ¡± Ph.D. dissertation
    [2009]
  • ¡°DiscreteCosine transform
    vol . 100 , no . 1 , pp . 90 ? 93 [1974]
  • ¡°Compressive networkCoding for approximate sensor data gathering
    pp . 1 ? 6 . [2011]
  • ¡°Compressed sensing and best kterm approximation
    [2006]
  • ¡°Communication over finite-field matrixChannels
    vol . 56 , no . 3 , pp . 1296 ? 1305 [2010]
  • ¡°Coherence-based performance guarantees for estimating a sparse vector under random noise , ¡± Signal Processing
    vol . 58 , no . 10 , pp . 5030 ? 5043 [2010]
  • ¡°Approximate decoding approaches for networkCodedCorrelated data
    vol . 93 , no . 1 , pp . 109 ? 123 [2013]
  • ¡°AContent distribution system based on sparse linear networkCoding
    [2007]
  • ¡°A survey on networkCodes for distributed storage
    vol . 99 , no . 3 , pp . 476 ? 489 [2011]
  • ¡°A rank-metric approach to errorControl in random networkCoding ,
    vol . 54 , no . 9 , pp . 3951 ? 3967 [2008]
  • ¡°A random linear networkCoding approach to multicast , ¡± Information Theory
    vol . 52 , no . 10 , pp . 4413 ? 4430 [2006]
  • [77] G. Werner-Allen, P. Swieskowski, and M. Welsh, ¡°Motelab: A wireless sensor network testbed,¡± in Proceedings of the 4th international symposium on Information processing in sensor networks. IEEE Press, 2005, p. 68.
  • [73] S. C. Draper and S. Malekpour, ¡°Compressed sensing over finite fields,¡± in Proceedings of the 2009 IEEE international conference on Symposium on Information Theory-Volume 1. IEEE Press, 2009, pp. 669?673.
  • [72] R. Berinde, A. C. Gilbert, P. Indyk, H. Karloff, and M. J. Strauss, ¡°Combining geometry and combinatorics: A unified approach to sparse signal recovery,¡± in Communication, Control, and Computing, 2008 46th Annual Allerton Conference on. IEEE, 2008, pp. 798?805.
  • [67] R. D. Nowak, S. J. Wright et al., ¡°Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems,¡± IEEE Journal of selected topics in signal processing, vol. 1, no. 4, pp. 586?597, 2007.
  • [66] J. A. Tropp and A. C. Gilbert, ¡°Signal recovery from random measurements via orthogonal matching pursuit,¡± Information Theory, IEEE Transactions on, vol. 53, no. 12, pp. 4655?4666, 2007.
  • [64] E. J. Cand`e and M. B. Wakin, ¡°An introduction to compressive sampling,¡± Signal Processing Magazine, IEEE, vol. 25, no. 2, pp. 21?30, 2008.
  • [62] D. L. Donoho and M. Elad, ¡°Optimally sparse representation in general (nonorthogonal) dictionaries via §¤1 minimization,¡± Proceedings of the National Academy of Sciences, vol. 100, no. 5, pp. 2197?2202, 2003.
  • [60] E. J.Candes and T. Tao, ¡°Decoding by linear programming,¡± Information Theory, IEEE Transactions on, vol. 51, no. 12, pp. 4203?4215, 2005.
    vol . 51 , no . 12 , pp . 4203 ? 4215 [2005]
  • [58] M. Nabaee and F. Labeau, ¡°Restricted isometry property in quantized network coding of sparse messages,¡± in Global Communications Conference (GLOBECOM), 2012 IEEE. IEEE, 2012, pp. 112?117.
  • [56] E. M. Gabidulin, ¡°Theory of codes with maximum rank distance,¡± Problemy Peredachi Informatsii, vol. 21, no. 1, pp. 3?16, 1985.
  • [50] H. Shojania and B. Li, ¡°Random network coding on the iphone: fact or fiction?¡± in Proceedings of the 18th international workshop on Network and operating systems support for digital audio and video. ACM, 2009, pp. 37?42.
  • [45] K.-J. Bathe and E. L. Wilson, ¡°Numerical methods in finite element analysis,¡± 1976.
    [1976]
  • [44] M. J. Siavoshani, S. Mohajer, C. Fragouli, and S. N. Diggavi, ¡°On the capacity of noncoherent network coding,¡± IEEE Transactions on Information Theory, vol. 57, no. 2, pp. 1046?1066, 2011.
  • [40] C. Fragouli and E. Soljanin, ¡°Information flow decomposition for network coding,¡± Information Theory, IEEE Transactions on, vol. 52, no. 3, pp. 829? 848, 2006.
  • [3] M. Medard and A. Sprintson, Network coding: fundamentals and applications. Academic Press, 2011.
  • [38] N. Cai and R. W. Yeung, ¡°Secure network coding,¡± in Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on. IEEE, 2002, p. 323.
  • [36] R. W. Yeung and N.Cai, NetworkCoding theory. Now Publishers Inc, 2006.
    [2006]
  • [33] R. Koetter and M. M¢¥edard, ¡°An algebraic approach to network coding,¡± IEEE/ACM Transactions on Networking (TON), vol. 11, no. 5, pp. 782? 795, 2003.
  • [31] S. Feizi and M. M¢¥edard, ¡°A power efficient sensing/communication scheme: Joint source-channel-network coding by using compressive sensing,¡± in Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on. IEEE, 2011, pp. 1048?1054.
  • [30] S. Katti, S. Shintre, S. Jaggi, D. Katabi, and M. Medard, ¡°Real networkCodes,¡± in Proc. Forty-Fifth Annual AllertonConference, 2007, pp. 389?395.
    pp . 389 ? 395 . [2007]
  • [29] R. G. Baraniuk, ¡°Compressive sensing,¡± IEEE signal processing magazine, vol. 24, no. 4, 2007.
  • [27] D. L. Donoho, M. Vetterli, R. A. DeVore, and I. Daubechies, ¡°Data compression and harmonic analysis,¡± IEEE Transactions on Information Theory, vol. 44, no. 6, pp. 2435?2476, 1998.
  • [26] D. L. Donoho and X. Huo, ¡°Uncertainty principles and ideal atomic decomposition,¡± IEEE Transactions on Information Theory, vol. 47, no. 7, pp. 2845?2862, 2001.
  • [25] D. L. Donoho, ¡°Compressed sensing,¡± Information Theory, IEEE Transactions on, vol. 52, no. 4, pp. 1289?1306, 2006.
  • [24] D. Silva and F. R. Kschischang, ¡°Using rank-metric codes for error correction in random network coding,¡± in Information Theory, 2007. ISIT 2007. IEEE International Symposium on. IEEE, 2007, pp. 796?800.
  • [19] H. Seferoglu and A. Markopoulou, ¡°Distributed rate control for video streaming over wireless networks with intersession network coding,¡± in Packet Video Workshop, 2009. PV 2009. 17th International. IEEE, 2009, pp. 1?10.
  • [18] H. Seferoglu and A. Markopoulou, ¡°Video-aware opportunistic network coding over wireless networks,¡± Selected Areas in Communications, IEEE Journal on, vol. 27, no. 5, pp. 713?728, 2009.
  • [17] H. Seferoglu and A. Markopoulou, ¡°Opportunistic network coding for video streaming over wireless,¡± in Packet Video 2007. IEEE, 2007, pp. 191?200.
  • [16] N. Thomos and P. Frossard, ¡°Network coding and media streaming,¡± Journal of Communications, vol. 4, no. 9, pp. 628?639, 2009.
  • [15] H. Seferoglu, A. Markopoulou, and K. Ramakrishnan, ¡°I 2 nc: intra-and inter-session network coding for unicast flows in wireless networks,¡± in INFOCOM, 2011 Proceedings IEEE. IEEE, 2011, pp. 1035?1043.
  • [11] C. Gkantsidis and P. R. Rodriguez, ¡°Network coding for large scale content distribution,¡± in Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies., vol. 4. IEEE, 2005, pp. 2235?2245.
  • R.C. Mullin , S. A. Vanstone , and T. Yaghoobian , Applications of finite fields .
    vol . 199 . [2013]
  • N. Thomos , and P. Frossard , ¡°Approximate decoding for network coded inter-dependent data ,
    vol . 120 , pp . 222 ? 235 [2016]
  • M. M¢¥edard , M. Effros , R. Koetter , and D. Karger , ¡°Network coding for correlated sources
    [2004]
  • M. Effros , and D. R. Karger , ¡°On randomized network coding ,
    vol . 41 , no . 1 . Citeseer , [2003]
  • Information theory and network coding
    [2008]
  • D. R. Karger , and M. Effros , The benefits of coding over routing in a randomized setting
    [2003]
  • D. L. Donoho , and M. A. Saunders , Atomic decomposition by basis pursuit
    vol . 43 , no . 1 , pp . 129 ? 159 [2001]