6 – Sensor Networks
暂无分享,去创建一个
[1] Toby Berger,et al. Multiterminal Source Coding with High Resolution , 1999, IEEE Trans. Inf. Theory.
[2] Baltasar Beferull-Lozano,et al. Scaling laws for correlated data gathering , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..
[3] Martin Vetterli,et al. On the optimal density for real-time data gathering of spatio-temporal processes in sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..
[4] Robert B. Ash,et al. Information Theory , 2020, The SAGE International Encyclopedia of Mass Media and Society.
[5] Michael Gastpar,et al. To code, or not to code: lossy source-channel communication revisited , 2003, IEEE Trans. Inf. Theory.
[6] Baltasar Beferull-Lozano,et al. Power-efficient sensor placement and transmission structure for data gathering under distortion constraints , 2006, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.
[7] Krishna M. Sivalingam,et al. Data gathering in sensor networks using the energy*delay metric , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.
[8] Kannan Ramchandran,et al. On distributed sampling of bandlimited and non-bandlimited sensor fields , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[9] Kannan Ramchandran,et al. Distributed source coding using syndromes (DISCUS): design and construction , 2003, IEEE Trans. Inf. Theory.
[10] Michael Gastpar,et al. Power, spatio-temporal bandwidth, and distortion in large sensor networks , 2005, IEEE Journal on Selected Areas in Communications.
[11] Wendi Heinzelman,et al. Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.
[12] Deborah Estrin,et al. Coping with irregular spatio-temporal sampling in sensor networks , 2004, CCRV.
[13] Ramesh Govindan,et al. Scale-free aggregation in sensor networks , 2005, Theor. Comput. Sci..
[14] S. PradhanS.,et al. Distributed source coding using syndromes (DISCUS) , 2006 .
[15] Deborah Estrin,et al. Simultaneous Optimization for Concave Costs: Single Sink Aggregation or Single Source Buy-at-Bulk , 2003, SODA '03.
[16] S.D. Servetto,et al. Efficient network architectures for sensor reachback , 2004, International Zurich Seminar on Communications, 2004.
[17] Baltasar Beferull-Lozano,et al. Lossy network correlated data gathering with high-resolution coding , 2005, IEEE Transactions on Information Theory.
[18] Jack K. Wolf,et al. Noiseless coding of correlated information sources , 1973, IEEE Trans. Inf. Theory.
[19] Baltasar Beferull-Lozano,et al. On network correlated data gathering , 2004, IEEE INFOCOM 2004.
[20] Gregory J. Pottie,et al. Wireless integrated network sensors , 2000, Commun. ACM.
[21] Mingyan Liu,et al. On the Many-to-One Transport Capacity of a Dense Wireless Sensor Network and the Compressibility of Its Data , 2003, IPSN.
[22] Sergio Verdú,et al. The source-channel separation theorem revisited , 1995, IEEE Trans. Inf. Theory.
[23] Toby Berger,et al. Lossy Source Coding , 1998, IEEE Trans. Inf. Theory.
[24] Martin Vetterli,et al. Power efficient gathering of correlated data: optimization, NP-completeness and heuristics , 2003, MOCO.
[25] Bernd Girod,et al. Compression with side information using turbo codes , 2002, Proceedings DCC 2002. Data Compression Conference.
[26] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.