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Volumn 2, Issue , 2005, Pages 373-377

Learning patterns in wireless sensor networks based on wavelet neural-networks

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; DATA ROBUSTNESS; SENSOR NETWORKS; WIRELESS SENSORS;

EID: 23944506746     PISSN: 15219097     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPADS.2005.178     Document Type: Conference Paper
Times cited : (6)

References (9)
  • 2
    • 0021776661 scopus 로고
    • A massively parallel architecture for a self-organizing neural pattern recognition machine
    • Carpenter, G.A., and Grossberg, S., A massively parallel architecture for a self-organizing neural pattern recognition machine, Computer Vision, Graphics, and Image Processing, vol. 37, pp. 54-115, 1987.
    • (1987) Computer Vision, Graphics, and Image Processing , vol.37 , pp. 54-115
    • Carpenter, G.A.1    Grossberg, S.2
  • 3
    • 0026408256 scopus 로고
    • Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system
    • Carpenter, G.A., Grossberg, S., and Rosen, D.B., Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system, Neural Networks, vol. 4, pp. 759-771, 1991.
    • (1991) Neural Networks , vol.4 , pp. 759-771
    • Carpenter, G.A.1    Grossberg, S.2    Rosen, D.B.3
  • 4
    • 26844475931 scopus 로고    scopus 로고
    • Self-organization in ad hoc sensor networks: An empirical study
    • The 8th Int. Conf. on the Simulation and Synthesis of Living Systems, Sydney, NSW, Australia
    • Catterall, E., Van Laerhoven, K., and Strohbach, M., Self-Organization in Ad Hoc Sensor Networks: An Empirical Study, in Proc. of Artificial Life VIII, The 8th Int. Conf. on the Simulation and Synthesis of Living Systems, Sydney, NSW, Australia, 2002.
    • (2002) Proc. of Artificial Life VIII
    • Catterall, E.1    Van Laerhoven, K.2    Strohbach, M.3
  • 5
    • 23944480820 scopus 로고    scopus 로고
    • DIMENSIONS: Why do we need a new data handling architecture for sensor networks?
    • Berkeley, California, USA
    • Ganesan, D., Estrin, D., Heidemann, J., DIMENSIONS: Why do we need a new Data Handling architecture for Sensor Networks?, in Proc. Information Processing in Sensor Networks, Berkeley, California, USA, 2004.
    • (2004) Proc. Information Processing in Sensor Networks
    • Ganesan, D.1    Estrin, D.2    Heidemann, J.3
  • 6
    • 0017120827 scopus 로고
    • Adaptive pattern classification and universal receding: I. Parallel development and coding of neural feature detectors
    • Grossberg, S. Adaptive pattern classification and universal receding: I. parallel development and coding of neural feature detectors, Biological Cybernetics, vol. 23, pp. 121-134, 1976.
    • (1976) Biological Cybernetics , vol.23 , pp. 121-134
    • Grossberg, S.1
  • 8
    • 3042820611 scopus 로고    scopus 로고
    • Distributed regression: An efficient framework for modeling sensor network data
    • April 26-27, 2004, Berkeley, California, USA
    • Guestrin, C., Bodik, P., Thibaux, R., Paskin M., and Madden, S., Distributed Regression: an Efficient Framework for Modeling Sensor Network Data, in Proceedings of IPSN'04, April 26-27, 2004, Berkeley, California, USA, 2004.
    • (2004) Proceedings of IPSN'04
    • Guestrin, C.1    Bodik, P.2    Thibaux, R.3    Paskin, M.4    Madden, S.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.