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Volumn 198 AISC, Issue , 2013, Pages 205-214

Nonlinear time series analysis by using gamma growing neural gas

Author keywords

[No Author keywords available]

Indexed keywords

CONFORMAL MAPPING; INFRARED LASERS;

EID: 84872247359     PISSN: 21945357     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-35230-0_21     Document Type: Conference Paper
Times cited : (10)

References (22)
  • 2
    • 0036790884 scopus 로고    scopus 로고
    • Recursive Self-Organizing Maps
    • Voegtlin, T.: Recursive Self-Organizing Maps. Neural Networks 15, 979-991 (2002)
    • (2002) Neural Networks , vol.15 , pp. 979-991
    • Voegtlin, T.1
  • 4
    • 15844418774 scopus 로고    scopus 로고
    • Merge SOM for Temporal Data
    • Strickert, M., Hammer, B.: Merge SOM for Temporal Data. Neurocomputing 64, 39-72 (2005)
    • (2005) Neurocomputing , vol.64 , pp. 39-72
    • Strickert, M.1    Hammer, B.2
  • 6
    • 85135470835 scopus 로고
    • A Growing Neural Gas Learns Topologies
    • Tesauro, G., Touretzky, D.S., Leen, T.K. (eds.) MIT Press, Cambridge
    • Fritzke, B.: A Growing Neural Gas Learns Topologies. In: Tesauro, G., Touretzky, D.S., Leen, T.K. (eds.) Neural Information Processing Systems (NIPS), pp. 625-632. MIT Press, Cambridge (1995)
    • (1995) Neural Information Processing Systems (NIPS) , pp. 625-632
    • Fritzke, B.1
  • 8
    • 69049106545 scopus 로고    scopus 로고
    • Incremental Unsupervised Time Series Analysis Using Merge Growing Neural Gas
    • Príncipe, J.C., Miikkulainen, R. (eds.) WSOM 2009. Springer, Heidelberg
    • Andreakis, A., Hoyningen-Huene, N.v., Beetz, M.: Incremental Unsupervised Time Series Analysis Using Merge Growing Neural Gas. In: Príncipe, J.C., Miikkulainen, R. (eds.) WSOM 2009. LNCS, vol. 5629, pp. 10-18. Springer, Heidelberg (2009)
    • (2009) LNCS , vol.5629 , pp. 10-18
    • Andreakis, A.1    Hoyningen-Huene, N.V.2    Beetz, M.3
  • 9
    • 0026895542 scopus 로고
    • The Gamma Model- A New Neural Model for Temporal Processing
    • De Vries, B., Principe, J.C.: The Gamma Model- A New Neural Model for Temporal Processing. Neural Networks 5, 565-576 (1992)
    • (1992) Neural Networks , vol.5 , pp. 565-576
    • De Vries, B.1    Principe, J.C.2
  • 10
    • 69049101237 scopus 로고    scopus 로고
    • Gamma SOMfor Temporal Sequence Processing
    • Príncipe, J.C., Miikkulainen, R. (eds.) WSOM 2009 Springer, Heidelberg
    • Estévez, P.A., Hernández, R.: Gamma SOMfor Temporal Sequence Processing. In: Príncipe, J.C., Miikkulainen, R. (eds.) WSOM 2009. LNCS, vol. 5629, pp. 63-71. Springer, Heidelberg (2009)
    • (2009) LNCS , vol.5629 , pp. 63-71
    • Estévez, P.A.1    Hernández, R.2
  • 11
    • 79957616240 scopus 로고    scopus 로고
    • Gamma-filter Self-organizing Neural Networks for Unsupervised Sequence Processing
    • Estévez, P.A., Hernández, R., Perez, C.A., Held, C.M.: Gamma-filter Self-organizing Neural Networks for Unsupervised Sequence Processing. Electronics Letters 47(8), 494-496 (2011)
    • (2011) Electronics Letters , vol.47 , Issue.8 , pp. 494-496
    • Estévez, P.A.1    Hernández, R.2    Perez, C.A.3    Held, C.M.4
  • 12
    • 79959294297 scopus 로고    scopus 로고
    • Gamma-Filter Self-Organizing Neural Networks for Time Series Analysis
    • Laaksonen, J., Honkela, T. (eds.)WSOM 2011. Springer, Heidelberg
    • Estévez, P.A., Hernández, R.: Gamma-Filter Self-Organizing Neural Networks for Time Series Analysis. In: Laaksonen, J., Honkela, T. (eds.)WSOM 2011. LNCS, vol. 6731, pp. 151-159. Springer, Heidelberg (2011)
    • (2011) LNCS , vol.6731 , pp. 151-159
    • Estévez, P.A.1    Hernández, R.2
  • 13
    • 0000779360 scopus 로고
    • Detecting Strange Atractors in Turbulence
    • x Springer, New York
    • Takens, F.: Detecting Strange Atractors in Turbulence. Lecture Notes in Math., vol. 898.x Springer, New York (1981)
    • (1981) Lecture Notes in Math. , vol.898
    • Takens, F.1
  • 14
    • 0000497094 scopus 로고
    • Times series prediction using delay coordinate embedding
    • Weigend, A.S., Gershenfeld, N.A. (eds.) Addison-Wesley, FL
    • Sauer, T.: Times series prediction using delay coordinate embedding. In: Weigend, A.S., Gershenfeld, N.A. (eds.) Time Series Prediction: Forecasting the Future and Understanding the Past, pp. 175-193. Addison-Wesley, FL (1994)
    • (1994) Time Series Prediction: Forecasting the Future and Understanding the Past , pp. 175-193
    • Sauer, T.1
  • 15
    • 34548696055 scopus 로고
    • Independent Coordinates for Strange Attractors from Mutual Information
    • Fraser, A.M., Swinney, H.L.: Independent Coordinates for Strange Attractors from Mutual Information. Physical Review A 33, 1134-1140 (1986)
    • (1986) Physical Review A , vol.33 , pp. 1134-1140
    • Fraser, A.M.1    Swinney, H.L.2
  • 16
    • 35949006791 scopus 로고
    • Determining Embedding Dimension for Phase-Space Reconstruction Using a Geometrical Construction
    • Kennel, M.B., Brown, R., Abarbanel, H.D.I.: Determining Embedding Dimension for Phase-Space Reconstruction Using a Geometrical Construction. Physical Review A 45, 3403-3411 (1992)
    • (1992) Physical Review A , vol.45 , pp. 3403-3411
    • Kennel, M.B.1    Brown, R.2    Abarbanel, H.D.I.3
  • 17
    • 84872250922 scopus 로고    scopus 로고
    • Analysis of Time Series
    • Berthold, M., Hand, D.J. (eds.) Springer, Berlin
    • Bradley, E.: Analysis of Time Series. In: Berthold, M., Hand, D.J. (eds.) Intelligent Data Analysis. Springer, Berlin (1999)
    • (1999) Intelligent Data Analysis
    • Bradley, E.1
  • 20
    • 0000241853 scopus 로고
    • Deterministic non-periodic flow
    • Lorenz, E.N.: Deterministic non-periodic flow. J. Atmos. Sci. 20, 130 (1963)
    • (1963) J. Atmos. Sci. , vol.20 , pp. 130
    • Lorenz, E.N.1
  • 22
    • 33846338227 scopus 로고    scopus 로고
    • Recurrence Plots for the Analysis of Complex Systems
    • M.N., Romano, M.C., Thiel, M., Kurths, J.: Recurrence Plots for the Analysis of Complex Systems. Physics Reports 438, 237-329 (2007)
    • (2007) Physics Reports , vol.438 , pp. 237-329
    • M, N.1    Romano, M.C.2    Thiel, M.3    Kurths, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.