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2003 Fiscal Year Final Research Report Summary

Systematic study for self-organization phenomena based on mathematical informatics and statistical mechanics

Research Project

Project/Area Number 13650062
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Engineering fundamentals
Research InstitutionChiba University

Principal Investigator

MATSUBA Ikuo  Chiba University, Faculty of Engineering, Professor, 工学部, 教授 (30251177)

Co-Investigator(Kenkyū-buntansha) SUYARI Hiroki  Chiba University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (70246685)
KOSHIGOE Hideyuki  Chiba University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (70110294)
KAWARADA Hideo  Ryutsu Keizai University, Distribution and logistics, Professor, 流通情報学部, 教授 (90010793)
SUITO Hiroshi  Okayama University, Faculty of Environmental Science and Technology, Associate Professor, 環境理工学部, 助教授 (10302530)
Project Period (FY) 2001 – 2003
KeywordsSelf-organization / Fractal / Self-similarity / Neural networks / Renormalization method
Research Abstract

It is a common feature of some physical systems consisting of a large number of coupled systems that a cascade of energy flow from large to small scales generates a scaling behavior, namely power-law behavior of some observable. Scaling is found in a wide range of systems, from geophysical to biological. A typical example is seismicity that is characterized by an energy transfer through a hierarchy stricture. One of recent research is to apply this idea to explain the observed scaling laws. We proposed the general model equation of threshold dynamics that exhibits self-similar properties. The commonly used dynamically driven Renormalization Group method is useful to analyze the scale invariance of the spatiotemporal structures produced by the operation of the updating algorithm. This method integrates the model in space and time in the analysis of the effect of coarse graining on the dynamics to produce the set of Renormalization group equations from which various characteristic exponents are obtained. A technically simpler, but nevertheless asymptotically exact, method where coarse graining is performed by updating the model with respect to time is used to study the self-similar behavior of the model to predict the characteristic exponents.

  • Research Products

    (16 results)

All Other

All Publications (16 results)

  • [Publications] 神谷良信, 須鎗弘樹, 松葉育雄: "ニューラルネットワークモデルの粗視化による脳波の1/fスペクトルの導出"電子情報通信学会論文誌. J84-A. 1148-1156 (2001)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] I.Matsuba: "Generalized Information Criterion for Linear and Nonlinear Processes"Int.J.Bifurcation and Chaos. 12. 389-395 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] I.Matsuba: "Renormalization group approach to earthquake scaling"Chaos, Solitons & Fractals. 13. 1281-1294 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] I.Matsuba, M.Namatame: "Scaling Behavior in Urban Development Process of Tokyo City and Hierarchical Dynamical Structure"Chaos, Solitons & Fractals. 16. 151-165 (2003)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] I.Matsuba, H.Takahashi: "Generalized Entropy Approach to Stable Levy Distributions with Financial Application"Physica A. 319. 458-468 (2003)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] Y.Kamitani, I.Matsuba: "Self-similar Characteristics of Neural Networks based on Fokker-Planck Equation"Chaos, Solitons & Fractals. 20. 329-335 (2004)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 生田目将慎, 松葉育雄: "都市成長のセルラオートマタモデルとフラクタル解析"日本応用数理学会論文誌. 13. 461-469 (2003)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] I.Matsuba, Y.Mukuta: "Scaling in Bucking of Long Columns"Chaos, Solitons & Fractals. 20. 451-454 (2004)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] Y.Kamitani, H.Suyari, I.Matsuba: "Derivation of I/f fluctuation by means of spatial coarse-graining method for neural network model"The transactions of the Institute of Electronics, Information and Communication Engineers (in Japanese). vol.J84-A. 1148-1156 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] I.Matsuba: "Generalized Information Criterion for Linear and Nonlinear Processes"Int.J.Bifurcation and Chaos. Vol.12. 389-395 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] I.Matsuba: "Renormalization group approach to earthquake scaling"Chaos, Solitons & Fractals. Vol.13. 1281-1294 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] I.Matsuba, M.Namatame: "Scaling Behavior in Urban Development Process of Tokyo City and Hierarchical Dynamical Structure"Chaos, Solitons & Fractals. Vol.16. 151-165 (2003)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] I.Matsuba, H.Takahashi: "Generalized Entropy Approach to Stable Levy Distributions with Financial Application"Physica A. Vol.319. 458-468 (2003)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Y.Kamitani, I.Matsuba: "Self-similar Characteristics of Neural Networks based on Fokker-Planck Equation"Chaos, Solitons & Fractals. Vol.20. 329-335 (2004)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] M.Namatame, I.Matsuba: "Cellular Automata Model of Urban Growth and Fractal Analysis"The Japan Society for Industrial and Applied Mathematics (in Japanese). Vol.13. 461-469 (2003)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] I.Matsuba, Y.Mukuta: "Scaling in Bucking of Long Columns"Chaos, Solitons & Fractals. Vol.20. 451-454 (2004)

    • Description
      「研究成果報告書概要(欧文)」より

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Published: 2005-04-19  

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