Spatial-temporal Analysis Method of Plane Circuits Based on Two-Layer Cellular Neural Networks

  • Masayoshi Oda
  • Yoshifumi Nishio
  • Akio Ushida
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4153)


Recently, the operational speeds of the integrated circuits are increasing rapidly. There have been many researches about transmission lines because they are very important for designing high performance integrated circuits. As well as transmission lines, the analysis of the power distribution of printed circuit boards becomes more and more important [1-3]. The analysis of the power distribution is important for designing decoupling capcitors. In the power distribution analysis, the finite element method is often applied. However, in the finite element method, in order to obtain the accurate results, we have to discretize the object into the many small elements and to solve large scale equations. It is very time consuming to solve those large scale equations by conventional degital computing.


Equivalent Circuit Print Circuit Board Power Distribution Cellular Neural Network Snap Shot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Herrell, D., Becker, B.: Modeling of Power Distribution Systems for High Performance Microprocessors. IEEE Trans. Adv. Packag. 22, 240–248 (1999)CrossRefGoogle Scholar
  2. 2.
    Kim, J., Swaminathan, M.: Modeling of Irregular Shaped Distribution Planes using Transmission Matrix Method. IEEE Trans. Adv. Packag. 24, 334–346 (2001)CrossRefGoogle Scholar
  3. 3.
    Kim, Y., Yoon, H., Lee, S., Moon, G., Kim, J., Wee, J.: An Efficient Path-Based Equivalent Circuit Model for Design, Synthesis, and Optimization of Power Distribution Networks in Multilayer Printed Circuit Boards. IEEE Trans. Adv. Packag. 27(1), 97–106 (2004)CrossRefGoogle Scholar
  4. 4.
    Chua, L.O., Yang, L.: Cellular Neural Networks: Theory. IEEE Trans. Circuits Syst. 35(10), 1257–1272 (1988)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Chua, L.O., Yang, L.: Cellular Neural Networks: Application. IEEE Trans. Circuits Syst. 35(10), 1273–1290 (1988)CrossRefMathSciNetGoogle Scholar
  6. 6.
    Roska, T., Chua, L.O., Wolf, D., Kozek, T., Tetzlaff, R., Puffer, F.: Simulating Nonlinear Waves and Partial Differential Equations via CNN —Part I: Basic Technique. IEEE Trans. Circuits Syst. 42(10), 807–815 (1995)CrossRefGoogle Scholar
  7. 7.
    Kozek, T., Chua, L.O., Roska, T., Wolf, D., Tetzlaff, R., Puffer, F., Lotz, K.: Simulating Nonlinear Waves and Partial Differential Equations via CNN —Part II: Typical Examples. IEEE Trans. Circuits Syst. 42(10), 816–819 (1995)CrossRefGoogle Scholar
  8. 8.
    Yang, Z., Nishio, Y., Ushida, A.: Generation of Various Types of Spatio-Temporal Phenomena in Two-Layer Cellular Neural Networks. IEICE Trans. on Fundamentals E87-A(4), 864–871 (2004)Google Scholar
  9. 9.
    Oda, M., Yang, Z., Nishio, Y., Ushida, A.: Analysis of Two-Dimensional Conductive Plates Based on CNNs. In: Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing (NCSP 2005), pp. 447–450 (March 2005)Google Scholar
  10. 10.
    Tanji, Y., Asai, H., Oda, M., Nishio, Y., Ushida, A.: Fast Timing Analysis of Plane Circuits via Two-Layer CNN-Based Modeling. In: Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS 2006), pp. 3738–3741 (May 2006)Google Scholar
  11. 11.
    Ushida, A., Tanji, Y., Nishio, Y.: Analysis of Two-Dimensional Circuits Based on Multi-conductive Theorem. IEICE Tech. Report NLP-97-16, pp. 25–29 (1997)Google Scholar
  12. 12.
    Thiran, P.: Influence of Boundary Conditions on the Behavior of Cellular Neural Networks. IEEE Trans. Circuits Syst. 40(3), 207–212 (1993)zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Masayoshi Oda
    • 1
  • Yoshifumi Nishio
    • 1
  • Akio Ushida
    • 2
  1. 1.Dept. of Electrical and Electronic EngineeringTokushima UniversityJapan
  2. 2.Dept. Mechanical and Electrical Electronic EngineeringTokushima Bunri UniversityJapan

Personalised recommendations