Skip to main content

Gauss Chaotic Neural Networks

  • Conference paper
PRICAI 2006: Trends in Artificial Intelligence (PRICAI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4099))

Included in the following conference series:

Abstract

We retrospect Chen’s chaotic neural network and then propose a new chaotic neural network model whose activation function is composed of Gauss and Sigmoid function. And the time evolution figures of the largest Lyapunov exponents of chaotic single neural units are plotted. Based on the new model, the model with different parameters is applied to combinational optimization problems. 10-city traveling salesman problem (TSP) is given to make a comparison between Chen’s and the new model with different parameters. Finally on the simulation results we conclude that the novel chaotic neural network model we proposed is more effective.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 239.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Hopfield, J.J., Tank, D.W.: Neural Computation of Decision in Optimization Problems. Biol. Cybern. 52, 141–152 (1985)

    MATH  MathSciNet  Google Scholar 

  2. Hopfield, J.: Neural Networks and Physical Systems with Emergent Collective Computa-tional Abilities. Proc. Natl. Acad. Sci. 79, 2554–2558 (1982)

    Article  MathSciNet  Google Scholar 

  3. Hopfield, J.: Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proc. Natl. Acad. Sci. 81, 3088–3092 (1984)

    Article  Google Scholar 

  4. Xu, Y.-Q., Sun, M., Duan, G.-R.: Wavelet Chaotic Neural Networks and Their Application to Optimization Problems. In: Wang, J., Yi, Z., Żurada, J.M., Lu, B.-L., Yin, H. (eds.) ISNN 2006. LNCS, vol. 3971, pp. 379–384. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  5. Chen, L., Aihara, K.: Chaotic Simulated Annealing by a Neural Network Model with Transient Chaos. Neural Networks 8, 915–930 (1995)

    Article  Google Scholar 

  6. Sun, S.-Y., Zheng, J.-l.: A Kind of Improved Algorithm and Theory Testify of Solving TSP in Hopfield Neural Network. Journal of electron. 1, 73–78 (1995)

    Google Scholar 

  7. Potapove, A., KAli, M.: Robust Chaos in Neural Networks. Physics Letters A 277, 310–322 (2000)

    Article  MathSciNet  Google Scholar 

  8. Aihara, K.: Chaos engineering and its application to parallel distributed processing with chaotic neural networks. Proceedings of the IEEE 90, 919–930 (2002)

    Article  Google Scholar 

  9. Wang, L.P., Li, S., Tian, F.Y., Fu, X.J.: A noisy chaotic neural network for solving combinatorial optimization problems: Stochastic chaotic simulated annealing. IEEE Trans. System, Man, Cybern, Part B - Cybernetics 34, 2119–2125 (2004)

    Article  Google Scholar 

  10. Wang, L.P., Shi, H.: A noisy chaotic neural network approach to topological optimization of a communication network with reliability constraints. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3174, pp. 230–235. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  11. Wang, L.P., Smith, K.: On chaotic simulated annealing. IEEE Trans Neural Networks 9, 716–718 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Xu, Yq., Sun, M., Shen, Jh. (2006). Gauss Chaotic Neural Networks. In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-36668-3_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36667-6

  • Online ISBN: 978-3-540-36668-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics