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Process Neurons

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Process Neural Networks

Part of the book series: Advanced Topics in Science and Technology in China ((ATSTC))

Abstract

In this chapter, we will begin to discuss in detail the process neural network (PNN) which is the subject of the book. First, the concept of the process neuron is introduced. The process neuron is the basic information-processing unit that constitutes the PNN, and the model used to form it and its operating mechanism determine the properties and information-processing ability of the PNN. In this chapter, we mainly introduce a general definition and basic properties of the process neuron, and the relationship between the process neuron and mathematical concepts, such as compound functions, functional functions, etc.

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References

  1. Tsoi A.C. (1994) Locally recurrent globally feedforward networks. A Critical Review of Architectures IEEE Transactions on Neural Networks 7(5):229–239

    Article  Google Scholar 

  2. Ou Y.K., Liu W.F. (1997) Theoretical frame based on neural network of biometric—model of nerve cells. Beijing Biomedical Engineering 16(2):93–101 (in Chinese)

    Google Scholar 

  3. Zhang L.I., Tao H.W., Holt C.E., Harris W.A., Poo M. (1998) A critical window for cooperation and competition among developing retinotectal synapses. Nature 395(6697):37–44

    Article  Google Scholar 

  4. Grzegorz S., Maria Z.S., Adam R. (2004) Building of rules base for fuzzy-logic control of the ECDM process. Journal of Materials Processing Technology 149(1–3):530–535

    Google Scholar 

  5. Zhang X.L, Zhao H.W., Qi Y.M., Wang L. (2008) Grinding process fuzzy control system design and application based on MATLAB. In: Fifth International Conference on Fuzzy Systems and Knowledge Discovery 2008 3:311–315

    Article  Google Scholar 

  6. Shin S.D., Kim Y.G., Lee B.K., Bae Y.C. (2004) Design of fuzzy controller for the steam temperature process in the coal fired power plant. International Journal of Fuzzy Logic and Intelligent Systems 4(2): 187–192

    Google Scholar 

  7. Al-Wedyan H., Demirli K., Bhat R. (2001) A technique for fuzzy logic modeling of machining process. In: IFSA World Congress and 20th NAFIPS International Conference 5:3021–3026

    Article  Google Scholar 

  8. Zhou C.G., Liang Y.C., Yang Z.M. (2002) A fuzzy neural network based on fuzzy weighted reasoning method. Proceedings of 2000 International Workshop on Autonomous Decentralized Systems 1:190–195

    Google Scholar 

  9. He X.G. (1990) Fuzzy computational reasoning and neural networks. Proceedings of the Second International Conference on Tools for Artificial Intelligence pp.706–711

    Google Scholar 

  10. Chen S.M. (2002) Weighted fuzzy reasoning using weighted fuzzy petri nets. IEEE Transactions on Knowledge and Data Engineering 14(2):386–397

    Article  Google Scholar 

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© 2009 Zhejiang University Press, Hangzhou and Springer-Verlag Berlin Heidelberg

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(2009). Process Neurons. In: Process Neural Networks. Advanced Topics in Science and Technology in China. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73762-9_3

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  • DOI: https://doi.org/10.1007/978-3-540-73762-9_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73761-2

  • Online ISBN: 978-3-540-73762-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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