Abstract
In order to conquer the disadvantage of the traditional Immune Neural Network (INN), the paper presents INN model which is based on extenics. With matter-element analysis, the model can solve the problem that antibody identifies and memorizes antigen in immune system. The model also can make correct judgments about activation or control of nerve cell. Consequently, the structure design of INN can be optimized. And then, the new model is applied in experiment which is used for solving the problem of nonlinearity function. Based on experiment results, the model is compared with the traditional neural network. Simulation results indicate that the new model has better convergence and stability.
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Zhu, X., Yu, Y., Wang, H. (2007). Research of Immune Neural Network Model Based on Extenics. In: Li, K., Fei, M., Irwin, G.W., Ma, S. (eds) Bio-Inspired Computational Intelligence and Applications. LSMS 2007. Lecture Notes in Computer Science, vol 4688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74769-7_3
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DOI: https://doi.org/10.1007/978-3-540-74769-7_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74768-0
Online ISBN: 978-3-540-74769-7
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