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Zheng TANG Takayuki YAMAGUCHI Koichi TASHIMA Okihiko ISHIZUKA Koichi TANNO
This paper describes a new model of multiple-valued immune network based on biological immune response network. The model of multiple-valued immune network is formulated based on the analogy with the interaction between B cells and T cells in immune system. The model has a property that resembles immune response quite well. The immunity of the network is simulated and makes several experimentally testable predictions. Simulation results are given to a letter recognition application of the network and compared with binary ones. The simulations show that, beside the advantages of less categories, improved memory pattern and good memory capacity, the multiple-valued immune network produces a stronger noise immunity than binary one.