多值免疫网络模型及其仿真

Zheng Tang, Takayuki Yamaguchi, Koichi Tashima, O. Ishizuka, K. Tanno
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引用次数: 27

摘要

提出了一种基于生物免疫应答网络的多值免疫网络模型。通过类比免疫系统中B细胞和T细胞的相互作用,建立了多值免疫网络模型。该模型具有与免疫反应非常相似的特性。对网络的抗扰度进行了仿真,并给出了几个实验可验证的预测。最后给出了该网络在字母识别中的应用仿真结果,并与二值识别进行了比较。仿真结果表明,多值免疫网络除了具有类别少、记忆模式改善、记忆容量大等优点外,还具有比二元免疫网络更强的抗噪声能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple-valued immune network model and its simulations
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.
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