Pattern recognition system using a clonal selection-based immune network

Studies of immune systems include the work of Jerne on the equilibrium state of a network modeling an immune network. The authors have previously studied the information processing capabilities of immune systems and have proposed models capable of acquiring immune memory based on immune responses in an immune system. These models are based on the interactions between cells constituting an immune system, and these interactions are controlled by the state of a network formed by the cells in advance. However, in these models, cell groups are constructed by repetitions of immune responses in the immune system of a real biological organism and the fact that the immune responses are made by cell groups is not taken into account. Therefore, in this paper an immune system model involving an interactive process of network generation by cell groups generated on the basis of the clonal selection theory is proposed. The immune properties of the proposed network are shown by simulation and its effectiveness is demonstrated by applying it to a pattern recognition system.