An associative memory based on the immune networks: perspectives on internal image with antibody dynamics

Authors:
Chung-Ming Ou;Chung-Jen Ou
Affiliations:
Department of Information Management, Kainan University, Luchu, Taiwan;Department of Electrical Engineering, Hsiuping University of Science and Technology, Taichung, Taiwan
Venue:
BICS'13 Proceedings of the 6th international conference on Advances in Brain Inspired Cognitive Systems
Year:
2013

Citing 3
Cited 0

The immune system, adaptation, and machine learning

Physica D
Original Contribution: Associative memory with nonmonotone dynamics

Neural Networks
Associative memory in artificial immune systems

Annales UMCS, Informatica

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Abstract

Immune memory can be regarded as an equilibrium state of immune network system with nonlinear dynamical behavior. The rapid response of immune systems to the second-time antigen is owing to the stable structure of memory state forming by a closed idiotypic immune network. Internal image of an antigen is defined while memory state is formed via such network. A dynamical system of cell population based on antibody chains and tree structure is proposed which explains how the memory state is formed in the immune network. We also propose a network dynamics model of idiotypic immune network based on cross-reactive correlation matrix to fill the gap of weaker assumption for artificial immune memory. Mathematical theory of associative memory is also explored, particularly, combining network structure and dynamical systems are some breakthrough in this paper. We realize that cyclic idiotypic immune network and dynamical systems can be a cooperative description for immune memory.