An improved artificial immune algorithm with application to multiple sensor systems

Recently, the human immune systems have aroused researcher’s interest due to it useful mechanisms which can be used and exploited for information processing in a complex cognition system. The scope of this research is not to reproduce any immune phenomenon accurately, rather to show that immune concepts can be applied to develop powerful computational tools for data processing. From this viewpoint, an improved artificial immune algorithm is presented and applied to the problems associated with image registration and configurations of multiple sensor systems. Simulation results show that the immune algorithm can successfully obtain the global optimum with less computational cost compared to other traditional algorithms. Therefore, this method has a potential application in other optimization problems.