Implementation of neuro-fuzzy system with modified high performance genetic algorithm on embedded systems

In this paper implementation of ANFIS on embedded systems based on single-core and multi-core ARM processors is presented. A novel evolutionary optimization tool named, modified high performance genetic algorithm (mHPGA) with bacterial conjugation operator is applied to ANFIS as a training method. Fixed point and floating point number representations are applied and compared. Moreover new mutation algorithm has been proposed for fixed point numbers. The proposed method is designed to sweep numbers space to search possible solutions in large state space. Concurrency nature of mHPGA benefits implementation of multi threading feature on ARM cortex-A53 with four cores.