A modified artificial bee colony (ABC) algorithm based blind source separation (BSS) method is proposed in this paper

aiming at the problems of slow convergence and low computational precision of existing blind source separation methods.The modified ABC algorithm can adjust the step size function of the selected neighbor food source position adaptively.On the other hand

it takes advantage of the information of the global best solution to guide the search of candidate solutions to improve the exploitation.The modified ABC algorithm balances the exploration and exploitation which contradict with each other well

so it can achieve good optimizate performance.The new BSS improves the separation precision and the stable performance.Experimental results demonstrate that the proposed BSS can separate linear and instantaneous mixed signals effectively.Compared to the other approaches

the proposed method not only obtains better separation performance

but also has a faster convergence speed.