The EEG signal is used in many clinical and biomedical applications. This EEG signal obtained contains artifacts such as eye blink, noise etc. One of the most common methods to remove the noise is to use Independent Component Analysis(ICA) algorithms. In this paper we have discussed about different algorithms of ICA and their Performance Index Seperabality, Standard Deviation and Mean and Average Computation time. Here we have tested with SOBI, Thin ICA, JADE ICA algorithms. The results based on Performance Seperabality Index and Average computation time, Mean and Standard Deviation that Second Order Blind Identification algorithm is best suited to remove EEG artifacts with faster time response. To accomplish this we have used ICALAB tool box which is compatible with MATLAB. © Research India Publications.