  Source localization using EEG is important in diagnosing various
physiological and psychiatric diseases related to the brain. The high temporal
resolution of EEG helps medical professionals assess the internal physiology of
the brain in a more informative way. The internal sources are obtained from EEG
by an inversion process. The number of sources in the brain outnumbers the
number of measurements. In this article, a comprehensive review of the state of
the art sparse source localization methods in this field is presented. A
recently developed method, certainty based reduced sparse solution (CARSS), is
implemented and is examined. A vast comparative study is performed using a
sixty four channel setup involving two source spaces. The first source space
has 5004 sources and the other has 2004 sources. Four test cases with one,
three, five, and seven simulated active sources are considered. Two noise
levels are also being added to the noiseless data. The CARSS is also evaluated.
The results are examined. A real EEG study is also attempted.
