  There are three classical divergence measures exist in the literature on
information theory and statistics. These are namely, Jeffryes-Kullback-Leiber
J-divergence. Sibson-Burbea-Rao Jensen-Shannon divegernce and Taneja
Arithmetic-Geometric divergence. These three measures bear an interesting
relationship among each other. The divergence measures like Hellinger
discrimination, symmetric chi-square divergence, and triangular discrimination
are also known in the literature. In this paper, we have considered generalized
symmetric divergence measures having the measures given above as particular
cases. Bounds on the probability of error are obtained in terms of generalized
symmetric divergence measures. Study of bounds on probability of error is
extended for the difference of divergence measures.
