  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
arithemtic-geometric mean divergence. These three measures bear an interesting
relationship among each other and are based on logarithmic expressions. The
divergence measures like Hellinger discrimination, symmetric chi-square
divergence, and triangular discrimination are also known in the literature and
are not based on logarithmic expressions. Past years Dragomir et al., Kumar and
Johnson and Jain and Srivastava studied different kind of divergence measures.
In this paper, we have presented some more new divergence measures and obtained
inequalities relating these new measures and also made connections with
previous ones. The idea of exponential divergence is also introduced.
