“…The essential reason is to evaluate how much data is contained within the information. Now a days, these measures are being connected in a few disciplines such as: color picture division [17], estimation of likelihood dispersions [4,8], design acknowledgment [9,23], 3D picture division and word arrangement [20], choice making [16,22,24,25], attractive reverberation picture investigation [27], fetched-touchy classification for therapeutic conclusion [19], turbulence stream [5], fuzzy divergence and applications [3,10,15,21,26], etc. Let Θ l = {U = (u 1 , u 2 , u 3 , ..., u l ) : u i > 0, l i=1 u i = 1}, l ≥ 2 be the set of all complete finite discrete probability distributions, where u i is a probability mass function.…”