Jensen–Shannon divergence（J-S散度） is a method of measuring the similarity between two probability distributions.

It is based on the Kullback–Leibler divergence（K-L散度）, with some notable

(and useful) differences, including that it is symmetric and it is always a finite value.

The Jensen–Shannon divergence (JSD)  is a symmetrized and smoothed version of the Kullback–Leibler divergence . It is defined by：

   where   

The Jensen–Shannon divergence is bounded by 1 for two probability distributions, given that one uses the base 2 logarithm.    

For log base e, or ln, which is commonly used in statistical thermodynamics, the upper bound is ln(2):    

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