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In this paper, we establish a new refinement of the arithmetic-geometric mean inequality. Applying this result in information theory, we obtain a more precise upper bound for Shannon's entropy.
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참고문헌 (8)
참고문헌 신청
S. S. Dragomir / 1996 / A counterpart of Jensen’s discrete inequality for differentiable convex mappings and applications in information theory / Math. Comput. Modelling 24(2):1~11
S. S. Dragomir / 1997 / Some bounds on entropy measures in information theory / Appl. Math. Lett 10(3):23~28
P. R. Mercer / 2003 / Refined arithmetic, geometric and harmonic mean inequalities / Rocky Mountain J. Math 33(4):1459~1464
O. Parkash / 2013 / Entropy bounds using arithmetic-geometric-harmonic mean inequality / Int. J. Pure Appl. Math 89(5):719~730
S. Simic / 2009 / Best possible global bounds for Jensen’s inequality / Appl. Math. Comput 215(6):2224~2228
S. S. Dragomir / 1997 / Some bounds on entropy measures in information theory / Appl. Math. Lett 10(3):23~28
P. R. Mercer / 2003 / Refined arithmetic, geometric and harmonic mean inequalities / Rocky Mountain J. Math 33(4):1459~1464
O. Parkash / 2013 / Entropy bounds using arithmetic-geometric-harmonic mean inequality / Int. J. Pure Appl. Math 89(5):719~730
S. Simic / 2009 / Best possible global bounds for Jensen’s inequality / Appl. Math. Comput 215(6):2224~2228
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