Variation of Uncertainty in Steady And Non-Steady Processes Of Queuing Theory
Probabilistic measures of uncertainty have been
obtained as functions of time and birth and death rates in a queuing
process. The variation of different entropy measures has been studied
in steady and non-steady processes of queuing theory.
[1] Asadi, M., Ebrahimi, N., Hamedani, G.G. and Soofi, S. (2004):
"Maximum dynamic entropy models", Applied Probability 4,1 379-
390.
[2] Cai, H., Kulkarni, S. and Verdu, S. (2006): "Universal divergence
estimation for finite-alphabet sources", IEEE Transactions on
Information Theory, 52, 3456-3475.
[3] Chakrabarti, C.G. (2005): "Shannon entropy: axiomatic
characterization and application", International Journal of Mathematics
and Mathematical Sciences, 17, 2847-2854.
[4] Chen, Y. (2006): "Properties of quasi-entropy and their applications",
Journal of Southeast University Natural Sciences, 36, 222-225.
[5] Garbaczewski, P. (2006): "Differential entropy and dynamics of
uncertainty", Journal of Statistical Physics, 123, 315-355.
[6] Kapur, J.N. (1967): "Generalized entropy of order ╬▒ and type β",
Mathematics Seminar, 4, 79-84.
[7] Kapur, J.N. (1995): "Measures of Information and Their Applications",
Wiley Eastern, New York.
[8] Medhi, J.M. (1982): "Stochastic Processes", Wiley Eastern, New
Delhi.
[9] Nanda, A. K.and Paul, P. (2006): "Some results on generalized
residual entropy", Information Sciences, 176, 27-47.
[10] Paninski, L. and Yajima, M. (2008): "Undersmoothed kernel entropy
estimators", IEEE Trans. Inform.Theory, 54(9), 4384-4388.
[11] Piera, F.J. and Parade, P. (2009): "On the convergence properties of
Shannon entropy", Problemy Peredacht Informatsii, 45(2), 75-94.
[12] Shannon, C. E. (1948): "A mathematical theory of communication",
Bell System Technical Journal, 27, 379-423, 623-659.
[13] Sharma, B.D. and Taneja, I.J. (1975): "Entropies of type (╬▒,β) and
other generalized measures of information theory", Metrica, 22, 202-
215.
[14] Zyczkowski, K. (2003): "Renyi extrapolation of Shannon entropy",
Open Systems and Information Dynamics, 10, 297-310.
[1] Asadi, M., Ebrahimi, N., Hamedani, G.G. and Soofi, S. (2004):
"Maximum dynamic entropy models", Applied Probability 4,1 379-
390.
[2] Cai, H., Kulkarni, S. and Verdu, S. (2006): "Universal divergence
estimation for finite-alphabet sources", IEEE Transactions on
Information Theory, 52, 3456-3475.
[3] Chakrabarti, C.G. (2005): "Shannon entropy: axiomatic
characterization and application", International Journal of Mathematics
and Mathematical Sciences, 17, 2847-2854.
[4] Chen, Y. (2006): "Properties of quasi-entropy and their applications",
Journal of Southeast University Natural Sciences, 36, 222-225.
[5] Garbaczewski, P. (2006): "Differential entropy and dynamics of
uncertainty", Journal of Statistical Physics, 123, 315-355.
[6] Kapur, J.N. (1967): "Generalized entropy of order ╬▒ and type β",
Mathematics Seminar, 4, 79-84.
[7] Kapur, J.N. (1995): "Measures of Information and Their Applications",
Wiley Eastern, New York.
[8] Medhi, J.M. (1982): "Stochastic Processes", Wiley Eastern, New
Delhi.
[9] Nanda, A. K.and Paul, P. (2006): "Some results on generalized
residual entropy", Information Sciences, 176, 27-47.
[10] Paninski, L. and Yajima, M. (2008): "Undersmoothed kernel entropy
estimators", IEEE Trans. Inform.Theory, 54(9), 4384-4388.
[11] Piera, F.J. and Parade, P. (2009): "On the convergence properties of
Shannon entropy", Problemy Peredacht Informatsii, 45(2), 75-94.
[12] Shannon, C. E. (1948): "A mathematical theory of communication",
Bell System Technical Journal, 27, 379-423, 623-659.
[13] Sharma, B.D. and Taneja, I.J. (1975): "Entropies of type (╬▒,β) and
other generalized measures of information theory", Metrica, 22, 202-
215.
[14] Zyczkowski, K. (2003): "Renyi extrapolation of Shannon entropy",
Open Systems and Information Dynamics, 10, 297-310.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:55479", author = "Om Parkash and C.P.Gandhi", title = "Variation of Uncertainty in Steady And Non-Steady Processes Of Queuing Theory", abstract = "Probabilistic measures of uncertainty have been
obtained as functions of time and birth and death rates in a queuing
process. The variation of different entropy measures has been studied
in steady and non-steady processes of queuing theory.", keywords = "Uncertainty, steady state, non-steady state, trafficintensity, monotonocity", volume = "5", number = "3", pages = "350-4", }
