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Original Article
An Analysis of Entropy Reduction in Digital Logic Circuits with Feedback
Sourjya Gupta1
Sumana Sikdar2
Anwesha Bose3
1 2 3 Department of Computer Science Engineering, Techno India University, Kolkata, West Bengal, India.
Published Online: September-December 2025
Pages: 258-264
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20250403041
References
1. Anderson, J. (2011), A million monkeys and Shakespeare. Significance, 8: 190-192. https://doi.org/10.1111/j.1740-9713.2011.00533.x
2. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
3. Norris, J. R. (1997). . Cambridge University Press.
4. Plemmons, R. J. (1988). Matrix Analysis (Roger A. Horn and Charles R. Johnson). SIAM Review, 30(1), 153–154. https://doi.org/10.1137/1030034
5. Jolliffe, F., & Ross, S. M. (1995). Introduction to probability models. Journal of the Royal Statistical Society Series a (Statistics in Society), 158(1), 201. https://doi.org/10.2307/2983433
6. Grimmett, G., & Stirzaker, D. (2001). Probability and random processes (3rd ed.). Oxford University Press.
7. Pakes, A. G. (1969). Some conditions for ergodicity and recurrence of Markov chains. Operations Research, 17(6), 1058-1061.
8. Breiman, L. (1960). The strong law of large numbers for a class of Markov chains. The Annals of Mathematical Statistics, 31(3), 801–803. https://doi.org/10.1214/aoms/1177705810
2. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
3. Norris, J. R. (1997). . Cambridge University Press.
4. Plemmons, R. J. (1988). Matrix Analysis (Roger A. Horn and Charles R. Johnson). SIAM Review, 30(1), 153–154. https://doi.org/10.1137/1030034
5. Jolliffe, F., & Ross, S. M. (1995). Introduction to probability models. Journal of the Royal Statistical Society Series a (Statistics in Society), 158(1), 201. https://doi.org/10.2307/2983433
6. Grimmett, G., & Stirzaker, D. (2001). Probability and random processes (3rd ed.). Oxford University Press.
7. Pakes, A. G. (1969). Some conditions for ergodicity and recurrence of Markov chains. Operations Research, 17(6), 1058-1061.
8. Breiman, L. (1960). The strong law of large numbers for a class of Markov chains. The Annals of Mathematical Statistics, 31(3), 801–803. https://doi.org/10.1214/aoms/1177705810
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