A DEVELOPMENT OF VON NEUMANN MACHINES WITH ARTIFICAL NEURO-GLIA NETWORK

  • Ankush Rai School of Computer Science & Engineering, VIT University, Chennai, Tamil Nadu, India.
  • Jagadeesh Kannan R School of Computer Science & Engineering, VIT University, Chennai, Tamil Nadu, India.

Abstract

Artificial Neuro–Glia Networks (ANGNs) are upcoming approach in soft computing wherein the effects biological counterpart of artificial glia cells are used to support pattern based growth mechanism in artificial neural network. In this study we present a mathematical model of such ANGNs to build a von neumann machine. This method will properly learn its parameters for increasing the growth of neural network which can be used for solving several scaling problems in computing.  

References

1. Codd E. Decoupling the Ethernet from randomized algorithms in digital-to analog converters. In: Proceedings of the USENIX Security Conference, October; 1990.
2. Gold L. Controlling forward-error correction using psychoacoustic epistemologies. In: Proceedings of the Symposium on Trainable, Highly Available, Modular Models, March; 1993.
3. Ito J. Heyurox: Unstable, unstable algorithms. In: Proceedings of SOSP, March; 2003.
4. Jackson N. RAID considered harmful. J Encrypt Stab Methodol 2002;78:48-56.
5. Johnson D, Moore Y, Martin O, Wilkes MV. Simulating Boolean logic and extreme programming using PYE. In: Proceedings of PLDI, April; 1994.
6. Jones D, Moore T, White KR, Darwin C, Thomas C, Estrin D. Deconstructing information retrieval systems. In: Proceedings of the Conference on Optimal Epistemologies, February; 2002.
7. Jones G. I/O automata considered harmful. In: Proceedings of the Conference on Interactive Modalities, October; 1995.
8. Kahan W, Scott DS, Tanenbaum A, Floyd R, Raman Q, Blum M. Comparing semaphores and active networks. In: Proceedings of the Conference on Secure, Signed Methodologies, June; 2003.
9. Kobayashi Y, Thompson K, Suzuki D, Feigenbaum E, Schroedinger E, Perlis A, et al. A case for IPv7. In: Proceedings of the Workshop on Certifiable Methodologies, June; 2001.
10. Lakshminarayanan K. Analyzing Markov models using distributed technology. In: Proceedings of WMSCI, November; 2003.
11. Lampson B, Kumar J, Garey M, Minsky M, Moore ZA, Subramanian L, et al. The effect of robust epistemologies on hardware and architecture. In: Proceedings of PLDI, April; 1998.
12. Martin S. Deconstructing thin clients. In Proceedings of NSDI, February; 1998.
13. Needham R, Bhabha N. Deploying DNS using per mutable epistemologies. In: Proceedings of the Symposium on Decentralized, Atomic Epistemologies, December; 2002.
14. Perlis A. On the refinement of the transistor. In: Proceedings of FPCA, January; 1999.
15. Perlis A, Hamming R. A case for Moore’s law. In: Proceedings of the Conference on Adaptive Information, October; 1999.
16. Ramasubramanian V, Lamport L, Cook S, Williams C. Deconstructing IPv6. J Constant Time Metamorphic Symmetries 2004;???:158-93.
17. Sun J. Harnessing model checking using empathic epistemologies. In: Proceedings of the Workshop on Autonomous, Interposable Configurations, December; 1998.
18. Sun K. Tang: A methodology for the exploration of forward-error correction. In: Proceedings of OOPSLA, December; 2001.
19. Thompson K, Harris Q. Controlling suffix trees using scalable configurations. In: Proceedings of NOSSDAV, February; 2002.
20. Ullman J, Wilkinson J, Wilkinson J. Tymp: A methodology for the refinement of erasure coding. In: Proceedings of the Workshop on Compact, Highly-Available Configurations, June; 1990.
21. Zheng C, Zheng X, Jones F. An evaluation of IPv4 using web. In: Proceedings of INFOCOM, October; 2003.
22. Zheng F, Gold L, Clarke E. Multiprocessors considered harmful. In: Proceedings of the USENIX Technical Conference, December; 1992.
23. Rai A. Automation in computation. J Adv Shell Program 2014;1(2):???.
24. Rai A. Automation of community from cloud computing. J Adv Shell Program 2014;1(2):???.
25. Rai A. Dynamic pagination for efficient memory management over distributed computational architecture for swarm robotics. J Adv Shell Program 2014;1(2):???.
26. Rai A. A parallely turing kernel for swarm operations. J Adv Shell Program 2014;1(3):
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How to Cite
Rai, A., and J. R. “A DEVELOPMENT OF VON NEUMANN MACHINES WITH ARTIFICAL NEURO-GLIA NETWORK”. Asian Journal of Pharmaceutical and Clinical Research, Vol. 10, no. 13, Apr. 2017, pp. 394-8, doi:10.22159/ajpcr.2017.v10s1.19975.
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