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Maria Isabel Garcia-planas



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Maria Isabel Garcia-planas


WSEAS Transactions on Systems


Print ISSN: 1109-2777
E-ISSN: 2224-2678

Volume 18, 2019

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.


Volume 18, 2019



Analyzing Controllability of Dynamical Systems Modelling Brain Neural Networks

AUTHORS: Maria Isabel Garcia-planas

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ABSTRACT: The brain structure can be modelled as a deep recurrent complex neuronal network. Networked systems are expressly interesting systems to control because of the role of the underlying architecture, which predisposes some components to particular control motions. The concept of brain cognitive control is analogous to the mathematical concept of control used in engineering, where the state of a complex system can be adjusted by a particular input. The in-depth study on the controllability character of dynamical systems, despite being very difficult, could help to regulate the brain cognitive function. small advances in the study can favour the study and action against learning difficulties such as dyscalculia or other disturbances like the phenomena of forgetting

KEYWORDS: Neural network, controllability, exact controllability, eigenvalues, eigenvectors, linear systems

REFERENCES:

[1] J. Assan, A. Lafay, A. Perdon, “Computation of maximal pre-controllability submodules over a Noetherian ring” Systems & Control Letters, vol. 2, no. 3, 1999, pp. 153–161.

[2] F. Cardetti, M. Gordina, A note on local controllability on lie groups. Systems & Control Letters, vol. 57, 2008, pp. 978–979.

[3] C.T. Chen, Introduction to Linear System Theory. Holt, Rinehart and Winston Inc, New York, 1970.

[4] M.I. Garcia-Planas. “Obtaining Consensus of Multi-agent Linear Dynamic Systems”. Advances in Applied and Pure Mathematics, 2005. pp.1–5.

[5] M.I. Garc´ıa-Planas, “Generalized Controllability Subspcaes for Time-invariant Singular Linear Systems”, Proceedings of Physcon 2011, IPACS Electronic Library, 2011.

[6] M.I. Garc´ıa-Planas, “Analyzing Controllability of Neural Networks”, Wseas Transactions on Circuits and Systems. vol. 18, 2019, pp. 1–6.

[7] M.I. Garc´ıa-Planas, “Exact Controllability of Linear Dynamical Systems: a Geometrical Approach”, Applications of Mathematics. vol. 1, 2017, pp. 37–47, DOI:10.21136/AM.2016.0427-15

[8] M.I. Garcia-Planas, J.L. Dom´ınguez, “Alternative tests for functional and pointwise outputcontrollability of linear time-invariant systems”, Systems & control letters, vol. 62, 2013, no 5, pp. 382–387.

[9] M. I. Garc´ıa-Planas, M.V. Garc´ıa-Camba Vives, M. V. Dyscalculia, mind, calculating brain and education. In EDULEARN18: 10th Annual International Conference on Education and New Learning Technologies: Palma de Mallorca, Spain: July 2-4, 2018: proceedings book, (2018). pp. 0480–0489.

[10] Sh, Gu, F. Pasqualetti, M. Cieslak, Q. K. Telesford, A. B. Yu, A. E. Kahn, J. D. Medaglia, J. M. Vettel, M. B. Miller, S. T. Grafton, D. S. Bassett. “Controllability of structural brain networks”2015. DOI: 10.1038/ncomms9414

[11] M. L. J. Hautus, “Controllability and observability conditions of linear autonomous systems”. Nederl. Akad. Wetensch. Proc. Ser. A 72 = Indag. Math. vol. 31, 1969, pp. 443–448.

[12] A. Heniche, I. Kamwa, “Using measures of controllability and observability for input and output selection”, Proceedings of the 2002 IEEE International Conference on Control Applications, vol. 2, (2002) pp. 1248–1251.

[13] R. E. Kalman, P. L. Falb and M. A. Arbib, “Topics in Mathematical Control Theory”, McGrawHill Book Co., New York-Toronto, Ont.-London 1969.

[14] N. Kriegeskorte Deep Neural Networks: “A New Framework for Modeling Biological Vision and Brain Information Processing”. Annual Review of Vision Science, vol. 1, 2015, pp. 417–46

[15] P. Kundur, Power System Stability and Control, McGraw-Hill, 1994.

[16] D. Leitold, A. Vathy-Fogarassy, J. Abonyi. “Controllability and observability in complex networks - the effect of connection types”. Scientific Reports. 2017;7(151). pmid:28273948

[17] C. Lin, Structural controllability, IEEE Trans. Automat. Contr. vol. 19, 1974, pp. 201–208.

[18] Y. Liu, J. Slotine, A. Barabasi, “Controllabil- ´ ity of complex networks ”, Nature, vol. 473, no (7346), 2011, pp. 167–173.

[19] R. Shields, J. Pearson, “Structural controllability of multi-input linear systems”. IEEE Trans. Automat. Contr, vol. 21, 1976, pp. 203–212.

[20] O. Sporns,“Graph theory methods: applications in brain networks”. Dialogues in Clinical Neuroscience, vol. 20,(2), 2018, pp. 111–120.

[21] J. Wang, D. Cheng, X. Hu, “Consensus of multiagent linear dynamics systems, Asian Journal of Control”vol. 10, (2), 2008, pp. 144–155.

[22] D. West Introduction to Graph Theory. Prentice Hall (3rd Edition), 2007.

[23] Z.Z. Yuan, C. Zhao, W.X. Wang, Z.R. Di, Y.C. Lai, “Exact controllability of multiplex networks”, New Journal of Physics, vol. 16, 2014, pp. 1–24

WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 18, 2019, Art. #38, pp. 304-312


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