Abstract
An approach for automatic formation of the structure of the Hopfield neural network model and its training (parameter settings) for solving systems of linear algebraic equations (SLAE) of arbitrary order is proposed. Adapted for solving of SLAE model of network is configured automatically in the environment for modeling Simulink, interacting with the Matlab computing system, which allows the user to vary the input data (order, constants vector and coefficients matrix system of linear algebraic equations). The results of research on the quality of the finding for solutions to SLAEs are presented.
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References
Ph. D. Wasserman Neural Computing: Theory and Practice, p. 230. Coriolis Group (1989)
Jain, A.K., Mao, J., Mohiuddin, K.M.: Artificial neural networks: a tutorial. IEEE Comput. 29(3), 31–44 (1996)
Baranovskiy, A.M., Dorozhko, I.V., Krasilo, D.P., Kobzarev, S.A.: Hopfield neural network model for solving systems of linear algebraic equations. Certificate of registration of a computer program. Request no. 2015611642 (2015)
Baranovskiy, A.M., Silantyev, S.B., Smolitsky, K., Yafrakov, M.F., Bubnov, V.P.: Synthesis of a neural-like Hopfield network for solving systems of linear algebraic equations. Proc. High. Educ. Inst. Instrum. 37(3–4), 47–51 (1994)
Akilova, I.M.: Neuroinformatics. Amur State University Press. Blagoveshchensk, p. 158 (2007)
Seidel method online. https://math.semestr.ru/optim/zeidel.php. Accessed 10 Nov 2020
Simple iteration method online. https://math.semestr.ru/optim/iter.php. Accessed 10 Nov 2020
Module «NM Stick». https://www.module.ru/products/2-moduli/nm-stick. Accessed 15 Nov 2020
Dmitriev, A.K., Yusupov, R.M.: Identification and technical diagnostics, p. 512. VIKKI (1987)
Baranovskiy, A.M.: Method of active identification of dynamic systems. Methods and algorithms for research and development of automatic control systems, pp. 50–54. VIKKI (1989)
Baranovskiy, A.M.: Active identification of stabilization systems. Proc. High. Educ. Inst. Instrum. 40(8), 31–34 (1997)
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Gluhov, A., Baranovskiy, A., Fomenko, Y., Bochkov, A. (2021). Adapted Model Neural-Like Hopfield Network and the Algorithm of Its Training for Finding the Roots Systems of Linear Algebraic Equations. In: Silhavy, R. (eds) Artificial Intelligence in Intelligent Systems. CSOC 2021. Lecture Notes in Networks and Systems, vol 229. Springer, Cham. https://doi.org/10.1007/978-3-030-77445-5_36
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DOI: https://doi.org/10.1007/978-3-030-77445-5_36
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