Abstract
The dynamic of Hopfield network is usually described by the system of differential equations. Our idea is to modify Hopfield network in aim to allow its behavior description by the system of transcendental exponential equations solvable analytically by the Special Trans Function Theory (STFT). Furthermore, the linear approximation method to the system of transcendental exponential equations describing the modified Hopfield network, based upon the STFT, has been discussed in some details.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Juang J-C. (1999), Stability Analysis of Hopfield-Type Neural Networks, IEEE Transactions on Neural Networks, vol. 10, no. 6, pp 1336–1374
Quiao H., et al. (1999), Nonlinear Measures: A New Approach to Exponential Stability Analysis for Hopfield-Type Neural Networks, IEEE Transactions on Neural Networks, vol. 12, no. 2, pp 360–369
Kakeya H., Okabe Y. (2000), Fast combinatorial optimization with parallel digital computers, IEEE Transactions on Neural Networks, vol. 11, no. 6, pp 1323–1331
Hassoun M. H. (1995), Fundamentals of Artificial Neural Networks, The MIT Press, London
Bauk S., Perovich S. M. (2003) STFT iterative procedure for estimating probability of clients arrivals in case of M/M/l queue, SYM-OP-IS, S&M, pp 735–737
Bauk S., Perovich S. M. (2003), Procjena vjerovatnoće nastupanja otkaza primjenom teorije specijalnih trans funkcija, NSS-OMO, S&M, pp 60–63
Bauk S., Perovich S. (2004) Considering the special trans function theory approach to the probability estimation (submitted to the Statistics and Probability Letters)
Perovich S. (2004) Research monograph — The Special Trans Function Theory, University of Montenegro
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag/Wien
About this paper
Cite this paper
Bauk, S.I., Perovich, S.M., Lompar, A. (2005). The Linear Approximation Method to the Modified Hopfield Neural Network Parameters Analysis. In: Ribeiro, B., Albrecht, R.F., Dobnikar, A., Pearson, D.W., Steele, N.C. (eds) Adaptive and Natural Computing Algorithms. Springer, Vienna. https://doi.org/10.1007/3-211-27389-1_8
Download citation
DOI: https://doi.org/10.1007/3-211-27389-1_8
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-24934-5
Online ISBN: 978-3-211-27389-0
eBook Packages: Computer ScienceComputer Science (R0)