Abstract
In recent years, the continuous Hopfield network has become the most required tool to solve quadratic problems (QP). But, it suffers from some drawbacks, such as, the initial states. This later affect the convergence to the optimal solution and if a bad starting point is arbitrarily specified, the infeasible solution is generated. In this paper, we examine this issue and try to provide a new technique to choose a good starting point in order to give a good optimal solution for any quadratic problems (QP). Numerical simulations are provided to demonstrate the performance of this new technique applied to task assignment problems.
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Haddouch, K., El Moutaouakil, K. (2018). New Starting Point of the Continuous Hopfield Network. In: Tabii, Y., Lazaar, M., Al Achhab, M., Enneya, N. (eds) Big Data, Cloud and Applications. BDCA 2018. Communications in Computer and Information Science, vol 872. Springer, Cham. https://doi.org/10.1007/978-3-319-96292-4_30
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DOI: https://doi.org/10.1007/978-3-319-96292-4_30
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