Abstract
Over the last few years, neural networks with values in multidimensional domains have been intensely studied. This paper introduces octonion-valued neural networks with delay, for which the states and weights are octonions. The octonion algebra represents a non-associative normed division algebra which generalizes the complex and quaternion algebras and doesn’t fall into the category of Clifford algebras, which are associative. A sufficient criterion is derived in terms of linear matrix inequalities that ensures the existence, uniqueness, and global asymptotic stability of the equilibrium point for the proposed networks. Finally, a simulation example illustrates the effectiveness of the theoretical results.
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Popa, CA. (2017). Global Asymptotic Stability for Octonion-Valued Neural Networks with Delay. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10261. Springer, Cham. https://doi.org/10.1007/978-3-319-59072-1_52
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DOI: https://doi.org/10.1007/978-3-319-59072-1_52
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