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Parallel Technique on Bidirectional Associative Memory Cohen-Grossberg Neural Network

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Recent Contributions to Bioinformatics and Biomedical Sciences and Engineering (BioInfoMed 2022)

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Abstract

The present paper is devoted to software analysis on applied method used on parallel technology, in particular CUDA and OpenMPI, to find stable areas of single mathematical model of Bidirectional Associative Memory (BAM) Cohen-Grossberg neural network with time-varying delays. The given type of neural networks give opportunity of modelling and study of biological problems.

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Acknowledgements

This research was funded in part by the European Regional Development Fund through the Operational Program “Science and Education for Smart Growth” under contract UNITe No BG05M2OP001–1.001–0004 (2018–2023).

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Correspondence to Ivan Torlakov .

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Stamov, G., Simeonov, S., Torlakov, I., Yaneva, M. (2023). Parallel Technique on Bidirectional Associative Memory Cohen-Grossberg Neural Network. In: Sotirov, S., Pencheva, T., Kacprzyk, J., Atanassov, K.T., Sotirova, E., Ribagin, S. (eds) Recent Contributions to Bioinformatics and Biomedical Sciences and Engineering. BioInfoMed 2022. Lecture Notes in Networks and Systems, vol 658. Springer, Cham. https://doi.org/10.1007/978-3-031-31069-0_2

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  • DOI: https://doi.org/10.1007/978-3-031-31069-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31068-3

  • Online ISBN: 978-3-031-31069-0

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