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- W576719102 abstract "Wireless Sensor Network (WSN) is an emerging technology that has revolutionized the whole world. This paper proposes an artificial neural network model for a reliable and fault-tolerant WSN based on an exponential Bi-directional Associative Memory (eBAM). An eBAM has higher capacity for pattern pair storage than the conventional BAMs. The proposed model strives to improve the fault tolerance and reliability of packet delivery in WSN by transmitting small-sized packets called vectors. The vectors are associated with the original large-sized packets after encoding the associations between the hetero-associative vectors for the given problem space. This encoding is done by the application of the evolution equations of an eBAM. The performance characteristics of the proposed model are compared with other BAM models through simulation." @default.
- W576719102 created "2016-06-24" @default.
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- W576719102 date "2015-01-01" @default.
- W576719102 modified "2023-10-09" @default.
- W576719102 title "An ANN Approach for Fault Tolerant Wireless Sensor Networks" @default.
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- W576719102 doi "https://doi.org/10.1007/978-3-319-13731-5_52" @default.
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