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• W4323362940 abstract "Sensor fusion is a widely exploited technique that combines data from two or more sensors to improve the accuracy to a level that cannot be achieved using a single sensor alone. Algorithms for sensor fusion are generally executed on conventional digital computing platforms; however, these algorithms impose a burden on small electrical systems with limited battery capacities and computing resources. In this study, we demonstrated an analog–digital hybrid computing platform based on an SnS2 memtransistor for energy-efficient and reconfigurable sensor fusion with a complementary filter algorithm. We experimentally verified that the power consumption of our hybrid computing-based complementary filter is only half that of the traditional software-based complementary filter, even with the same accuracy." @default.
• W4323362940 created "2023-03-08" @default.
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• W4323362940 date "2023-05-01" @default.
• W4323362940 modified "2023-10-07" @default.
• W4323362940 title "Energy-efficient and reconfigurable complementary filter based on analog–digital hybrid computing with SnS2 memtransistor" @default.
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• W4323362940 doi "https://doi.org/10.1016/j.nanoen.2023.108333" @default.
• W4323362940 hasPublicationYear "2023" @default.
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