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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Learning automata based energy-efficient AI hardware design for IoT applications.

Adrian Wheeldon1, Rishad Shafik1, Tousif Rahman1

  • 1Microsystems Group, School of Engineering Newcastle University, Newcastle upon Tyne NE1 7RU, UK.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|September 14, 2020
PubMed
Summary

This study introduces a novel AI hardware architecture for IoT devices, utilizing learning automata and propositional logic for enhanced energy efficiency and accuracy. The design achieves significantly lower energy consumption than current AI hardware while maintaining high performance.

Failed At:

2026-06-19T13:38:43.089418+00:00

Keywords:
Tsetlin machinesartificial intelligence hardware designenergy efficiencyneural networks

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