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Analogue and Physical Reservoir Computing Using Water Waves

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arxiv 2306.09095 v1 pith:MNT7C4PK submitted 2023-06-15 physics.flu-dyn cs.AInlin.CDnlin.PS

classification physics.flu-dyncs.AInlin.CDnlin.PS
keywords wateranaloguecomputingreservoircitiesenergylargepeople
verification ladder T0 review T1 audit T2 compute T3 formal
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More than 3.5 billion people live in rural areas, where water and water energy resources play an important role in ensuring sustainable and productive rural economies. This article reviews and critically analyses the recent advances in the field of analogue and reservoir computing that have been driven by unique physical properties and energy of water waves. It also demonstrates that analogue and reservoir computing hold the potential to bring artificial intelligence closer to people living outside large cities, thus enabling them to enjoy the benefits of novel technologies that already work in large cities but are not readily available and suitable for regional communities.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Traveling Waves Integrate Spatial Information Through Time

    cs.CV 2025-02 conditional novelty 7.0 of 10

    Wave-producing recurrent neural networks with time-series readouts outperform local feed-forward models and rival larger U-Nets on semantic segmentation.

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