ArticlePloS one2022
Differential Hebbian learning with time-continuous signals for active noise reduction.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Dendritic heterosynaptic plasticity arises from calcium-based input learning.Communications biology · 2026Article
- Temperature stabilization with Hebbian learning using an autonomous optoelectronic dendritic unit.Frontiers of optoelectronics · 2025Article
- Hebbian Optocontrol of Cross-Modal Disruptive Reading in Increasing Acoustic Noise in an Adult with Developmental Coordination Disorder: A Case Report.Brain sciences · 2024Article
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Authors and funding
6 authors.
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Abstract
Spike timing-dependent plasticity, related to differential Hebb-rules, has become a leading paradigm in neuronal learning, because weights can grow or shrink depending on the timing of pre- and post-synaptic signals. Here we use this paradigm to reduce unwanted (acoustic) noise. Our system relies on heterosynaptic differential Hebbian learning and we show that it can efficiently eliminate noise by up to -140 dB in multi-microphone setups under various conditions. The system quickly learns, most often within a few seconds, and it is robust with respect to different geometrical microphone configurations, too. Hence, this theoretical study demonstrates that it is possible to successfully transfer differential Hebbian learning, derived from the neurosciences, into a technical domain.
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