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• W2065892713 abstract "Within Brain-Machine Interface systems, cortically implanted microelectrode arrays and associated hardware have a low power budget for data sampling, processing and transmission. It is already possible to reduce neural data rates by on-site spike detection; we propose a method to further compress spiking data at a low computational cost, with the objective of maintaining clustering and classification abilities. The method relies on random binary vector projections, and simulations show that it is possible to achieve a compression ratio of 5 at virtually no cost in terms of classification errors." @default.
• W2065892713 created "2016-06-24" @default.
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• W2065892713 date "2012-08-01" @default.
• W2065892713 modified "2023-10-13" @default.
• W2065892713 title "Low-cost intracortical spiking recordings compression with classification abilities for implanted BMI devices" @default.
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• W2065892713 doi "https://doi.org/10.1109/embc.2012.6346502" @default.
• W2065892713 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23366463" @default.
• W2065892713 hasPublicationYear "2012" @default.
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