Bioinspired random projections for robust, sparse classification
- URL: http://arxiv.org/abs/2206.09222v1
- Date: Sat, 18 Jun 2022 15:24:20 GMT
- Title: Bioinspired random projections for robust, sparse classification
- Authors: Bryn Davies and Nina Dekoninck Bruhin
- Abstract summary: Inspired by the use of random projections in biological sensing systems, we present a new algorithm for processing data in classification problems.
This is based on observations of the human brain and the fruit fly's olfactory system and involves randomly projecting data into a space of greatly increased dimension before applying a cap operation to truncate the smaller entries.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Inspired by the use of random projections in biological sensing systems, we
present a new algorithm for processing data in classification problems. This is
based on observations of the human brain and the fruit fly's olfactory system
and involves randomly projecting data into a space of greatly increased
dimension before applying a cap operation to truncate the smaller entries. This
leads to an algorithm that achieves a sparse representation with minimal loss
in classification accuracy and is also more robust in the sense that
classification accuracy is improved when noise is added to the data. This is
demonstrated with numerical experiments, which supplement theoretical results
demonstrating that the resulting signal transform is continuous and invertible,
in an appropriate sense.
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