2022/06/18 by Nina Dekoninck Bruhin, Bruhin, Nina Dekoninck, Bryn Davies +1 · 2 citations
Computer Science · Engineering · Neuroscience · #15B52 #68T01 #92C20 #94A12 #Advanced Chemical Sensor Technologies #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2206.09222
openalex publication_date 2022/06/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 a simple algorithm that is very computationally efficient and can be used to either give a sparse representation with minimal loss in classification accuracy or give improved robustness, 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.