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Several statistical methods have been proposed for the analysis of large amounts of data, including artificial neural networks. However, the amount of energy required for the training of these models is extremely high, and the request for data storage in the cloud is even more demanding. Edge computing solutions are currently regarded as viable alternatives to mitigate this energetically unfavorable condition. Herein, a random\u2010assembled resistive switching (RS) device is reported based on a nanostructured nanocomposite Au\/ZrO\n                    <jats:sub>x<\/jats:sub>\n                    film used as a preprocessing element of a highly efficient classifier of time\u2010series. As the resistance of the device evolves in a complex way under voltage variable input, a time\u2010series statistical analysis is applied to extract the key features from the nonlinear electrical response of the nanostructured device. The potential of combining these nanocomposite RS devices is demonstrated by their ability to accurately and in real\u2010time classify neuronal traces, corresponding to physiological and evoked local field potentials and spiking activity recorded from the rat barrel cortex.\n                  <\/jats:p>","DOI":"10.1002\/aisy.202401150","type":"journal-article","created":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T05:41:42Z","timestamp":1750830102000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Highly Efficient Classification of Time\u2010Series Based on Resistive Switching Cluster\u2010Assembled Materials"],"prefix":"10.1002","volume":"7","author":[{"given":"Filippo","family":"Profumo","sequence":"first","affiliation":[{"name":"CIMAINA\u2014Interdisciplinary Centre for Nanostructured Materials and Interfaces Department of Physics \u201cAldo Pontremoli\u201d University of Milan  20133 Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6980-4910","authenticated-orcid":false,"given":"Francesca","family":"Borghi","sequence":"additional","affiliation":[{"name":"CIMAINA\u2014Interdisciplinary Centre for Nanostructured Materials and Interfaces Department of Physics \u201cAldo Pontremoli\u201d University of Milan  20133 Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tommaso","family":"Ang\u00ec","sequence":"additional","affiliation":[{"name":"CIMAINA\u2014Interdisciplinary Centre for Nanostructured Materials and Interfaces Department of Physics \u201cAldo Pontremoli\u201d University of Milan  20133 Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marta","family":"Maschietto","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, Section of Physiology University of Padova  35131 Padova Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Vassanelli","sequence":"additional","affiliation":[{"name":"NeuroChip Laboratory Department of Biomedical Sciences and Padua Neuroscience Center University of Padova Padova, Italy and ICMATE\u2010CNR  35122 Padova Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paolo","family":"Milani","sequence":"additional","affiliation":[{"name":"CIMAINA\u2014Interdisciplinary Centre for Nanostructured Materials and Interfaces Department of Physics \u201cAldo Pontremoli\u201d University of Milan  20133 Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,6,25]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2024.3443254"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1152\/physrev.00027.2016"},{"key":"e_1_2_9_4_1","volume-title":"Intelligent and Biosensors","author":"Alani T.","year":"2010"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.3389\/fenrg.2022.850252"},{"key":"e_1_2_9_6_1","first-page":"27","author":"Dao N.\u2010N.","year":"2020","journal-title":"Edge Comp. 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