{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T06:14:02Z","timestamp":1784182442612,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,8,4]]},"DOI":"10.1145\/3822454.3822483","type":"proceedings-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T05:57:39Z","timestamp":1784181459000},"page":"185-192","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Neuroprocessor Noise Resilience Using HfO2-Based Synapses"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3553-9551","authenticated-orcid":false,"given":"Charles","family":"Rizzo","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, Knoxville, TN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7300-6606","authenticated-orcid":false,"given":"Jeelka","family":"Solanki","sequence":"additional","affiliation":[{"name":"Department of Nanoscale Science &amp; Engineering, University at Albany, Albany, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0629-9640","authenticated-orcid":false,"given":"Soumya Swaraj","family":"Mondal","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4345-3627","authenticated-orcid":false,"given":"Nathaniel","family":"Cady","sequence":"additional","affiliation":[{"name":"Department of Nanoscale Science &amp; Engineering, University at Albany, Albany, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4264-8097","authenticated-orcid":false,"given":"Catherine","family":"Schuman","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Knoxville, TN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9841-6076","authenticated-orcid":false,"given":"James","family":"Plank","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, Knoxville, TN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3070-4087","authenticated-orcid":false,"given":"Garrett","family":"Rose","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Knoxville, TN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2548-8754","authenticated-orcid":false,"given":"Hritom","family":"Das","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,8,4]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"D. Auge J. Hille E. Mueller and A. Knoll. 2021. A survey of encoding techniques for signal processing in spiking neural networks. Neural Processing Letters 53 6 (2021) 4693\u20134710.","DOI":"10.1007\/s11063-021-10562-2"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"crossref","unstructured":"A.\u00a0G. Barto R.\u00a0S. Sutton and C.\u00a0W. Anderson. 2012. Neuronlike adaptive elements that can solve difficult learning control problems. IEEE transactions on systems man and cybernetics5 (2012) 834\u2013846.","DOI":"10.1109\/TSMC.1983.6313077"},{"key":"e_1_3_3_1_4_2","unstructured":"R. Bock. 2004. MAGIC Gamma Telescope. UCI Machine Learning Repository. DOI: https:\/\/doi.org\/10.24432\/C52C8B."},{"key":"e_1_3_3_1_5_2","unstructured":"G. Brockman V. Cheung L. Pettersson J. Schneider J. Schulman J. Tang and W. Zaremba. 2016. Openai gym. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1606.01540 (2016)."},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"Hritom Das Rocco\u00a0D Febbo Charles\u00a0P Rizzo Nishith\u00a0N Chakraborty James\u00a0S Plank and Garrett\u00a0S Rose. 2023. Optimizations for a current-controlled memristor-based neuromorphic synapse design. IEEE Journal on Emerging and Selected Topics in Circuits and Systems 13 4 (2023) 889\u2013900.","DOI":"10.1109\/JETCAS.2023.3312163"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"crossref","unstructured":"Hritom Das Rocco\u00a0D Febbo Sree Nirmillo\u00a0Biswash Tushar Nishith\u00a0N Chakraborty Maximilian Liehr Nathaniel\u00a0C Cady and Garrett\u00a0S Rose. 2023. An efficient and accurate memristive memory for array-based spiking neural networks. IEEE Transactions on Circuits and Systems I: Regular Papers 70 12 (2023) 4804\u20134815.","DOI":"10.1109\/TCSI.2023.3301020"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"crossref","unstructured":"Hritom Das Karan\u00a0P Patel Rocco\u00a0D Febbo Catherine\u00a0D Schuman and Garrett\u00a0S Rose. 2025. Leveraging stochasticity in memristive synapses for efficient and reliable neuromorphic systems. npj Unconventional Computing 2 1 (2025) 3.","DOI":"10.1038\/s44335-024-00017-x"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"Hritom Das Catherine Schuman Nishith\u00a0N Chakraborty and Garrett\u00a0S Rose. 2024. Enhanced read resolution in reconfigurable memristive synapses for spiking neural networks. Scientific Reports 14 1 (2024) 8897.","DOI":"10.1038\/s41598-024-58947-2"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"crossref","unstructured":"B. Efron T. Hastie I. Johnstone and R. Tibshirani. 2004. Least angle regression. (2004).","DOI":"10.1214\/009053604000000067"},{"key":"e_1_3_3_1_11_2","unstructured":"R.\u00a0A. Fisher. 1936. Iris. UCI Machine Learning Repository. DOI: https:\/\/doi.org\/10.24432\/C56C76."},{"key":"e_1_3_3_1_12_2","unstructured":"A.\u00a0Z. Foshie J.\u00a0S. Plank G.\u00a0S. Rose and C.\u00a0D. Schuman. 2023. Functional Specification of the RAVENS Neuroprocessor. arXiv:2307.15232. doi:10.48550\/ARXIV.2307.15232"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICONS69015.2025.00019"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/MDTS54894.2022.9826924"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3354265.3354271"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/IIRW49815.2020.9312855"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICONS69015.2025.00040"},{"key":"e_1_3_3_1_18_2","volume-title":"IEEE International Conference on Rebooting Computing (ICRC)","author":"Plank J.\u00a0S.","year":"2024","unstructured":"J.\u00a0S. Plank, K.\u00a0E.\u00a0M. Dent, B. Gullett, C.\u00a0P. Rizzo, and C.\u00a0D. Schuman. 2024. The RISP Neuroprocessor \u2013 Open Source Support for Embedded Neuromorphic Computing. In IEEE International Conference on Rebooting Computing (ICRC). San Diego."},{"key":"e_1_3_3_1_19_2","volume-title":"44th Annual GOMACTech Conference","author":"Plank J.\u00a0S.","year":"2019","unstructured":"J.\u00a0S. Plank, C. Rizzo, K. Shahat, G. Bruer, T. Dixon, M. Goin, G. Zhao, J. Anantharaj, C.\u00a0D. Schuman, M.\u00a0E. Dean, G.\u00a0S. Rose, N.\u00a0C. Cady, and J. Van Nostrand. 2019. The TENNLab Suite of LIDAR-Based Control Applications for Recurrent, Spiking, Neuromorphic Systems. In 44th Annual GOMACTech Conference. Albuquerque. http:\/\/neuromorphic.eecs.utk.edu\/raw\/files\/publications\/2019-Plank-Gomac.pdf"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"J.\u00a0S. Plank C.\u00a0P. Rizzo C.\u00a0A. White and C.\u00a0D. Schuman. 2025. The Cart-Pole Application as a Benchmark for Neuromorphic Computing. Journal of Low Power Electronics and Applications 15 1 (2025) 1\u201327. doi:10.3390\/jlpea15010005","DOI":"10.3390\/jlpea15010005"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"crossref","unstructured":"J.\u00a0S. Plank C.\u00a0D. Schuman G. Bruer M.\u00a0E. Dean and G.\u00a0S. Rose. 2018. The TENNLab Exploratory Neuromorphic Computing Framework. IEEE Letters of the Computer Society 1 2 (July-Dec 2018) 17\u201320. doi:10.1109\/LOCS.2018.2885976","DOI":"10.1109\/LOCS.2018.2885976"},{"key":"e_1_3_3_1_22_2","unstructured":"J.\u00a0S. Plank C. Zheng B. Gullett N. Skuda C. Rizzo C.\u00a0D. Schuman and G.\u00a0S. Rose. 2022. The Case for RISP: A Reduced Instruction Spiking Processor. arXiv:2206.14016. arXiv:https:\/\/arXiv.org\/abs\/2206.14016https:\/\/arxiv.org\/abs\/2206.14016"},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"crossref","unstructured":"Mingyi Rao Hao Tang Jiangbin Wu Wenhao Song Max Zhang Wenbo Yin Ye Zhuo Fatemeh Kiani Benjamin Chen Xiangqi Jiang et\u00a0al. 2023. Thousands of conductance levels in memristors integrated on CMOS. Nature 615 7954 (2023) 823\u2013829.","DOI":"10.1038\/s41586-023-05759-5"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"crossref","unstructured":"C. Rizzo B. Gullett A. Crumley M. Marcum M. Hyman C. Earheart-Brown J. Steed F. Standaert C. Schuman and J.\u00a0S. Plank. 2025. NeuroPong: The event-based camera driven embedded neuromorphic system. Neuromorphic Computing and Engineering (2025). doi:10.1088\/2634-4386\/add0db","DOI":"10.1088\/2634-4386\/add0db"},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICONS69015.2025.00026"},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/3381755.3381758"},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3546790.3546792"},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"crossref","unstructured":"T. Serrano-Gotarredona T. Masquelier T. Prodromakis G. Indiveri and B. Linares-Barranco. 2013. STDP and STDP variations with memristors for spiking neuromorphic learning systems. Frontiers in neuroscience 7 (2013) 2.","DOI":"10.3389\/fnins.2013.00002"},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/MDTS58049.2023.10168152"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICONS62911.2024.00038"}],"event":{"name":"ICONS '26: International Conference on Neuromorphic Systems","location":"Chicago USA","acronym":"ICONS 2026","sponsor":["SIGDA ACM Special Interest Group on Design Automation","SIGAI ACM Special Interest Group on Artificial Intelligence"]},"container-title":["Proceedings of the International Conference on Neuromorphic Systems"],"original-title":[],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T05:58:13Z","timestamp":1784181493000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3822454.3822483"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,4]]},"references-count":29,"alternative-id":["10.1145\/3822454.3822483","10.1145\/3822454"],"URL":"https:\/\/doi.org\/10.1145\/3822454.3822483","relation":{},"subject":[],"published":{"date-parts":[[2026,8,4]]},"assertion":[{"value":"2026-08-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}