{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T16:02:08Z","timestamp":1781884928328,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,7,27]],"date-time":"2022-07-27T00:00:00Z","timestamp":1658880000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["16ES0992K"],"award-info":[{"award-number":["16ES0992K"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,7,27]]},"DOI":"10.1145\/3546790.3546816","type":"proceedings-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:10:51Z","timestamp":1662610251000},"page":"1-4","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Resonate-and-Fire Neurons for Radar Interference Detection"],"prefix":"10.1145","author":[{"given":"Julian","family":"Hille","sequence":"first","affiliation":[{"name":"Technical University of Munich, Germany and Infineon Technologies AG, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Auge","sequence":"additional","affiliation":[{"name":"Infineon Technologies AG, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cyprian","family":"Grassmann","sequence":"additional","affiliation":[{"name":"Infineon Technologies AG, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alois","family":"Knoll","sequence":"additional","affiliation":[{"name":"Technical University of Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,9,7]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Daniel Auge and Etienne Mueller. 2020. Resonate-and-Fire Neurons as Frequency Selective Input Encoders for Spiking Neural Networks. (2020) 8.  Daniel Auge and Etienne Mueller. 2020. Resonate-and-Fire Neurons as Frequency Selective Input Encoders for Spiking Neural Networks. (2020) 8."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEMC.2006.890223"},{"key":"e_1_3_2_1_3_1","volume-title":"ACE-SNN: Algorithm-Hardware Co-design of Energy-Efficient & Low-Latency Deep Spiking Neural Networks for 3D Image Recognition. Frontiers in Neuroscience 16 (April","author":"Datta Gourav","year":"2022","unstructured":"Gourav Datta , Souvik Kundu , Akhilesh\u00a0 R. Jaiswal , and Peter\u00a0 A. Beerel . 2022. ACE-SNN: Algorithm-Hardware Co-design of Energy-Efficient & Low-Latency Deep Spiking Neural Networks for 3D Image Recognition. Frontiers in Neuroscience 16 (April 2022 ), 815258. https:\/\/doi.org\/10.3389\/fnins.2022.815258 10.3389\/fnins.2022.815258 Gourav Datta, Souvik Kundu, Akhilesh\u00a0R. Jaiswal, and Peter\u00a0A. Beerel. 2022. ACE-SNN: Algorithm-Hardware Co-design of Energy-Efficient & Low-Latency Deep Spiking Neural Networks for 3D Image Recognition. Frontiers in Neuroscience 16 (April 2022), 815258. https:\/\/doi.org\/10.3389\/fnins.2022.815258"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/13\/5\/051001"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/2635959"},{"key":"e_1_3_2_1_6_1","volume-title":"2011 German Microwave Conference. IEEE, 1\u20134.","author":"Goppelt Markus","year":"2011","unstructured":"Markus Goppelt , Hans-Ludwig Bl\u00f6cher , and Wolfgang Menzel . 2011 . Analytical Investigation of Mutual Interference between Automotive FMCW Radar Sensors . In 2011 German Microwave Conference. IEEE, 1\u20134. Markus Goppelt, Hans-Ludwig Bl\u00f6cher, and Wolfgang Menzel. 2011. Analytical Investigation of Mutual Interference between Automotive FMCW Radar Sensors. In 2011 German Microwave Conference. IEEE, 1\u20134."},{"key":"e_1_3_2_1_7_1","volume-title":"Data Mining (thirded.), Jiawei Han, Micheline Kamber, and Jian Pei (Eds.). Morgan Kaufmann","author":"Han Jiawei","unstructured":"Jiawei Han , Micheline Kamber , and Jian Pei . 2012. 8 - Classification: Basic Concepts . In Data Mining (thirded.), Jiawei Han, Micheline Kamber, and Jian Pei (Eds.). Morgan Kaufmann , Boston , 327\u2013391. Jiawei Han, Micheline Kamber, and Jian Pei. 2012. 8 - Classification: Basic Concepts. In Data Mining (thirded.), Jiawei Han, Micheline Kamber, and Jian Pei (Eds.). Morgan Kaufmann, Boston, 327\u2013391."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/RadarConf2248738.2022.9764236"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(01)00078-8"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/PRIME55000.2022.9816777"},{"key":"e_1_3_2_1_11_1","volume-title":"Int. symp. on nonlinear theory and its applications. 82\u201385","author":"Nakada Kazuki","year":"2005","unstructured":"Kazuki Nakada , Tetsuya Asai , and Hatsuo Hayashi . 2005 . A silicon Resonate-and-fire neuron based on the volterra system . In Int. symp. on nonlinear theory and its applications. 82\u201385 . Kazuki Nakada, Tetsuya Asai, and Hatsuo Hayashi. 2005. A silicon Resonate-and-fire neuron based on the volterra system. In Int. symp. on nonlinear theory and its applications. 82\u201385."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/SiPS52927.2021.00053"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2016.2628914"},{"key":"#cr-split#-e_1_3_2_1_14_1.1","unstructured":"Christian Pehle and Jens\u00a0Egholm Pedersen. 2021. Norse - A deep learning library for spiking neural networks. https:\/\/doi.org\/10.5281\/zenodo.4422025 Documentation: https:\/\/norse.ai\/docs\/. 10.5281\/zenodo.4422025"},{"key":"#cr-split#-e_1_3_2_1_14_1.2","unstructured":"Christian Pehle and Jens\u00a0Egholm Pedersen. 2021. Norse - A deep learning library for spiking neural networks. https:\/\/doi.org\/10.5281\/zenodo.4422025 Documentation: https:\/\/norse.ai\/docs\/."},{"key":"e_1_3_2_1_15_1","volume-title":"Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals. In 2020 IEEE International Radar Conference (RADAR). IEEE, 624\u2013629","author":"Rock Johanna","year":"2020","unstructured":"Johanna Rock , Mate Toth , Paul Meissner , and Franz Pernkopf . 2020 . Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals. In 2020 IEEE International Radar Conference (RADAR). IEEE, 624\u2013629 . Johanna Rock, Mate Toth, Paul Meissner, and Franz Pernkopf. 2020. Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals. In 2020 IEEE International Radar Conference (RADAR). IEEE, 624\u2013629."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s004220050570"},{"key":"e_1_3_2_1_17_1","volume-title":"Analytical Investigation of Non-Coherent Mutual FMCW Radar Interference. In 2018 15th European Radar Conference (EuRAD). IEEE, Madrid, 71\u201374","author":"Toth Mate","year":"2018","unstructured":"Mate Toth , Paul Meissner , Alexander Melzer , and Klaus Witrisal . 2018 . Analytical Investigation of Non-Coherent Mutual FMCW Radar Interference. In 2018 15th European Radar Conference (EuRAD). IEEE, Madrid, 71\u201374 . https:\/\/doi.org\/10.23919\/EuRAD.2018.8546588 10.23919\/EuRAD.2018.8546588 Mate Toth, Paul Meissner, Alexander Melzer, and Klaus Witrisal. 2018. Analytical Investigation of Non-Coherent Mutual FMCW Radar Interference. In 2018 15th European Radar Conference (EuRAD). IEEE, Madrid, 71\u201374. https:\/\/doi.org\/10.23919\/EuRAD.2018.8546588"}],"event":{"name":"ICONS: International Conference on Neuromorphic Systems","location":"Knoxville TN USA","acronym":"ICONS"},"container-title":["Proceedings of the International Conference on Neuromorphic Systems 2022"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3546790.3546816","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3546790.3546816","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:00:40Z","timestamp":1750186840000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3546790.3546816"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,27]]},"references-count":18,"alternative-id":["10.1145\/3546790.3546816","10.1145\/3546790"],"URL":"https:\/\/doi.org\/10.1145\/3546790.3546816","relation":{},"subject":[],"published":{"date-parts":[[2022,7,27]]},"assertion":[{"value":"2022-09-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}