I. Messaris, A. Ascoli, D. Prousalis, V. Ntinas, A. S. Demirkol, R. Tetzlaff
{"title":"忆阻器细胞非线性网络中的多任务处理和Memcomputing:对潜在机制的洞察","authors":"I. Messaris, A. Ascoli, D. Prousalis, V. Ntinas, A. S. Demirkol, R. Tetzlaff","doi":"10.1109/SMACD58065.2023.10192210","DOIUrl":null,"url":null,"abstract":"Memristor Cellular Nonlinear Networks (M-CNNs) represent a significant leap in computational technology compared to traditional Cellular Nonlinear Networks (CNNs), thanks to their multi-tasking and memcomputing capabilities. Recent studies have demonstrated various configurations of M-CNNs that utilize these capabilities to perform image processing tasks. This paper employs the Dynamic Route Map circuit-theoretic analysis tool to investigate the dynamic features of M-CNNs and shed light on the underlying mechanisms responsible for their ability to handle multiple tasks. The findings from this theoretical study offer valuable insights for the development of more compact and highly efficient data processing M-CNNs that possess such versatile properties.","PeriodicalId":239306,"journal":{"name":"2023 19th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)","volume":"333 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multitasking and Memcomputing in Memristor Cellular Nonlinear Networks: Insights into the Underlying Mechanisms\",\"authors\":\"I. Messaris, A. Ascoli, D. Prousalis, V. Ntinas, A. S. Demirkol, R. Tetzlaff\",\"doi\":\"10.1109/SMACD58065.2023.10192210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Memristor Cellular Nonlinear Networks (M-CNNs) represent a significant leap in computational technology compared to traditional Cellular Nonlinear Networks (CNNs), thanks to their multi-tasking and memcomputing capabilities. Recent studies have demonstrated various configurations of M-CNNs that utilize these capabilities to perform image processing tasks. This paper employs the Dynamic Route Map circuit-theoretic analysis tool to investigate the dynamic features of M-CNNs and shed light on the underlying mechanisms responsible for their ability to handle multiple tasks. The findings from this theoretical study offer valuable insights for the development of more compact and highly efficient data processing M-CNNs that possess such versatile properties.\",\"PeriodicalId\":239306,\"journal\":{\"name\":\"2023 19th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)\",\"volume\":\"333 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 19th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMACD58065.2023.10192210\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 19th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMACD58065.2023.10192210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multitasking and Memcomputing in Memristor Cellular Nonlinear Networks: Insights into the Underlying Mechanisms
Memristor Cellular Nonlinear Networks (M-CNNs) represent a significant leap in computational technology compared to traditional Cellular Nonlinear Networks (CNNs), thanks to their multi-tasking and memcomputing capabilities. Recent studies have demonstrated various configurations of M-CNNs that utilize these capabilities to perform image processing tasks. This paper employs the Dynamic Route Map circuit-theoretic analysis tool to investigate the dynamic features of M-CNNs and shed light on the underlying mechanisms responsible for their ability to handle multiple tasks. The findings from this theoretical study offer valuable insights for the development of more compact and highly efficient data processing M-CNNs that possess such versatile properties.