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SPIGA, SABINA

SPIGA, SABINA  

Istituto per la Microelettronica e Microsistemi - IMM - Sede Secondaria Agrate Brianza  

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Risultati 1 - 20 di 151 (tempo di esecuzione: 0.034 secondi).
Titolo Data di pubblicazione Autore(i) File
Memristive Materials, Devices, and Systems (MEMRISYS 2023) 1-gen-2024 Ricciardi, C.; Ielmini, D.; Corinto, F.; Spiga, S.
Modeling and simulation of electrochemical and surface diffusion effects in filamentary cation-based resistive memory devices 1-gen-2024 Vaccaro, F.; Mauri, A. G.; Perotto, S.; Brivio, S.; Spiga, S.
Roadmap to neuromorphic computing with emerging technologies 1-gen-2024 Mehonic, A.; Ielmini, D.; Roy, K.; Mutlu, O.; Kvatinsky, S.; Serrano-Gotarredona, T.; Linares-Barranco, B.; Spiga, S.; Savel'Ev, S.; Balanov, A. G.; Chawla, N.; Desoli, G.; Malavena, G.; Monzio Compagnoni, C.; Wang, Z.; Yang, J. J.; Sarwat, S. G.; Sebastian, A.; Mikolajick, T.; Slesazeck, S.; Noheda, B.; Dieny, B.; Hou, T. -H.; Varri, A.; Bruckerhoff-Pluckelmann, F.; Pernice, W.; Zhang, X.; Pazos, S.; Lanza, M.; Wiefels, S.; Dittmann, R.; Ng, W. H.; Buckwell, M.; Cox, H. R. J.; Mannion, D. J.; Kenyon, A. J.; Lu, Y.; Yang, Y.; Querlioz, D.; Hutin, L.; Vianello, E.; Chowdhury, S. S.; Mannocci, P.; Cai, Y.; Sun, Z.; Pedretti, G.; Strachan, J. P.; Strukov, D.; Le Gallo, M.; Ambrogio, S.; Valov, I.; Waser, R.
Unraveling the roles of switching and relaxation times in volatile electrochemical memristors to mimic neuromorphic dynamical features 1-gen-2024 Dutta, Mrinmoy; Brivio, Stefano; Spiga, Sabina
Chua’s Circuit With Tunable Nonlinearity Based on a Nonvolatile Memristor: Design and Realization 1-gen-2023 Escudero, Manuel; Spiga, Sabina; Marco, Mauro Di; Forti, Mauro; Innocenti, Giacomo; Tesi, Alberto; Corinto, Fernando; Brivio, Stefano
Noise induced oscillations in a second order circuit with nonvolatile memristor 1-gen-2023 Bonnin, M.; Song, K.; Corinto, F.; Bonani, F.; Traversa, F. L.; Escudero Lopez, M.; Brivio, S.; Spiga, S.
SHIP: a computational framework for simulating and validating novel technologies in hardware spiking neural networks 1-gen-2023 Gemo, Emanuele; Spiga, Sabina; Brivio, Stefano
The 2022 applied physics by pioneering women: a roadmap 1-gen-2023 Abad, B.; Alberi, K.; Ayers, K. E.; Badhulika, S.; Ban, C.; Bea, H.; Beron, F.; Cairney, J.; Chang, J. P.; Charles, C.; Creatore, M.; Dong, H.; Du, J.; Egan, R.; Everschor-Sitte, K.; Foley, C.; Fontcuberta i Morral, A.; Jung, M. -H.; Kim, H.; Kurtz, S.; Lee, J.; Leitao, D. C.; Lemmer, K.; Marschilok, A. C.; Mitu, B.; Newman, B. K.; Owens, R.; Pappa, A. -M.; Park, Y.; Peckham, M.; Rossi, L. M.; Shim, S. -H.; Siddiqui, S. A.; Son, J. -W.; Spiga, S.; Tsikata, S.; Vianello, E.; Wilson, K.; Yuasa, H.; Zardo, I.; Zenyuk, I.; Zhang, Y.; Zhao, Y.
2022 roadmap on neuromorphic computing and engineering 1-gen-2022 Christensen, D. V.; Dittmann, R.; Linares-Barranco, B.; Sebastian, A.; Le Gallo, M.; Redaelli, A.; Slesazeck, S.; Mikolajick, T.; Spiga, S.; Menzel, S.; Valov, I.; Milano, G.; Ricciardi, C.; Liang, S. -J.; Miao, F.; Lanza, M.; Quill, T. J.; Keene, S. T.; Salleo, A.; Grollier, J.; Markovic, D.; Mizrahi, A.; Yao, P.; Yang, J. J.; Indiveri, G.; Strachan, J. P.; Datta, S.; Vianello, E.; Valentian, A.; Feldmann, J.; Li, X.; Pernice, W. H. P.; Bhaskaran, H.; Furber, S.; Neftci, E.; Scherr, F.; Maass, W.; Ramaswamy, S.; Tapson, J.; Panda, P.; Kim, Y.; Tanaka, G.; Thorpe, S.; Bartolozzi, C.; Cleland, T. A.; Posch, C.; Liu, S.; Panuccio, G.; Mahmud, M.; Mazumder, A. N.; Hosseini, M.; Mohsenin, T.; Donati, E.; Tolu, S.; Galeazzi, R.; Christensen, M. E.; Holm, S.; Ielmini, D.; Pryds, N.
Atomic Defects Profiling and Reliability of Amorphous Al2O3Metal-Insulator-Metal Stacks 1-gen-2022 Torraca, P La; Caruso, F; Padovani, A; Tallarida, G; Spiga, S; Larcher, L
Hardware calibrated learning to compensate heterogeneity in analog RRAM-based Spiking Neural Networks 1-gen-2022 Moro, F.; Esmanhotto, E.; Hirtzlin, T.; Castellani, N.; Trabelsi, A.; Dalgaty, T.; Molas, G.; Andrieu, F.; Brivio, S.; Spiga, S.; Indiveri, G.; Payvand, M.; Vianello, E.
HfO2-based resistive switching memory devices for neuromorphic computing 1-gen-2022 Brivio, S.; Spiga, S.; Ielmini, D.
Improving HfO2-Based Resistive Switching Devices by Inserting a TaOxThin Film via Engineered In Situ Oxidation 1-gen-2022 Wang, T.; Brivio, S.; Cianci, E.; Wiemer, C.; Perego, M.; Spiga, S.; Lanza, M.
MOx materials by ALD method 1-gen-2022 Cianci, E.; Spiga, S.
Physical Implementation of a Tunable Memristor-based Chua's Circuit 1-gen-2022 Escudero Lopez, Manuel; Spiga, S.; Di Marco, M.; Forti, Mauro; Innocenti, G.; Tesi, A.; Corinto, F.; Brivio, S.
Physics-based compact modelling of the analog dynamics of HfOx resistive memories 1-gen-2022 Vaccaro, F.; Brivio, S.; Perotto, S.; Mauri, A. G.; Spiga, S.
The electrons' journey in thick metal oxides 1-gen-2022 Caruso, F.; La Torraca, P.; Larcher, L.; Tallarida, G.; Spiga, S.
Extraction of Defects Properties in Dielectric Materials From I-V Curve Hysteresis 1-gen-2021 Torraca, P La; Caruso, F; Padovani, A; Spiga, S; Tallarida, G; Larcher, L
Non-linear Memristive Synaptic Dynamics for Efficient Unsupervised Learning in Spiking Neural Networks 1-gen-2021 Brivio, Stefano; Ly Denys, Rb; Vianello, Elisa; Spiga, Sabina
Standards for the Characterization of Endurance in Resistive Switching Devices 1-gen-2021 Lanza, M.; Waser, R.; Ielmini, D.; Yang, J. J.; Goux, L.; Sune, J.; Kenyon, A. J.; Mehonic, A.; Spiga, S.; Rana, V.; Wiefels, S.; Menzel, S.; Valov, I.; Villena, M. A.; Miranda, E.; Jing, X.; Campabadal, F.; Gonzalez, M. B.; Aguirre, F.; Palumbo, F.; Zhu, K.; Roldan, J. B.; Puglisi, F. M.; Larcher, L.; Hou, T. -H.; Prodromakis, T.; Yang, Y.; Huang, P.; Wan, T.; Chai, Y.; Pey, K. L.; Raghavan, N.; Duenas, S.; Wang, T.; Xia, Q.; Pazos, S.