Stochastic model of memristor based on the length of conductive region

We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does no...
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Autor*in:	Agudov, N.V. [verfasserIn] Dubkov, A.A. [verfasserIn] Safonov, A.V. [verfasserIn] Krichigin, A.V. [verfasserIn] Kharcheva, A.A. [verfasserIn] Guseinov, D.V. [verfasserIn] Koryazhkina, M.N. [verfasserIn] Novikov, A.S. [verfasserIn] Shishmakova, V.A. [verfasserIn] Antonov, I.N. [verfasserIn] Carollo, A. [verfasserIn] Spagnolo, B. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Memristor Stochasticity Resistive switching Yttria stabilized zirconia

Übergeordnetes Werk:	Enthalten in: Chaos, solitons & fractals - Amsterdam [u.a.] : Elsevier Science, 1991, 150
Übergeordnetes Werk:	volume:150

DOI / URN:	10.1016/j.chaos.2021.111131

Katalog-ID:	ELV006377041

Internformat


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245	1	0	\|a Stochastic model of memristor based on the length of conductive region
264		1	\|c 2021
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520			\|a We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching.
650		4	\|a Memristor
650		4	\|a Stochasticity
650		4	\|a Resistive switching
650		4	\|a Yttria stabilized zirconia
700	1		\|a Dubkov, A.A. \|e verfasserin \|4 aut
700	1		\|a Safonov, A.V. \|e verfasserin \|4 aut
700	1		\|a Krichigin, A.V. \|e verfasserin \|4 aut
700	1		\|a Kharcheva, A.A. \|e verfasserin \|4 aut
700	1		\|a Guseinov, D.V. \|e verfasserin \|4 aut
700	1		\|a Koryazhkina, M.N. \|e verfasserin \|4 aut
700	1		\|a Novikov, A.S. \|e verfasserin \|4 aut
700	1		\|a Shishmakova, V.A. \|e verfasserin \|4 aut
700	1		\|a Antonov, I.N. \|e verfasserin \|4 aut
700	1		\|a Carollo, A. \|e verfasserin \|4 aut
700	1		\|a Spagnolo, B. \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Chaos, solitons & fractals \|d Amsterdam [u.a.] : Elsevier Science, 1991 \|g 150 \|h Online-Ressource \|w (DE-627)314118497 \|w (DE-600)2003919-0 \|w (DE-576)094504040 \|x 1873-2887 \|7 nnns
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912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
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912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
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912			\|a GBV_ILN_4251
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912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
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912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
936	b	k	\|a 30.20 \|j Nichtlineare Dynamik
936	b	k	\|a 31.00 \|j Mathematik: Allgemeines
951			\|a AR
952			\|d 150

Indexfelder

author_variant	n a na a d ad a s as a k ak a k ak d g dg m k mk a n an v s vs i a ia a c ac b s bs
matchkey_str	article:18732887:2021----::tcatcoeommitraeoteeghf
hierarchy_sort_str	2021
bklnumber	30.20 31.00
publishDate	2021
allfields	10.1016/j.chaos.2021.111131 doi (DE-627)ELV006377041 (ELSEVIER)S0960-0779(21)00485-9 DE-627 ger DE-627 rda eng 510 DE-600 30.20 bkl 31.00 bkl Agudov, N.V. verfasserin (orcid)0000-0003-1767-0118 aut Stochastic model of memristor based on the length of conductive region 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching. Memristor Stochasticity Resistive switching Yttria stabilized zirconia Dubkov, A.A. verfasserin aut Safonov, A.V. verfasserin aut Krichigin, A.V. verfasserin aut Kharcheva, A.A. verfasserin aut Guseinov, D.V. verfasserin aut Koryazhkina, M.N. verfasserin aut Novikov, A.S. verfasserin aut Shishmakova, V.A. verfasserin aut Antonov, I.N. verfasserin aut Carollo, A. verfasserin aut Spagnolo, B. verfasserin aut Enthalten in Chaos, solitons & fractals Amsterdam [u.a.] : Elsevier Science, 1991 150 Online-Ressource (DE-627)314118497 (DE-600)2003919-0 (DE-576)094504040 1873-2887 nnns volume:150 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 30.20 Nichtlineare Dynamik 31.00 Mathematik: Allgemeines AR 150
spelling	10.1016/j.chaos.2021.111131 doi (DE-627)ELV006377041 (ELSEVIER)S0960-0779(21)00485-9 DE-627 ger DE-627 rda eng 510 DE-600 30.20 bkl 31.00 bkl Agudov, N.V. verfasserin (orcid)0000-0003-1767-0118 aut Stochastic model of memristor based on the length of conductive region 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching. Memristor Stochasticity Resistive switching Yttria stabilized zirconia Dubkov, A.A. verfasserin aut Safonov, A.V. verfasserin aut Krichigin, A.V. verfasserin aut Kharcheva, A.A. verfasserin aut Guseinov, D.V. verfasserin aut Koryazhkina, M.N. verfasserin aut Novikov, A.S. verfasserin aut Shishmakova, V.A. verfasserin aut Antonov, I.N. verfasserin aut Carollo, A. verfasserin aut Spagnolo, B. verfasserin aut Enthalten in Chaos, solitons & fractals Amsterdam [u.a.] : Elsevier Science, 1991 150 Online-Ressource (DE-627)314118497 (DE-600)2003919-0 (DE-576)094504040 1873-2887 nnns volume:150 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 30.20 Nichtlineare Dynamik 31.00 Mathematik: Allgemeines AR 150
allfields_unstemmed	10.1016/j.chaos.2021.111131 doi (DE-627)ELV006377041 (ELSEVIER)S0960-0779(21)00485-9 DE-627 ger DE-627 rda eng 510 DE-600 30.20 bkl 31.00 bkl Agudov, N.V. verfasserin (orcid)0000-0003-1767-0118 aut Stochastic model of memristor based on the length of conductive region 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching. Memristor Stochasticity Resistive switching Yttria stabilized zirconia Dubkov, A.A. verfasserin aut Safonov, A.V. verfasserin aut Krichigin, A.V. verfasserin aut Kharcheva, A.A. verfasserin aut Guseinov, D.V. verfasserin aut Koryazhkina, M.N. verfasserin aut Novikov, A.S. verfasserin aut Shishmakova, V.A. verfasserin aut Antonov, I.N. verfasserin aut Carollo, A. verfasserin aut Spagnolo, B. verfasserin aut Enthalten in Chaos, solitons & fractals Amsterdam [u.a.] : Elsevier Science, 1991 150 Online-Ressource (DE-627)314118497 (DE-600)2003919-0 (DE-576)094504040 1873-2887 nnns volume:150 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 30.20 Nichtlineare Dynamik 31.00 Mathematik: Allgemeines AR 150
allfieldsGer	10.1016/j.chaos.2021.111131 doi (DE-627)ELV006377041 (ELSEVIER)S0960-0779(21)00485-9 DE-627 ger DE-627 rda eng 510 DE-600 30.20 bkl 31.00 bkl Agudov, N.V. verfasserin (orcid)0000-0003-1767-0118 aut Stochastic model of memristor based on the length of conductive region 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching. Memristor Stochasticity Resistive switching Yttria stabilized zirconia Dubkov, A.A. verfasserin aut Safonov, A.V. verfasserin aut Krichigin, A.V. verfasserin aut Kharcheva, A.A. verfasserin aut Guseinov, D.V. verfasserin aut Koryazhkina, M.N. verfasserin aut Novikov, A.S. verfasserin aut Shishmakova, V.A. verfasserin aut Antonov, I.N. verfasserin aut Carollo, A. verfasserin aut Spagnolo, B. verfasserin aut Enthalten in Chaos, solitons & fractals Amsterdam [u.a.] : Elsevier Science, 1991 150 Online-Ressource (DE-627)314118497 (DE-600)2003919-0 (DE-576)094504040 1873-2887 nnns volume:150 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 30.20 Nichtlineare Dynamik 31.00 Mathematik: Allgemeines AR 150
allfieldsSound	10.1016/j.chaos.2021.111131 doi (DE-627)ELV006377041 (ELSEVIER)S0960-0779(21)00485-9 DE-627 ger DE-627 rda eng 510 DE-600 30.20 bkl 31.00 bkl Agudov, N.V. verfasserin (orcid)0000-0003-1767-0118 aut Stochastic model of memristor based on the length of conductive region 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching. Memristor Stochasticity Resistive switching Yttria stabilized zirconia Dubkov, A.A. verfasserin aut Safonov, A.V. verfasserin aut Krichigin, A.V. verfasserin aut Kharcheva, A.A. verfasserin aut Guseinov, D.V. verfasserin aut Koryazhkina, M.N. verfasserin aut Novikov, A.S. verfasserin aut Shishmakova, V.A. verfasserin aut Antonov, I.N. verfasserin aut Carollo, A. verfasserin aut Spagnolo, B. verfasserin aut Enthalten in Chaos, solitons & fractals Amsterdam [u.a.] : Elsevier Science, 1991 150 Online-Ressource (DE-627)314118497 (DE-600)2003919-0 (DE-576)094504040 1873-2887 nnns volume:150 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 30.20 Nichtlineare Dynamik 31.00 Mathematik: Allgemeines AR 150
language	English
source	Enthalten in Chaos, solitons & fractals 150 volume:150
sourceStr	Enthalten in Chaos, solitons & fractals 150 volume:150
format_phy_str_mv	Article
bklname	Nichtlineare Dynamik Mathematik: Allgemeines
institution	findex.gbv.de
topic_facet	Memristor Stochasticity Resistive switching Yttria stabilized zirconia
dewey-raw	510
isfreeaccess_bool	false
container_title	Chaos, solitons & fractals
authorswithroles_txt_mv	Agudov, N.V. @@aut@@ Dubkov, A.A. @@aut@@ Safonov, A.V. @@aut@@ Krichigin, A.V. @@aut@@ Kharcheva, A.A. @@aut@@ Guseinov, D.V. @@aut@@ Koryazhkina, M.N. @@aut@@ Novikov, A.S. @@aut@@ Shishmakova, V.A. @@aut@@ Antonov, I.N. @@aut@@ Carollo, A. @@aut@@ Spagnolo, B. @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	314118497
dewey-sort	3510
id	ELV006377041
language_de	englisch
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author	Agudov, N.V.
spellingShingle	Agudov, N.V. ddc 510 bkl 30.20 bkl 31.00 misc Memristor misc Stochasticity misc Resistive switching misc Yttria stabilized zirconia Stochastic model of memristor based on the length of conductive region
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topic_title	510 DE-600 30.20 bkl 31.00 bkl Stochastic model of memristor based on the length of conductive region Memristor Stochasticity Resistive switching Yttria stabilized zirconia
topic	ddc 510 bkl 30.20 bkl 31.00 misc Memristor misc Stochasticity misc Resistive switching misc Yttria stabilized zirconia
topic_unstemmed	ddc 510 bkl 30.20 bkl 31.00 misc Memristor misc Stochasticity misc Resistive switching misc Yttria stabilized zirconia
topic_browse	ddc 510 bkl 30.20 bkl 31.00 misc Memristor misc Stochasticity misc Resistive switching misc Yttria stabilized zirconia
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
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title	Stochastic model of memristor based on the length of conductive region
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title_full	Stochastic model of memristor based on the length of conductive region
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author_browse	Agudov, N.V. Dubkov, A.A. Safonov, A.V. Krichigin, A.V. Kharcheva, A.A. Guseinov, D.V. Koryazhkina, M.N. Novikov, A.S. Shishmakova, V.A. Antonov, I.N. Carollo, A. Spagnolo, B.
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title_sort	stochastic model of memristor based on the length of conductive region
title_auth	Stochastic model of memristor based on the length of conductive region
abstract	We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching.
abstractGer	We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching.
abstract_unstemmed	We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. Based on the proposed model, the mathematical apparatus of Markov processes for the first passage time of the boundaries can be used to analyse the temporal characteristics of resistive switching.
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title_short	Stochastic model of memristor based on the length of conductive region
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author2	Dubkov, A.A. Safonov, A.V. Krichigin, A.V. Kharcheva, A.A. Guseinov, D.V. Koryazhkina, M.N. Novikov, A.S. Shishmakova, V.A. Antonov, I.N. Carollo, A. Spagnolo, B.
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up_date	2024-07-06T21:10:23.179Z
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score	7.401434

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Stochastic model of memristor based on the length of conductive region

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Zugang & Verfügbarkeit

Vorhandene Bände

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