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Memristive Device Fundamentals And Modeling: Applications To Circuits And Systems Simulation

K. Eshraghian, O. Kavehei, Kyoung-Rok Cho, J. M. Chappell, A. Iqbal, S. Al-Sarawi, D. Abbott
Published 2012 · Computer Science, Engineering

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The nonvolatile memory property of a memristor enables the realization of new methods for a variety of computational engines ranging from innovative memristive-based neuromorphic circuitry through to advanced memory applications. The nanometer-scale feature of the device creates a new opportunity for realization of innovative circuits that in some cases are not possible or have inefficient realization in the present and established design domain. The nature of the boundary, the complexity of the ionic transport and tunneling mechanism, and the nanoscale feature of the memristor introduces challenges in modeling, characterization, and simulation of future circuits and systems. Here, a deeper insight is gained in understanding the device operation, leading to the development of practical models that can be implemented in current computer-aided design (CAD) tools.
This paper references
BThe effects of switching time and SrTiO 3Àx N y nanostructures on the operation of Al/SrTiO 3Àx N y /Al memristors,[ IOP Conf
A Shkabko (2010)
10.1063/1.2001146
Resistive switching mechanism of TiO2 thin films grown by atomic-layer deposition
Byung Joon Choi (2005)
10.1007/s11999-008-0182-y
Electromagnetic Fields
M. Ishida (2008)
B TerraByte flash memory with carbon nanotubes , [ Appl
L. B. Kish
and R
P. O. Vontobel (2009)
10.1103/PhysRevE.80.021926
Memristive model of amoeba learning.
Y. Pershin (2009)
10.1109/TCT.1971.1083337
Memristor-The missing circuit element
L. Chua (1971)
and W
S. H. Jo (2010)
10.1063/1.3236506
Switching dynamics in titanium dioxide memristive devices
M. Pickett (2009)
10.1021/NL034795U
Molecule-Independent Electrical Switching in Pt/Organic Monolayer/Ti Devices
D. Stewart (2004)
10.1088/1757-899X/8/1/012035
The effects of switching time and SrTiO3-xNy nanostructures on the operation of Al/SrTiO 3-x N y /Al memristors
A. Shkabko (2010)
10.1007/S00339-008-4975-3
Exponential ionic drift: fast switching and low volatility of thin-film memristors
D. Strukov (2009)
BTerraByte flash memory with carbon
L. B. Kish (2005)
10.1063/1.1874304
TerraByte flash memory with carbon nanotubes
L. B. Kish (2005)
BCMOL/CMOS implementations of Bayesian inference engine: Digital and mixed-signal architectures and performance/priceVA hardware design space exploration
D Hammerstrom (2010)
BFabrication and modeling of Ag/TiO 2 /ITO memristor
O Kavehei (2011)
10.1063/1.3227651
Force modulation of tunnel gaps in metal oxide memristive nanoswitches
F. Miao (2009)
10.1098/rspa.2009.0553
The fourth element: characteristics, modelling and electromagnetic theory of the memristor
O. Kavehei (2010)
and R
M. D. Pickett (2009)
IEEE) received the B.S. degree in electronic engineering from Kyoungpook National University, Taegu, Korea, in 1977 and the M.S. and Ph.D. degrees in electrical engineering from University of Tokyo
Kyoung Rok (1989)
10.1063/1.1702682
Generalized Formula for the Electric Tunnel Effect between Similar Electrodes Separated by a Thin Insulating Film
J. Simmons (1963)
BMemristive devices and systems
L O Chua (1976)
10.1088/0957-4484/20/34/345201
An electrically modifiable synapse array of resistive switching memory.
H. Choi (2009)
10.1021/nl904092h
Nanoscale memristor device as synapse in neuromorphic systems.
S. Jo (2010)
10.1119/1.17202
An introduction to geometric calculus and its application to electrodynamics
T. Vold (1993)
10.1017/cbo9780511807497
Geometric Algebra for Physicists
C. Doran (2003)
10.1109/TVLSI.2008.2007735
Design of Spin-Torque Transfer Magnetoresistive RAM and CAM/TCAM with High Sensing and Search Speed
W. Xu (2010)
10.1136/BJO.46.11.704
A and V
R. Stephenson (1962)
BAn electrically modifiable synapse array of resistive switching memory
H Choi (2009)
and C
F. Miao (2009)
BNanoionics-based resistive switching memories
R Waser (2007)
BThe missing memristor found
D B Strukov (2008)
10.1109/PROC.1976.10092
Memristive devices and systems
L. Chua (1976)
10.1038/NMAT1614
Switching the electrical resistance of individual dislocations in single-crystalline SrTiO3
K. Szot (2006)
10.1038/NPRE.2009.3010.1
Memristance can explain Spike-Time-Dependent-Plasticity in Neural Synapses
B. Linares-Barranco (2009)
10.1021/JP066846S
Analyzing Molecular Current-Voltage Characteristics with the Simmons Tunneling Model: Scaling and Linearization
A. Vilan (2007)
10.1038/nnano.2008.160
Memristive switching mechanism for metal/oxide/metal nanodevices.
J. Yang (2008)
10.1038/nature06932
The missing memristor found
D. Strukov (2008)
BAdaptive FADALINE_ neuron using chemical Fmemistors
B Widrow (1960)
Memristive Device Fundamentals and Modeling: Applications to Circuits and Systems Simulation
Kamran Eshraghian (2012)
10.1109/MWSCAS.2011.6026575
Fabrication and modeling of Ag/TiO2/ITO memristor
O. Kavehei (2011)
10.1038/NMAT2023
Nanoionics-based resistive switching memories.
R. Waser (2007)
10.1109/JPROC.2003.818319
Nonlinear circuit foundations for nanodevices. I. The four-element torus
L. Chua (2003)
J. Analog Integr. Circuits Signal Process
(2011)
BMemristive model of amoeba learning
Y V Pershin (2009)
and M
Y. V. Pershin (2009)
10.1109/JPROC.2009.2021077
Circuit Elements With Memory: Memristors, Memcapacitors, and Meminductors
M. Ventra (2009)
10.1109/ECCTD.2009.5274934
SPICE modeling of memristive, memcapacitative and meminductive systems
D. Biolek (2009)
BResistive switching mechanism of TiO 2 thin films grown by atomic-layer deposition
B J Choi (2005)
and K
T. Kumaki (2005)
and M
T. Hasegawa (2010)
10.1017/CBO9781139207249.009
I and J
William M. Marsden (2012)
10.1109/ISCAS.2005.1465807
CAM-based VLSI architecture for Huffman coding with real-time optimization of the code word table [image coding example]
T. Kumaki (2005)
B Exponential ionic drift : Fast switching and low volatility of thin - film memristors , [ Appl
R. Williams (2009)
10.1109/TCAD.2010.2042891
Compact Models for Memristors Based on Charge-Flux Constitutive Relationships
S. Shin (2010)
BCMOL/CMOS implementations of Bayesian inference engine: Digital and mixed-signal architectures and performance/priceVA hardware design space exploration,[ in CMOS Processors and Memories, Part 1, K
D. Hammerstrom (2010)
and R
K. Szot (2006)
10.1109/TVLSI.2010.2049867
Memristor MOS Content Addressable Memory (MCAM): Hybrid Architecture for Future High Performance Search Engines
K. Eshraghian (2011)
and R
D. B. Strukov (2008)
BSwitching the electrical resistance of individual dislocations in single-crystalline SrTiO 3
K Szot (2006)
BAn introduction to geometric calculus and its application to electrodynamics,[ Amer
T G Vold (1993)
10.1109/ISCAS.2011.5937942
SPICE modeling of memristors
Hisham Abdalla (2011)
10.1109/JSSC.2005.864128
Content-addressable memory (CAM) circuits and architectures: a tutorial and survey
K. Pagiamtzis (2006)
10.1109/JSSC.2004.831433
A low-power content-addressable memory (CAM) using pipelined hierarchical search scheme
K. Pagiamtzis (2004)
10.1007/978-90-481-9216-8_4
CMOL/CMOS Implementations of Bayesian Inference Engine: Digital and Mixed-Signal Architectures and Performance/Price – A Hardware Design Space Exploration
D. Hammerstrom (2010)
10.1109/TNANO.2011.2174802
An Analytical Approach for Memristive Nanoarchitectures
O. Kavehei (2012)
and S
B. J. Choi (2005)
and S
B. J. Choi (2005)
10.1002/adma.200903680
Learning abilities achieved by a single solid-state atomic switch.
T. Hasegawa (2010)
BThe elusive memristor: Properties of basic electrical circuits,[ Eur
Y N Joglekar (2009)
BSPICE modeling of memristive
D. Biolek (2009)
B Force modulation of tunnel gaps in metal oxide memristive nanoswitches , [ Appl
J. J. Yang
and R
J. J. Yang (2008)
10.1088/0957-4484/20/42/425204
Writing to and reading from a nano-scale crossbar memory based on memristors.
P. Vontobel (2009)
B Resistive switching mechanism of TiO 2 thin films grown by atomiclayer deposition
D. S. Jeong (2005)
BAdaptive FADALINE_ neuron using chemical Fmemistors_,[ Stanford Electron
B. Widrow (1960)
BSPICE modeling of memristors,[ in Proc
H Abdalla (2011)
10.1109/CNNA.2010.5430304
CNN using memristors for neighborhood connections
E. Lehtonen (2010)
10.1049/pbew001e_ch2
Electromagnetic Fields
J. V. Bladel (1985)
10.1088/0143-0807/30/4/001
The elusive memristor: properties of basic electrical circuits
Y. Joglekar (2009)
and K
O. Kavehei (2011)
and H
H. Choi (2009)
BThe fourth element: Characteristics
O. Kavehei (2010)
and T
A. Shkabko (2010)
SPICE Model of Memristor with Nonlinear Dopant Drift
D. Biolek (2009)
10.1007/S10470-010-9505-5
PSPICE modeling of meminductor
D. Biolek (2011)



This paper is referenced by
Chapter 2 Memristor Modeling 2 . 1
(2019)
10.1109/TNANO.2013.2241075
Programmable CMOS/Memristor Threshold Logic
Ligang Gao (2013)
A Reconfigurable FIR Filter with Memristor-Based Weights
F. Merrikh-Bayat (2016)
10.1109/TNANO.2014.2314126
Two Memristor SPICE Models and Their Applications in Microwave Devices
K. Xu (2014)
10.1109/TNANO.2014.2299558
Memristor Multiport Readout: A Closed-Form Solution for Sneak Paths
Mohammed Affan Zidan (2014)
10.20868/upm.thesis.46845
Resistive RAM: simulation and modeling for reliable design
F. G. Redondo (2017)
10.1007/s00521-016-2248-1
Transient response characteristic of memristor circuits and biological-like current spikes
M. S. Feali (2016)
10.25560/17981
A mathematical framework for the analysis and modelling of memristor nanodevices
Panayiotis S. Georgiou (2013)
Neuromorphic VLSI designs for spike timing and rate-based synaptic plasticity with application in pattern classification.
Rahimi Azghadi (2014)
10.1002/cta.2327
Modeling and simulation of large memristive networks
D. Biolek (2018)
10.1088/0268-1242/30/11/115009
Modeling of bipolar resistive switching of a nonlinear MISM memristor
F. O. Hatem (2015)
Memristive devices and circuits for computing, memory, and neuromorphic applications.
O. Kavehei (2012)
10.1515/ntrev-2015-0029
State of the art of metal oxide memristor devices
B. Mohammad (2016)
10.25781/KAUST-LUT70
Von-Neumann and Beyond: Memristor Architectures
R. Naous (2017)
10.1007/S11071-019-04890-1
Hidden extreme multistability and dimensionality reduction analysis for an improved non-autonomous memristive FitzHugh–Nagumo circuit
H. Bao (2019)
MEMRISTOR. UNA PERSPECTIVA GENERAL CARLOS Oy ARCE MARAMBIO, KRISTOPhER ChANdí A VALENz UELA y ALEjANdRO ROdRí GUEz E STAy
Alejandro Rodríguez (2014)
10.1007/S00339-015-8993-7
Phenomenological modeling of memristive devices
F. Merrikh Bayat (2015)
10.1016/J.CHAOS.2019.03.003
Dynamical effects of memristive load on peak current mode buck-boost switching converter
Bocheng Bao (2019)
10.15760/ETD.2717
The Design of a Simple, Spiking Sparse Coding Algorithm for Memristive Hardware
Walt Woods (2016)
10.1142/s0218127420500455
Memristor Synapse-Based Morris–Lecar Model: Bifurcation Analyses and FPGA-Based Validations for Periodic and Chaotic Bursting/Spiking Firings
Han Bao (2020)
10.1002/cta.2414
Harmonic balance method to analyze bifurcations in memristor oscillatory circuits
M. Marco (2018)
10.1109/MWSCAS.2013.6674799
Polynomial Metamodel integrated Verilog-AMS for memristor-based mixed-signal system design
G. Zheng (2013)
10.1002/cta.2186
Window functions and sigmoidal behaviour of memristive systems
Panayiotis S. Georgiou (2016)
10.1109/IRANIANCEE.2014.6999567
A novel CMOS-memristor based inverter circuit design
B. Abdoli (2014)
Bipolar resistive switching of bi-layered Pt/Ta2O5/TaOx/Pt RRAM : physics-based modelling, circuit design and testing
Firas Odai Hatem (2017)
10.1002/cta.1957
SPICE modeling of nonlinear memristive behavior
I. Vourkas (2015)
10.1016/j.mejo.2017.05.006
Accurate charge transport model for nanoionic memristive devices
A. Amirsoleimani (2017)
10.1142/s0218126621200024
Spice Behavioral Modeling of TiO2 Memristors for Digital Logic Applications
Nadine Gergel-Hackett (2020)
10.1142/S0218127420300293
Experimentally accessible orbits near a Bykov cycle
Han Bao (2020)
Comparative Analysis of Switching Dynamics in Different Memristor Models
S. Parajuli (2019)
Efficient minimization Techniques for Threshold Logic Gate
R. Kumar (2016)
10.1007/s00034-015-0067-8
Analog Emulator of Genuinely Floating Memcapacitor with Piecewise-Linear Constitutive Relation
D. Biolek (2016)
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