Memristive Devices for Neuromorphic Applications: Comparative Analysis

Neuromorphic systems must have at least five unavoidable features that are present in living beings. First, neuromorphic systems must perform memorizing and processing functions, using same elements. Second, it must allow data acquisition from sensors with preliminary processing and recording. Third, it must allow non-equilibrium processes, such as oscillator behavior at fixed values of input stimuli. Fourth, it must mimic some features of nervous systems. Fifth, it must permit possibility of coupling with living beings. In this paper, these features are considered with a special attention to how memristive devices can be implemented for reaching the goal. Comparison of characteristic properties of organic and inorganic memristive devices is discussed.

[1]  Bin Gao,et al.  Fully hardware-implemented memristor convolutional neural network , 2020, Nature.

[2]  Robert Kozma,et al.  Hierarchical random cellular neural networks for system-level brain-like signal processing , 2013, Neural Networks.

[3]  T. Berzina,et al.  Hybrid electronic device based on polyaniline-polyethyleneoxide junction , 2005 .

[4]  Ronald Tetzlaff,et al.  An Improved Cellular Nonlinear Network Architecture for Binary and Grayscale Image Processing , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

[5]  F. Zeng,et al.  Recent progress in resistive random access memories: Materials, switching mechanisms, and performance , 2014 .

[6]  Y. Liu,et al.  Synaptic Learning and Memory Functions Achieved Using Oxygen Ion Migration/Diffusion in an Amorphous InGaZnO Memristor , 2012 .

[7]  Fernando Corinto,et al.  Nonlinear Dynamics of Memristor Oscillators , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[8]  Hojjat Adeli,et al.  Spiking Neural Networks , 2009, Int. J. Neural Syst..

[9]  Giacomo Indiveri,et al.  Integration of nanoscale memristor synapses in neuromorphic computing architectures , 2013, Nanotechnology.

[10]  Karthikeyan Rajagopal,et al.  Dynamical investigation and chaotic associated behaviors of memristor Chua’s circuit with a non-ideal voltage-controlled memristor and its application to voice encryption , 2019, AEU - International Journal of Electronics and Communications.

[11]  M. Tellekamp,et al.  Evidence of ion intercalation mediated band structure modification and opto-ionic coupling in lithium niobite , 2015 .

[12]  Herbert Ho-Ching Iu,et al.  Chaotic oscillator based on memcapacitor and meminductor , 2019, Nonlinear Dynamics.

[13]  Tatiana Berzina,et al.  Polymeric elements for adaptive networks , 2007 .

[14]  Andrew Schumann,et al.  Physarum Chip Project: Growing Computers From Slime Mould , 2012, Int. J. Unconv. Comput..

[15]  Byung Joon Choi,et al.  Engineering nonlinearity into memristors for passive crossbar applications , 2012 .

[16]  Victor Erokhin,et al.  Spectrophotometric characterization of organic memristive devices , 2016 .

[17]  Y. van de Burgt,et al.  Towards organic neuromorphic devices for adaptive sensing and novel computing paradigms in bioelectronics , 2019, Journal of Materials Chemistry C.

[18]  R. Waser,et al.  Nanoscale cation motion in TaO(x), HfO(x) and TiO(x) memristive systems. , 2016, Nature nanotechnology.

[19]  A. V. Emelyanov,et al.  Hardware elementary perceptron based on polyaniline memristive devices , 2015 .

[20]  M. Awais,et al.  Resistive switching and current conduction mechanism in full organic resistive switch with the sandwiched structure of poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate)/poly(4-vinylphenol)/poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) , 2014, Electronic Materials Letters.

[21]  Massimiliano Di Ventra,et al.  Memristive model of amoeba learning. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Leon Chua,et al.  Memristors in the electrical network of Aloe vera L. , 2014, Plant signaling & behavior.

[23]  Andrew Adamatzky,et al.  Slime Mould Memristors , 2013, 1306.3414.

[24]  D. Sahu,et al.  Detection of bovine serum albumin using hybrid TiO2 + graphene oxide based Bio – resistive random access memory device , 2019, Scientific Reports.

[25]  Luping Shi,et al.  Memristor devices for neural networks , 2018, Journal of Physics D: Applied Physics.

[26]  Bocheng Bao,et al.  Steady periodic memristor oscillator with transient chaotic behaviours , 2010 .

[27]  Andrej Plecenik,et al.  Gasistor: A memristor based gas-triggered switch and gas sensor with memory , 2019, Applied Physics Letters.

[28]  Leon O. Chua,et al.  UNIVERSAL CNN CELLS , 1999 .

[29]  Sandro Carrara,et al.  Label-Free Ultrasensitive Memristive Aptasensor. , 2016, Nano letters.

[30]  Vincent Garcia,et al.  Ferroelectric tunnel junctions for information storage and processing , 2014, Nature Communications.

[31]  Xiaoli Chen,et al.  Bioinspired Artificial Sensory Nerve Based on Nafion Memristor , 2019, Advanced Functional Materials.

[32]  V. Erokhin,et al.  On the resistive switching mechanism of parylene-based memristive devices , 2019, Organic Electronics.

[33]  Zhigang Zeng,et al.  Noise cancellation of memristive neural networks , 2014, Neural Networks.

[34]  Seung Hwan Lee,et al.  Reservoir computing using dynamic memristors for temporal information processing , 2017, Nature Communications.

[35]  Sung-Min Yoon,et al.  Polymeric ferroelectric and oxide semiconductor-based fully transparent memristor cell , 2011 .

[36]  Tatiana Berzina,et al.  A functional polymeric material based on hybrid electrochemically controlled junctions , 2008 .

[37]  Ali Khiat,et al.  Memristive synapses connect brain and silicon spiking neurons , 2020, Scientific Reports.

[38]  M. K. Hota,et al.  A Natural Silk Fibroin Protein‐Based Transparent Bio‐Memristor , 2012 .

[39]  Md. Zubbair Malik,et al.  Neuronal communication: Stochastic neuron dynamics and multi-synchrony states , 2019, AEU - International Journal of Electronics and Communications.

[40]  J. Yang,et al.  Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. , 2017, Nature materials.

[41]  M. Marinella,et al.  A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. , 2017, Nature materials.

[42]  Ping Liu,et al.  Analysis and Implementation of a New Switching Memristor Scroll Hyperchaotic System and Application in Secure Communication , 2018, Complex..

[43]  Peng Lin,et al.  Reinforcement learning with analogue memristor arrays , 2019, Nature Electronics.

[44]  Yiran Chen,et al.  Spintronic Memristor Temperature Sensor , 2010, IEEE Electron Device Letters.

[45]  Massimiliano Di Ventra,et al.  On the validity of memristor modeling in the neural network literature , 2019, Neural Networks.

[46]  Qiangfei Xia,et al.  Review of memristor devices in neuromorphic computing: materials sciences and device challenges , 2018, Journal of Physics D: Applied Physics.

[47]  K. Thamilmaran,et al.  Implementation and study of the nonlinear dynamics of a memristor-based Duffing oscillator , 2017 .

[48]  George G. Malliaras,et al.  Neuromorphic device architectures with global connectivity through electrolyte gating , 2017, Nature Communications.

[49]  Dmitri B. Strukov,et al.  Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits , 2017, Nature Communications.

[50]  C. N. Lau,et al.  The mechanism of electroforming of metal oxide memristive switches , 2009, Nanotechnology.

[51]  Dianzhong Wen,et al.  Nonvolatile Bio-Memristor Based on Silkworm Hemolymph Proteins , 2017, Scientific Reports.

[52]  Giovanni De Micheli,et al.  Computational Study on the Electrical Behavior of Silicon Nanowire Memristive Biosensors , 2015, IEEE Sensors Journal.

[53]  Andrew S. Cassidy,et al.  A million spiking-neuron integrated circuit with a scalable communication network and interface , 2014, Science.

[54]  C. Choi,et al.  Stabilized and RESET-voltage controlled multi-level switching characteristics in ZrO2-based memristors by inserting a-ZTO interface layer , 2020 .

[55]  Victor Erokhin,et al.  Skeleton-supported stochastic networks of organic memristive devices: Adaptations and learning , 2015 .

[56]  Leon O. Chua.  Resistance switching memories are memristors , 2011 .

[57]  Xiaoping Wang,et al.  Memristive Circuit Design of Emotional Generation and Evolution Based on Skin-Like Sensory Processor , 2019, IEEE Transactions on Biomedical Circuits and Systems.

[58]  Damien Querlioz,et al.  Neuromorphic computing with nanoscale spintronic oscillators , 2017, Nature.

[59]  R. Waser,et al.  Coexistence of Grain‐Boundaries‐Assisted Bipolar and Threshold Resistive Switching in Multilayer Hexagonal Boron Nitride , 2017 .

[60]  P. I. Fierens,et al.  On the beneficial role of noise in resistive switching , 2013, 1307.0143.

[61]  J. Yang,et al.  Robust memristors based on layered two-dimensional materials , 2018, 1801.00530.

[62]  Tatiana Berzina,et al.  Optimization of an organic memristor as an adaptive memory element , 2009 .

[63]  Pavel K. Kashkarov,et al.  Electrochemical model of the polyaniline based organic memristive device , 2014 .

[64]  J. Yang,et al.  Memristive switching mechanism for metal/oxide/metal nanodevices. , 2008, Nature nanotechnology.

[65]  Victor Erokhin,et al.  Hybrid slime mould-based system for unconventional computing , 2015, Int. J. Gen. Syst..

[66]  V. Erokhin,et al.  Parylene Based Memristive Devices with Multilevel Resistive Switching for Neuromorphic Applications , 2019, Scientific Reports.

[67]  A. Volkov,et al.  Cyclic voltammetry of apple fruits: Memristors in vivo. , 2016, Bioelectrochemistry.

[68]  Jacopo Frascaroli,et al.  Role of Al doping in the filament disruption in HfO2 resistance switches , 2017, Nanotechnology.

[69]  Farnood Merrikh-Bayat,et al.  Training and operation of an integrated neuromorphic network based on metal-oxide memristors , 2014, Nature.

[70]  Yusuf Leblebici,et al.  Memristive-Biosensors: A New Detection Method by Using Nanofabricated Memristors , 2012 .

[71]  Pavel K. Kashkarov,et al.  Polyaniline-based memristive microdevice with high switching rate and endurance , 2018 .

[72]  Jacques Kengne,et al.  Coexisting bifurcations in a memristive hyperchaotic oscillator , 2018, AEU - International Journal of Electronics and Communications.

[73]  A. Volkov,et al.  Sunpatiens compact hot coral: memristors in flowers. , 2018, Functional plant biology : FPB.

[74]  Ali Khiat,et al.  Real-time encoding and compression of neuronal spikes by metal-oxide memristors , 2016, Nature Communications.

[75]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[76]  Wei Yang Lu,et al.  Nanoscale memristor device as synapse in neuromorphic systems. , 2010, Nano letters.

[77]  H. Yu,et al.  Nonvolatile Bio-Memristor Fabricated with Egg Albumen Film , 2015, Scientific Reports.

[78]  Ruixin Dong,et al.  Organic memristive devices based on silver nanoparticles and DNA , 2014 .

[79]  Richard Miles,et al.  EPSP Amplification and the Precision of Spike Timing in Hippocampal Neurons , 2000, Neuron.

[80]  L. Chua.  Memristor-The missing circuit element , 1971 .

[81]  Mikel Sanz,et al.  Perceptrons from Memristors , 2018, Neural Networks.

[82]  Ying Zhu,et al.  Rectification‐Regulated Memristive Characteristics in Electron‐Type CuPc‐Based Element for Electrical Synapse , 2017 .

[83]  Salvatore Iannotta,et al.  A bio-inspired memory device based on interfacing Physarum polycephalum with an organic semiconductor , 2015 .

[84]  Tatiana Berzina,et al.  Conductivity patterning with Physarum polycephalum: natural growth and deflecting , 2015 .

[85]  A. Adamatzky,et al.  Drop-coated titanium dioxide memristors , 2012, 1205.2885.

[86]  Péter Szolgay,et al.  Configurable multilayer CNN-UM emulator on FPGA , 2003 .

[87]  R. Khazipov,et al.  Coupling Cortical Neurons through Electronic Memristive Synapse , 2018, Advanced Materials Technologies.

[88]  S. H. Herman,et al.  Trends of deposition and patterning techniques of TiO2 for memristor based bio-sensing applications , 2013 .

[89]  Andrea Padovani,et al.  Multiscale Modeling for Application-Oriented Optimization of Resistive Random-Access Memory , 2019, Materials.

[90]  Qing Wan,et al.  Artificial synapse network on inorganic proton conductor for neuromorphic systems. , 2014, Nature communications.

[91]  Raymond Beausoleil,et al.  Power-efficient combinatorial optimization using intrinsic noise in memristor Hopfield neural networks , 2020, Nature Electronics.

[92]  Bernabé Linares-Barranco,et al.  On Spike-Timing-Dependent-Plasticity, Memristive Devices, and Building a Self-Learning Visual Cortex , 2011, Front. Neurosci..

[93]  Tamás Roska,et al.  A Biomimetic Model of the Outer Plexiform Layer by Incorporating Memristive Devices , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[94]  Alexander G. Volkov,et al.  Biosensors, memristors and actuators in electrical networks of plants , 2017, Int. J. Parallel Emergent Distributed Syst..

[95]  Shukai Duan,et al.  Adaptive sparse coding based on memristive neural network with applications , 2019, Cognitive Neurodynamics.

[96]  Seungjun Kim,et al.  Flexible memristive memory array on plastic substrates. , 2011, Nano letters.

[97]  A Adamatzky,et al.  Slime mould processors, logic gates and sensors , 2015, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[98]  V. Cros,et al.  Spin-torque building blocks. , 2014, Nature Materials.

[99]  Victor Erokhin,et al.  Organic Memristor and Bio-Inspired Information Processing , 2010, Int. J. Unconv. Comput..

[100]  Herbert Jaeger,et al.  Reservoir computing approaches to recurrent neural network training , 2009, Comput. Sci. Rev..

[101]  G. Buzsáki,et al.  Tools for probing local circuits: high-density silicon probes combined with optogenetics , 2015, Neuron.

[102]  Huamin Wang,et al.  Pavlov associative memory in a memristive neural network and its circuit implementation , 2016, Neurocomputing.

[103]  Ru Huang,et al.  Artificial Shape Perception Retina Network Based on Tunable Memristive Neurons , 2018, Scientific Reports.

[104]  Daoben Zhu,et al.  A Dual‐Organic‐Transistor‐Based Tactile‐Perception System with Signal‐Processing Functionality , 2017, Advanced materials.

[105]  A. V. Emelyanov,et al.  Spike-timing-dependent plasticity of polyaniline-based memristive element , 2018 .

[106]  L. Chua,et al.  Memristors in plants , 2014, Plant signaling & behavior.

[107]  SchmidhuberJürgen.  Deep learning in neural networks , 2015 .

[108]  Shimeng Yu,et al.  Neuro-Inspired Computing With Emerging Nonvolatile Memorys , 2018, Proceedings of the IEEE.

[109]  Narayan Srinivasa,et al.  A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications. , 2012, Nano letters.

[110]  Brahim Dkhil,et al.  Research progress on solutions to the sneak path issue in memristor crossbar arrays , 2020, Nanoscale advances.

[111]  Andrew Adamatzky,et al.  Organic memristor Devices for Logic Elements with Memory , 2012, Int. J. Bifurc. Chaos.

[112]  Shukai Duan,et al.  Artificial and wearable albumen protein memristor arrays with integrated memory logic gate functionality , 2019, Materials Horizons.

[113]  Sen Song,et al.  Bridging Biological and Artificial Neural Networks with Emerging Neuromorphic Devices: Fundamentals, Progress, and Challenges , 2019, Advanced materials.

[114]  Leon Chua,et al.  An analytical model of memristors in plants , 2014, Plant signaling & behavior.

[115]  T. Berzina,et al.  Spectral imaging method for studying Physarum polycephalum growth on polyaniline surface. , 2015, Materials science & engineering. C, Materials for biological applications.

[116]  M. Ziegler,et al.  An Electronic Version of Pavlov's Dog , 2012 .

[117]  Ho Won Jang,et al.  Recent Advances in Memristive Materials for Artificial Synapses , 2018 .

[118]  K. Staras,et al.  A systems approach to the cellular analysis of associative learning in the pond snail Lymnaea. , 2000, Learning & memory.

[119]  Jie Lin,et al.  A scalable and reconfigurable in-memory architecture for ternary deep spiking neural network with ReRAM based neurons , 2020, Neurocomputing.

[120]  Paolo Camorani,et al.  Electrical properties of an organic memristive system , 2011 .

[121]  T. Berzina,et al.  Non-equilibrium electrical behaviour of polymeric electrochemical junctions , 2007 .

[122]  Péter Szolgay,et al.  Implementation of embedded emulated-digital CNN-UM global analogic programming unit on FPGA and its application , 2008 .

[123]  Dianzhong Wen,et al.  Resistive Switching Memory Devices Based on Body Fluid of Bombyx mori L. , 2019, Micromachines.

[124]  Shukai Duan,et al.  Chaotic circuit of ion migration memristor and its application in the voice secure communication , 2015 .

[125]  N. V. Agudov,et al.  Nonstationary distributions and relaxation times in a stochastic model of memristor , 2020, Journal of Statistical Mechanics: Theory and Experiment.

[126]  Qingliang Liao,et al.  Bioinspired Tribotronic Resistive Switching Memory for Self-Powered Memorizing Mechanical Stimuli. , 2017, ACS applied materials & interfaces.

[127]  Sandro Carrara,et al.  Nanowire Sensors in Cancer. , 2019, Trends in biotechnology.

[128]  Chaoxing Wu,et al.  Mimicking Classical Conditioning Based on a Single Flexible Memristor , 2017, Advanced materials.

[130]  T. Berzina,et al.  A hybrid living/organic electrochemical transistor based on the Physarum polycephalum cell endowed with both sensing and memristive properties , 2015, Chemical science.

[131]  Sungjun Kim,et al.  Oxygen annealing effect on resistive switching characteristics of multilayer CeO2/Al/CeO2 resistive random-access memory , 2020, Materials Research Express.

[132]  Victor Erokhin,et al.  Stochastic hybrid 3D matrix: learning and adaptation of electrical properties , 2012 .

[133]  Wei Lu,et al.  The future of electronics based on memristive systems , 2018, Nature Electronics.

[134]  Anthony J. Kenyon,et al.  Resistive switching in silicon sub-oxide films , 2012 .

[135]  T. Serrano-Gotarredona,et al.  STDP and STDP variations with memristors for spiking neuromorphic learning systems , 2013, Front. Neurosci..

[136]  V. Erokhin,et al.  Organic memristive devices for perceptron applications , 2018, Journal of Physics D: Applied Physics.

[137]  Kinam Kim,et al.  A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O(5-x)/TaO(2-x) bilayer structures. , 2011, Nature materials.

[138]  T. Berzina,et al.  Spectroscopic investigation of an electrochemically controlled conducting polymer-solid electrolyte junction , 2007 .

[139]  Michela Chiappalone,et al.  Coupling Resistive Switching Devices with Neurons: State of the Art and Perspectives , 2017, Front. Neurosci..

[140]  Sundarapandian Vaidyanathan,et al.  A memristor-based system with hidden hyperchaotic attractors, its circuit design, synchronisation via integral sliding mode control and an application to voice encryption , 2019, Int. J. Autom. Control..

[141]  M. Xiao,et al.  Synaptic learning behavior of a TiO2 nanowire memristor , 2019, Nanotechnology.

[142]  L. Abbott,et al.  Competitive Hebbian learning through spike-timing-dependent synaptic plasticity , 2000, Nature Neuroscience.

[143]  F. Gul.  Nano-scale single layer TiO2-based artificial synaptic device , 2019, Applied Nanoscience.

[144]  Leon O. Chua,et al.  The analogic cellular neural network as a bionic eye , 1995, Int. J. Circuit Theory Appl..

[145]  J. Grollier,et al.  High-performance ferroelectric memory based on fully patterned tunnel junctions , 2014 .

[146]  Leon O. Chua,et al.  Computing with Front Propagation: Active Contour And Skeleton Models In Continuous-Time CNN , 1999, J. VLSI Signal Process..

[147]  Fei Zhuge,et al.  Memristive Synapses for Brain‐Inspired Computing , 2019, Advanced Materials Technologies.

[148]  Tatiana Berzina,et al.  Conducting polymer-solid electrolyte fibrillar composite material for adaptive networks. , 2006, Soft matter.

[149]  Jan van den Hurk,et al.  Nanobatteries in redox-based resistive switches require extension of memristor theory , 2013, Nature Communications.

[150]  Tatiana Berzina,et al.  Polymeric electrochemical element for adaptive networks: Pulse mode , 2008 .

[151]  Yan Liang,et al.  A Floating Memristor Emulator Based Relaxation Oscillator , 2014, IEEE Transactions on Circuits and Systems I: Regular Papers.

[152]  V. Erokhin,et al.  Optical Monitoring of the Resistive States of a Polyaniline‐Based Memristive Device , 2020, Advanced Electronic Materials.

[153]  Anteo Smerieri,et al.  Origin of current oscillations in a polymeric electrochemically controlled element , 2008 .

[154]  D. Stewart,et al.  The missing memristor found , 2008, Nature.

[155]  Leandro Lorenzelli,et al.  Logic with memory: and gates made of organic and inorganic memristive devices , 2014 .

[156]  Armantas Melianas,et al.  A biohybrid synapse with neurotransmitter-mediated plasticity , 2020, Nature Materials.

[157]  Victor Erokhin,et al.  Associative STDP-like learning of neuromorphic circuits based on polyaniline memristive microdevices , 2020, Journal of Physics D: Applied Physics.

[158]  Eduardo Miranda,et al.  On Building Practical Biocomputers for Real-world Applications: Receptacles for Culturing Slime Mould Memristors and Component Standardisation , 2017 .

[159]  Alex Pappachen James,et al.  Learning in Memristive Neural Network Architectures Using Analog Backpropagation Circuits , 2018, IEEE Transactions on Circuits and Systems I: Regular Papers.

[160]  Jun Ma,et al.  Minireview on signal exchange between nonlinear circuits and neurons via field coupling , 2019, The European Physical Journal Special Topics.

[161]  Victor Erokhin,et al.  Bio-inspired adaptive networks based on organic memristors , 2010, Nano Commun. Networks.

[162]  Huagan Wu,et al.  Chaotic and periodic bursting phenomena in a memristive Wien-bridge oscillator , 2016 .

[163]  Y. Dan,et al.  Spike timing-dependent plasticity: a Hebbian learning rule. , 2008, Annual review of neuroscience.

[164]  Jimson Mathew,et al.  Efficient sensing approaches for high-density memristor sensor array , 2018 .

[165]  Philip D. Wasserman,et al.  Neural computing - theory and practice , 1989 .

[166]  Gregory S. Snider,et al.  ‘Memristive’ switches enable ‘stateful’ logic operations via material implication , 2010, Nature.

[167]  Seung Hwan Lee,et al.  Temporal data classification and forecasting using a memristor-based reservoir computing system , 2019, Nature Electronics.

[168]  Zhigang Zeng,et al.  Adjusting Learning Rate of Memristor-Based Multilayer Neural Networks via Fuzzy Method , 2019, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[169]  Oliver Pabst,et al.  The non-linear electrical properties of human skin make it a generic memristor , 2018, Scientific Reports.

[170]  Yusuf Leblebici,et al.  Memristive Biosensors Under Varying Humidity Conditions , 2014, IEEE Transactions on NanoBioscience.

[171]  Ali Khiat,et al.  Improving Detection Accuracy of Memristor-Based Bio-Signal Sensing Platform , 2017, IEEE Transactions on Biomedical Circuits and Systems.

[172]  Yi Shen,et al.  Compound synchronization of four memristor chaotic oscillator systems and secure communication. , 2013, Chaos.

[173]  V. V. Sharkov,et al.  Noise-induced resistive switching in a memristor based on ZrO2(Y)/Ta2O5 stack , 2019, Journal of Statistical Mechanics: Theory and Experiment.

[174]  I. Kang,et al.  Unconventional Inorganic‐Based Memristive Devices for Advanced Intelligent Systems , 2019, Advanced Materials Technologies.

[175]  Yanhao Du,et al.  Emerging Artificial Synaptic Devices for Neuromorphic Computing , 2019, Advanced Materials Technologies.

[176]  A. Volkov,et al.  Electrophysiology of pumpkin seeds: Memristors in vivo , 2016, Plant signaling & behavior.

[177]  Yusuf Leblebici,et al.  New Insight on Bio-sensing by Nano-fabricated Memristors , 2011 .

[178]  Daniele Ielmini,et al.  Brain-inspired computing with resistive switching memory (RRAM): Devices, synapses and neural networks , 2018 .

[179]  Victor Erokhin,et al.  First steps towards the realization of a double layer perceptron based on organic memristive devices , 2016 .

[180]  Jiewei Chen,et al.  2D Materials Based Optoelectronic Memory: Convergence of Electronic Memory and Optical Sensor , 2019, Research.

[181]  Sha Zhang,et al.  Flexible artificial nociceptor using a biopolymer-based forming-free memristor. , 2019, Nanoscale.

[182]  Jianfeng Feng,et al.  Material Memristive Device Circuits with Synaptic Plasticity: Learning and Memory , 2011 .

[183]  Xiaoping Wang,et al.  A Novel Memristor-Based Circuit Implementation of Full-Function Pavlov Associative Memory Accorded With Biological Feature , 2018, IEEE Transactions on Circuits and Systems I: Regular Papers.

[184]  Max Talanov,et al.  Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics , 2020, Frontiers in Neuroscience.

[185]  Rabia Riaz,et al.  Silver‐Adapted Diffusive Memristor Based on Organic Nitrogen‐Doped Graphene Oxide Quantum Dots (N‐GOQDs) for Artificial Biosynapse Applications , 2019, Advanced Functional Materials.

[186]  Lixin Dong,et al.  Fabrication of a W/CuxO/Cu memristor with sub-micron holes for passive sensing of oxygen , 2016 .

[187]  Jürgen Schmidhuber,et al.  Deep learning in neural networks: An overview , 2014, Neural Networks.

[188]  Doo Seok Jeong,et al.  Towards artificial neurons and synapses: a materials point of view , 2013 .

[189]  Kevin Staras,et al.  Role of Delayed Nonsynaptic Neuronal Plasticity in Long-Term Associative Memory , 2006, Current Biology.

[190]  Kenneth D Harris,et al.  Spike sorting for large, dense electrode arrays , 2015, Nature Neuroscience.

[191]  Eugene M. Izhikevich,et al.  Which model to use for cortical spiking neurons? , 2004, IEEE Transactions on Neural Networks.

[192]  Zhigang Zeng,et al.  Synchronization control of a class of memristor-based recurrent neural networks , 2012, Inf. Sci..

[193]  Massimiliano Di Ventra,et al.  Experimental demonstration of associative memory with memristive neural networks , 2009, Neural Networks.

[194]  M. Lei,et al.  A nonvolatile organic resistive switching memory based on lotus leaves , 2019, Chemical Physics.

[195]  Yu Chen,et al.  Polymer memristor for information storage and neuromorphic applications , 2014 .

[196]  Victor Erokhin.  On the Learning of Stochastic Networks of Organic Memristive Devices , 2013, Int. J. Unconv. Comput..

[197]  George G. Malliaras,et al.  Orientation selectivity with organic photodetectors and an organic electrochemical transistor , 2016 .

[198]  S. Zöld,et al.  The computational infrastructure of analogic CNN computing. I. The CNN-UM chip prototyping system , 1999 .

[199]  Victor Erokhin,et al.  Hysteresis loop and cross-talk of organic memristive devices , 2014, Microelectron. J..

[200]  Ojas Parekh,et al.  Energy Scaling Advantages of Resistive Memory Crossbar Based Computation and Its Application to Sparse Coding , 2016, Front. Neurosci..

[201]  V. Erokhin,et al.  Planar and 3D fibrous polyaniline-based materials for memristive elements. , 2017, Soft matter.

[202]  Ya Wang,et al.  The Electrical Activity of Neurons Subject to Electromagnetic Induction and Gaussian White Noise , 2017, Int. J. Bifurc. Chaos.

[203]  S. Iannotta,et al.  Prototyping a memristive-based device to analyze neuronal excitability. , 2019, Biophysical chemistry.

[204]  Bilge Saruhan,et al.  Effect of Pt/TiO2 interface on room temperature hydrogen sensing performance of memristor type Pt/TiO2/Pt structure , 2017 .

[205]  J. -M. Liu,et al.  Coexistence of high performance resistance and capacitance memory based on multilayered metal-oxide structures , 2013, Scientific Reports.

[206]  Leon O. Chua,et al.  Neuromemristive Circuits for Edge Computing: A Review , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[207]  Yoon-Ha Jeong,et al.  Optimization of Conductance Change in Pr1–xCaxMnO3-Based Synaptic Devices for Neuromorphic Systems , 2015, IEEE Electron Device Letters.

[208]  Toshiyuki Yamane,et al.  Recent Advances in Physical Reservoir Computing: A Review , 2018, Neural Networks.

[209]  Byung-Gook Park,et al.  Implementing an artificial synapse and neuron using a Si nanowire ion-sensitive field-effect transistor and indium-gallium-zinc-oxide memristors , 2019, Sensors and Actuators B: Chemical.

[210]  Frank Rosenblatt,et al.  PRINCIPLES OF NEURODYNAMICS. PERCEPTRONS AND THE THEORY OF BRAIN MECHANISMS , 1963 .

[211]  Paolo Camorani,et al.  Modeling and simulating the adaptive electrical properties of stochastic polymeric 3D networks , 2013 .

[212]  Daniele Ielmini,et al.  Resistive switching memories based on metal oxides: mechanisms, reliability and scaling , 2016 .

[213]  V. A. Slipko,et al.  Changing the state of a memristive system with white noise. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[214]  Zhen Liu,et al.  Synaptic long-term potentiation realized in Pavlov's dog model based on a NiOx-based memristor , 2014 .

[215]  Xiaobing Yan,et al.  Overview of Resistive Random Access Memory (RRAM): Materials, Filament Mechanisms, Performance Optimization, and Prospects , 2019, physica status solidi (RRL) – Rapid Research Letters.

[216]  D. Kolchanov,et al.  Inkjet assisted fabrication of planar biocompatible memristors , 2019, RSC advances.