Memristor simulate

In this document, first of all, code sections of memristor window functions (Strukov, Joglekar, Prodromakis and Biolek) were created in Pspice package program in detail. Then, the design of the wien bridge oscillator circuit with BJT with a memristor with different window functions was created. Finally, the system's oscillation start time, oscillation band settling time and center oscillation frequency analysis data were imported into the Matlab program and a comprehensive presentation was made. It was seen that the output responses of the wien bridge oscillator circuit realized with the Strukov window function were better than the other window functions. It has also been shown that designs that can be realized with memristor with different window functions in various analog oscillator circuits that can be made in the future can be obtained with this method.

The work describes the various methods of memristor modelling and simulation in the MATLAB and Simulink environment. Previously published papers about memristors and their features are used as the foundation of the work. There are three various methods used in the MATLAB and Simulink for the differential and other equations formulation. The first equation uses the standard system core offer for the Ordinary Differential Equations solutions (ODE) in the m- file form. The second solution is the model construction in Simulink environment. The third method includes a physical modelling using the built-in SimscapeTM system. The results are the basic memristor characteristics and appropriate time courses. The characteristics of all models and their computer simulations are described in the paper.

The work describes the various methods of memristor modelling and simulation in the MATLAB and Simulink environment. Previously published papers about memristors and their features are used as the foundation of the work. There are three various methods used in the MATLAB and Simulink for the differential and other equations formulation. The first equation uses the standard system core offer for the Ordinary Differential Equations solutions (ODE) in the m- file form. The second solution is the model construction in Simulink environment. The third method includes a physical modelling using the built-in SimscapeTM system. The results are the basic memristor characteristics and appropriate time courses. The characteristics of all models and their computer simulations are described in the paper.

Computers transform to the smaller, faster and more reliable devices year by year. Accordingly designing more efficient logic gates, as the basic blocks of the VLSI chips, are essential for circuit designers. Since the integration reached to its limits through the conventional technologies mainly the CMOS
based VLSI designs the quest for the novel promising
technologies was commenced. Memristor is a passive element
that has been fabricated recently and taken increasing attentions.
Less area and non-volatility are the most important properties of
this element. Also Memristors compatibility for fabrication over
CMOS structures makes it as a breakthrough for the VLSI
design enhancement. Memristor based logic computation are
developed primarily. This paper presents a novel
CMOS-Memristor based inverter with acceptable performance
and also has nonvolatile output. This feature makes this circuit to
be utilized not only as a conventional inverter circuit but also as a
SRAM memory cell with the capability of input negation for
specific applications. This includes a 0.18um PMOS and two
Memristors. The output voltage level, non-volatility and
read/write time is analyzed and simulated with Hspice.

Driven by the trends of increasing core-count and bandwidth-wall problem, the size of last level caches (LLCs) has greatly increased. Since SRAM consumes high leakage power, researchers have explored use of non-volatile memories (NVMs) for designing caches as they provide high density and consume low leakage power. However, since NVMs have low write-endurance and the existing cache management policies are write variation-unaware, effective wear-leveling techniques are required for achieving reasonable cache lifetimes using NVMs. We present WriteSmoothing, a technique for mitigating intra-set write variation in NVM caches.  WriteSmoothing logically divides the cache-sets into multiple modules. For each module, WriteSmoothing collectively records number of writes in each way for any of the sets. It then periodically makes most frequently written ways in a module unavailable to shift the write-pressure to other ways in the sets of the module. Extensive simulation results have shown that on average, for single and dual-core system configurations, WriteSmoothing improves cache lifetime by 2.17X and 2.75X, respectively. Also, its implementation overhead is small and it works well for a  wide range of algorithm and system parameters.

The memristor is an electrical circuit element that is similar to a resistor but has the potential to maintain state between turning power on and off. These memristors are about half the size of the transistors found in current flash storage technology, allowing capacity of these devices to double. This paper discusses the basics of memristors, which is an electrical circuit element, and presents the first principle simulation results of Pt/TiO2-x - TiO2/Pt system where the central region has a boundary separating TiO2-x and TiO2 regions. This barrier is progressively shifted towards the TiO2-x region with applied bias to gradually increase the thickness of TiO2 region. A comparison of the electrical characteristics of the device when the TiO2 region is extended towards TiO2-x region is also presented. The basis of memristive behavior, the non linear hysteresis curve of memristor, has been obtained based upon the simulation results.

Memristor devices are crucial for developing neuromorphic computers and next-generation memory technologies. In this work, we provide a comprehensive modelling tool for simulating static DC reading operations of memristor crossbar arrays that use passive selectors with matrix algebra in MATLAB. The software tool was parallel coded and optimized to run with personal computers and distributed computer clusters with minimized CPU and memory consumption. We study the effect of changing the line resistance, array size, voltage selection scheme, selector diode’s ideality factor, reverse saturation current and sense resistance on the electrical behaviour and expected sense margin of a conventional one-diode-one-resistor crossbar arrays. We then investigate the effect of single and dual side array biasing and grounding on the dissipated current throughout the array cells. The tool we offer to the memristor community and the studies we present enables the design of larger and more practical memristor arrays for application in data storage and neuromorphic computing.

Memristor (short for memory resistor) is the fundamental electronic device theoretically proposed by Chua in and physically designed in HP labs. The invention of physical memristor caused the significant interest among researchers. Many attempts for creation of precise device model were made. The new approach for memristor modeling was proposed basing on the device’s dimensions and material properties. The findings reveal interesting relations such as nonlinear relationship between the device area and the width of pinched hysteresis loop and positive relationship between resistivity of the device and the area inside the pinched-hysteresis loop.

An important endeavor in modern materials science is the synthesis of adaptive assemblies with information processing capabilities similar to those of biological neural systems. Recent developments concern materials functionally similar to the memristor, a notional electrical circuit whose conductivity is dependent on past activity. This feature is analogous to synaptic plasticity: the ability of neurons to modify their synaptic connections as a result of accumulated experience—the basis of learning and the formation of memory. In this paper, we present the first evidence that memristive device-based organic materials show adaptive behavior similar to biological cognitive systems, using learning in the feeding neural network of the pond snail, Lymnaea stagnalis, as a specific biological reference. The synthetic reproduction of synaptic plasticity reported here can create new paradigms for novel comput- ing systems and give impetus to the search for bio-inspired nanoscale molecular architectures capable of learning and decision making.

Memristors are passive two-terminal circuit elements that combine resistance and memory. Although in theory memristors are a very promising approach to fabricate hardware with adaptive properties, there are only very few implementations able to show their basic properties. We recently developed stochastic polymeric matrices with a functionality that evidences the formation of self-assembled three-dimensional (3D) networks of memristors. We demonstrated that those networks showthe typical hysteretic behavior observed in the ‘one input-one output’ memristive configuration. Interestingly, using different protocols to electrically stimulate the networks, we also observed that their adaptive properties are similar to those present in the nervous
system. Here, we model and simulate the electrical properties of these selfassembled polymeric networks of memristors, the topology of which is defined stochastically. First, we show that the model recreates the hysteretic behavior observed in the real experiments. Second, we demonstrate that the networks modeled indeed have a 3D instead of a planar functionality. Finally, we show that the adaptive properties of the networks depend on their connectivity pattern.
Our model was able to replicate fundamental qualitative behavior of the real organic 3D memristor networks; yet, through the simulations, we also explored other interesting properties, such as the relation between connectivity patterns and adaptive properties. Our model and simulations represent an interesting
tool to understand the very complex behavior of self-assembled memristor networks, which can finally help to predict and formulate hypotheses for future experiments.

In this study, fourth basic circuit element with two-terminals is performed using
memristor circuit simulations in their response to different types of input signals of different types were compared. Also, tested the effect on output in different frequency ranges is examined. By comparing the ratio of input voltage to output voltage, behavior with respect to frequency are evaluated. Firstly, reference model of a memristor circuit drawing program PSPICE simulation performed, terminal relations are provided. Joglekar, Biolek, Strukov and Prodromakis memristor types, one by one formed in the PSPICE program mathematical model of the window functions was
created. The output characteristics through the codes of different window functions are generated by specifying the type of memristor in the PSPICE program were compared. Non-linear drift memristor model with internal structure, dismissed with the PSPICE codes are explained. The simplified integrated circuit configurations are expressed and terminal relations are calculated. With this study, different frequencies applied to an input, by examining the effect of memristor output voltage parameters for different windows functions and different analog circuits in the advanced
functions which change the sensitivity memristor type will provide advantages in terms of detection would be more efficient.

Öz: Bu çalışmada ilk olarak Alharbi, Muthuswamy ile Mutlu ve arkadaşları tarafından literatürde önerilen memristör taklit devrelerinin Multisim programında düşük frekanslarda (5Hz-150Hz) benzetimi yapıldı. Taklit devreleri için farklı frekanslarda akım-gerilim (I-V) eğrileri incelenerek en kararlı çıkış eğrisini veren Mutlu ve arkadaşları tarafından önerilen devre gerçekleştirildi. Bu devre kullanılarak 2. dereceden aktif yüksek geçiren filtre devresi tasarlandı. Memristörlü ve direnç kullanılarak gerçekleştirilen filtre devreleri kalite faktörleri, Bode diyagramları ve kesim frekansları açısından karşılaştırıldı. Memristörlü filtre devresinin 0-10 Hz frekans aralığında direnç kullanılarak gerçekleştirilen filtre devresinden daha iyi süzme işlemi yaptığı görüldü.

In laboratory experiments, we demonstrate that protoplasmic tubes of the acellular slime mould Physarum polycephalum show current versus voltage profiles consistent with memristive systems, and that this effect is due to the living protoplasm of the mould. This complements previous findings on memristive properties of other living systems (human skin and blood) and contributes to the development of self-growing bio-electronic circuits. Distinctive asymmetric V–I curves which were occasionally observed when the internal current is on the same order as the driven current, are well-modelled by the concept of active memristors.

In this document, first of all, code sections of memristor window functions (Strukov, Joglekar, Biolek and Prodromakis) were created in Pspice package program in detail. Then, the design of the wien bridge oscillator circuit with BJT with a memristor with different window functions was created. Finally, the system's oscillation start time, oscillation band settling time and center oscillation frequency analysis data were imported into the Matlab program and a comprehensive presentation was made. It was seen that the output responses of the wien bridge oscillator circuit realized with the Strukov window function were better than the other window functions. It has also been shown that designs that can be realized with memristor with different window functions in various analog oscillator circuits that can be made in the future can be obtained with this method.

The present communication deals with the development of the titanium dioxide (TiO 2) thin films memristor using simple and cost effective hydrothermal route for neuromorphic application. The developed devices show pinched hysteresis loop in current-voltage (I-V) plane, which is the fingerprint characteristic of a memristor. Furthermore, current in the device continuously increases and decreases similar to synaptic weights of the biological neurons. The rectifying property similar to biological synapse is observed in the device which can be converted into the non-rectifying property by the suitable surfactant. The proper surfactant is responsible for the control of data flow in the memristor-based electronic synapse.

Gale, E., Adamatzky, A. and de Lacy Costello, B. (2012) Fabrication and modelling of titanium dioxide memristors. In: RSC Younger Members Symposium 2012, Nottingham, UK, 13 June 2012. ... We recommend you cite the published version. The publisher's URL is http://eprints.uwe.ac.uk/17057/ ... Poster abstract was referred and selected for conference. ... UWE has obtained warranties from all depositors as to their title in the material deposited and as to their right to deposit such material. ... UWE makes no representation or warranties ...