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Leon O. Chua - One of the best experts on this subject based on the ideXlab platform.

  • Dynamics of Memristor Circuits
    International Journal of Bifurcation and Chaos, 2020
    Co-Authors: Makoto Itoh, Leon O. Chua
    Abstract:

    In this paper, we show that Hamilton's equations can be recast into the equations of dissipative Memristor circuits. In these Memristor circuits, the Hamiltonians can be obtained from the principles of conservation of "charge" and "flux", or the principles of conservation of "energy". Furthermore, the dynamics of Memristor circuits can be recast into the dynamics of "ideal Memristor" circuits. We also show that nonlinear capacitors are transformed into nonideal Memristors if an exponential coordinate transformation is applied. Furthermore, we show that the zero-crossing phenomenon does not occur in some Memristor circuits because the trajectories do not intersect the i = 0 axis. We next show that nonlinear circuits can be realized with fewer elements if we use Memristors. For example, Van der Pol oscillator can be realized by only two elements: an inductor and a Memristor. Chua's circuit can be realized by only three elements: an inductor, a capacitor, and a voltage-controlled Memristor. Finally, we show an example of two-cell Memristor CNNs. In this system, the neuron's activity depends partly on the supplied currents of the Memristors.

  • Memory elements in the electrical network of Mimosa pudica L.
    Plant Signaling & Behavior, 2014
    Co-Authors: Alexander G. Volkov, Vladislav S. Markin, Jada Reedus, Colee M. Mitchell, Clayton Tuckett, Maya I. Volkova, Leon O. Chua
    Abstract:

    The fourth basic circuit element, a Memristor, is a resistor with memory that was postulated by Chua in 1971. Here we found that Memristors exist in vivo. The electrostimulation of the Mimosa pudica by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of Memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar sinusoidal or triangle periodic electrostimulating waves. Memristive behavior of an electrical network in the Mimosa pudica is linked to the properties of voltage gated ion channels: the channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K+ channel in the excitable tissue of plants has properties of a Memristor. The discovery of Memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants.

  • An analytical model of Memristors in plants
    Plant Signaling & Behavior, 2014
    Co-Authors: Vladislav S. Markin, Alexander G. Volkov, Leon O. Chua
    Abstract:

    The Memristor, a resistor with memory, was postulated by Chua in 1971 and the first solid-state Memristor was built in 2008. Recently, we found Memristors in vivo in plants. Here we propose a simple analytical model of 2 types of Memristors that can be found within plants. The electrostimulation of plants by bipolar periodic waves induces electrical responses in the Aloe vera and Mimosa pudica with fingerprints of Memristors. Memristive properties of the Aloe vera and Mimosa pudica are linked to the properties of voltage gated K+ ion channels. The potassium channel blocker TEACl transform plant Memristors to conventional resistors. The analytical model of a Memristor with a capacitor connected in parallel exhibits different characteristic behavior at low and high frequency of applied voltage, which is the same as experimental data obtained by cyclic voltammetry in vivo.

  • Memristors in the Venus flytrap
    Plant Signaling & Behavior, 2014
    Co-Authors: Alexander G. Volkov, Vladislav S. Markin, Jada Reedus, Colee M. Mitchell, Victoria Forde-tuckett, Maya I. Volkova, Leon O. Chua
    Abstract:

    A Memristor is a nonlinear element because its current-voltage characteristic is similar to that of a Lissajous pattern for nonlinear systems. We investigated the possible presence of Memristors in the electrical circuitry of the Venus flytrap’s upper and lower leaves. The electrostimulation of this plant by bipolar sinusoidal or triangle periodic waves induces electrical responses in the upper and lower leaves of the Venus flytrap with fingerprints of Memristors. The analysis was based on cyclic voltammetric characteristics where the Memristor, a resistor with memory, should manifest itself. Tetraethylammonium chloride, an inhibitor of voltage gated K+ channels, or NPPB, a blocker of voltage gated Cl- and K+ channels, transform a Memristor to a resistor in plant tissue. Uncouplers carbonylcyanide-3-chlorophenylhydrazone (CCCP) and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone (FCCP) decrease the amplitude of electrical responses at low and high frequencies of bipolar periodic electrostimulating waves. Our results demonstrate that voltage gated K+ channels in the Venus flytrap have properties of Memristors of type 1 and type 2. The discovery of Memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants.

  • Memristor Networks
    2014
    Co-Authors: Andrew Adamatzky, Leon O. Chua
    Abstract:

    Using Memristors one can achieve circuit functionalities that are not possible to establish with resistors, capacitors and inductors, therefore the Memristor is of great pragmatic usefulness. Potential unique applications of Memristors are in spintronic devices, ultra-dense information storage, neuromorphic circuits and programmable electronics. Memristor Networks focuses on the design, fabrication, modelling of and implementation of computation in spatially extended discrete media with many Memristors. Top experts in computer science, mathematics, electronics, physics and computer engineering present foundations of the Memristor theory and applications, demonstrate how to design neuromorphic network architectures based on Memristor assembles, analyse varieties of the dynamic behaviour of memristive networks and show how to realise computing devices from Memristors. All aspects of Memristor networks are presented in detail, in a fully accessible style. An indispensable source of information and an inspiring reference text, Memristor Networks is an invaluable resource for future generations of computer scientists, mathematicians, physicists and engineers.

Hyongsuk Kim - One of the best experts on this subject based on the ideXlab platform.

  • Linear programming of voltage-controlled Memristors with an anti-serial Memristor circuit
    2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015
    Co-Authors: Hyuncheol Choi, Changju Yang, Ram Kaji Budhathoki, Sedong Park, Hyongsuk Kim
    Abstract:

    The memristance variation of a single Memristor with voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of Memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is addressed. The anti-serial architecture is composed of two Memristors with opposite polarities. It linearizes the variation of memristance by virtue of complimentary actions of two Memristors. For programming a Memristor, additional Memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and Memristor bridge synapse which is built with two sets of anti-serial Memristor architecture is taken as an application example of the proposed method.

  • ISCAS - Linear programming of voltage-controlled Memristors with an anti-serial Memristor circuit
    2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015
    Co-Authors: Hyuncheol Choi, Changju Yang, Ram Kaji Budhathoki, Sedong Park, Hyongsuk Kim
    Abstract:

    The memristance variation of a single Memristor with voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of Memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is addressed. The anti-serial architecture is composed of two Memristors with opposite polarities. It linearizes the variation of memristance by virtue of complimentary actions of two Memristors. For programming a Memristor, additional Memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and Memristor bridge synapse which is built with two sets of anti-serial Memristor architecture is taken as an application example of the proposed method.

  • Behavior of Multiple Memristor Circuits
    Memristor Networks, 2014
    Co-Authors: Ram Kaji Budhathoki, Shyam Prasad Adhikari, Hyongsuk Kim, Maheshwar Pd Sah, Leon O. Chua
    Abstract:

    Memristor is a new circuit element defined by a state-dependent Ohm’s law between the Memristor voltage and current. It has recently been successfully built, however, its electrical characteristics are not fully known yet. Like other circuit elements R, L and C, there could have various configurations of multiple Memristors including serial and parallel connections in a variety of applications. When input voltage/current is supplied to a circuit with multiple Memristors, behavior of the device becomes complicated and is difficult to predict. In this chapter, composite characteristics of the serial and parallel connections of Memristors are investigated using both linear and nonlinear models. Also, the behavior of individual Memristor is formulated mathematically and a general computation method of composite memristance for multiple Memristor circuits of diverse configurations is proposed.

  • Brains Are Made of Memristors
    IEEE Circuits and Systems Magazine, 2014
    Co-Authors: Maheshwar Pd Sah, Hyongsuk Kim, Leon O. Chua
    Abstract:

    This exposition shows that the potassium ion-channels and the sodium ion-channels that are distributed over the entire length of the axons of our neurons are in fact locally-active Memristors. In particular, they exhibit all of the fingerprints of Memristors, including the characteristic pinched hysteresis Lissajous figures in the voltage-current plane, whose loop areas shrink as the frequency of the periodic excitation signal increases. Moreover, the pinched hysteresis loops for the potassium ion-channel Memristor, and the sodium ion-channel Memristor, from the Hodgkin-Huxley axon circuit model are unique for each periodic excitation signal. An in-depth circuit-theoretic analysis and characterizations of these two classic biological Memristors are presented via their small-signal memristive equivalent circuits, their frequency response, and their Nyquist plots. Just as the Hodgkin-Huxley circuit model has stood the test of time, its constituent potassium ion-channel and sodium ion-channel Memristors are destined to be classic examples of locally-active Memristors in future textbooks on circuit theory and bio-physics.

  • Memristor emulator with off-the-shelf solid state components for Memristor application circuits
    2012 13th International Workshop on Cellular Nanoscale Networks and their Applications, 2012
    Co-Authors: Changju Yang, Maheshwar Pd Sah, Ki-sang Jung, Seong-ik Cho, Hyongsuk Kim
    Abstract:

    A Memristor emulator circuit which is designed with off-the-shelf solid state components is presented. As the Memristors are not commercially available so far, some circuit replacements which behave like Memristors are needed to develop application circuits. In this paper, the variable resistance of a Memristor is built utilizing the input resistance of the closed loop circuit of an OP amp. The Memristor emulator circuit has been implemented on breadboard with off-the-shelf solid state components. The experimental results of the proposed Memristor emulator circuit show a Memristor behavior that can be utilized as an alternative of hp TiO2 Memristor model.

Eby G. Friedman - One of the best experts on this subject based on the ideXlab platform.

  • Memristor based circuit design for multilayer neural networks
    IEEE Transactions on Circuits and Systems I-regular Papers, 2018
    Co-Authors: Yang Zhang, Xiao Ping Wang, Eby G. Friedman
    Abstract:

    Memristors are promising components for applications in nonvolatile memory, logic circuits, and neuromorphic computing. In this paper, a novel circuit for Memristor-based multilayer neural networks is presented, which can use a single Memristor array to realize both the plus and minus weight of the neural synapses. In addition, Memristor-based switches are utilized during the learning process to update the weight of the Memristor-based synapses. Moreover, an adaptive back propagation algorithm suitable for the proposed Memristor-based multilayer neural network is applied to train the neural networks and perform the XOR function and character recognition. Another highlight of this paper is that the robustness of the proposed Memristor-based multilayer neural network exhibits higher recognition rates and fewer cycles as compared with other multilayer neural networks.

  • MAGIC—Memristor-Aided Logic
    IEEE Transactions on Circuits and Systems Ii-express Briefs, 2014
    Co-Authors: Shahar Kvatinsky, Dmitry Belousov, Slavik Liman, Avinoam Kolodny, Guy Satat, Nimrod Wald, Eby G. Friedman, Uri C. Weiser
    Abstract:

    Memristors are passive components with a varying resistance that depends on the previous voltage applied across the device. While Memristors are naturally used as memory, Memristors can also be used for other applications, including logic circuits. In this brief, a Memristor-only logic family, i.e., Memristor-aided logic (MAGIC), is presented. In each MAGIC logic gate, Memristors serve as an input with previously stored data, and an additional Memristor serves as an output. The topology of a MAGIC nor gate is similar to the structure of a common Memristor-based crossbar memory array. A MAGIC nor gate can therefore be placed within memory, providing opportunities for novel non-von Neumann computer architectures. Other MAGIC gates also exist (e.g., and , or , not , and nand ) and are described in this brief.

  • MAGIC - Memristor-aided logic
    IEEE Transactions on Circuits and Systems II: Express Briefs, 2014
    Co-Authors: Shahar Kvatinsky, Dmitry Belousov, Slavik Liman, Avinoam Kolodny, Guy Satat, Nimrod Wald, Eby G. Friedman, Uri C. Weiser
    Abstract:

    Memristors are passive components with a varying resistance that depends on the previous voltage applied across the device. While Memristors are naturally used as memory, Memristors can also be used for other applications, including logic circuits. In this brief, a Memristor-only logic family, i.e., Memristor-aided logic (MAGIC), is presented. In each MAGIC logic gate, Memristors serve as an input with previously stored data, and an additional Memristor serves as an output. The topology of a MAGIC nor gate is similar to the structure of a common Memristor-based crossbar memory array. A MAGIC nor gate can therefore be placed within memory, providing opportunities for novel non-von Neumann computer architectures. Other MAGIC gates also exist (e.g., and, or, not, and nand) and are described in this brief.

  • The desired Memristor for circuit designers
    IEEE Circuits and Systems Magazine, 2013
    Co-Authors: Shahar Kvatinsky, Avinoam Kolodny, Eby G. Friedman, Uri C. Weiser
    Abstract:

    Memristors are two-terminal devices with varying resistance, where the behavior is dependent on the history of the device. In recent years, different physical phenomena of resistive switching have been linked with the theoretical concept of a Memristor, and several emerging memory devices (e.g., Phase Change Memory, Resistive RAM, STT-MRAM) are now considered as Memristors. Memristors hold promise for use in diverse applications such as memory, digital logic, analog circuits, and neuromorphic systems. Important characteristics of Memristors include high speed, low power, good scalability, data retention, endurance, and compatibility with conventional CMOS in terms of manufacturing and operating voltages. One interesting property of some Memristors is a nonlinear response to current or voltage. Nonlinear Memristors exhibit a current or voltage threshold, such that the resistance is affected only by currents or voltages which exceed the threshold, while the resistance of a linear Memristor changes with small perturbations in device current. Different applications exploit different characteristics of a Memristor. In this article, the desired characteristics for different applications are presented from the viewpoint of an integrated circuit designer. Understanding the desired characteristics for different applications can assist device and material engineers in providing the appropriate behavior when developing memristive devices, thereby optimizing these devices for different applications.

  • Models of Memristors for SPICE simulations
    2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, 2012
    Co-Authors: Shahar Kvatinsky, Avinoam Kolodny, Keren Talisveyberg, Dmitry Fliter, Uri C. Weiser, Eby G. Friedman
    Abstract:

    Memristors are novel devices which can be used in applications such as memory, logic, analog circuits, and neuromorphic systems. Several Memristor technologies have been developed such as ReRAM (Resistive RAM), MRAM (Magnetoresistance RAM), and PCM (Phase Change Memory). To design circuits with Memristors, the behavior of the Memristor needs to be described by a mathematical model. While the model for Memristors should be sufficiently accurate as compared to the behavior of physical devices, the model must also be computationally efficient. Several models for Memristors have been proposed — the linear ion drift model, the nonlinear ion drift model, the Simmons tunnel barrier model, and the ThrEshold Adaptive Memristor (TEAM) model. In this paper, the different Memristor models are described and a Verilog-A implementation for these models, including the relevant window functions, are presented. These models are suitable for EDA tools such as SPICE.

Uri C. Weiser - One of the best experts on this subject based on the ideXlab platform.

  • MAGIC—Memristor-Aided Logic
    IEEE Transactions on Circuits and Systems Ii-express Briefs, 2014
    Co-Authors: Shahar Kvatinsky, Dmitry Belousov, Slavik Liman, Avinoam Kolodny, Guy Satat, Nimrod Wald, Eby G. Friedman, Uri C. Weiser
    Abstract:

    Memristors are passive components with a varying resistance that depends on the previous voltage applied across the device. While Memristors are naturally used as memory, Memristors can also be used for other applications, including logic circuits. In this brief, a Memristor-only logic family, i.e., Memristor-aided logic (MAGIC), is presented. In each MAGIC logic gate, Memristors serve as an input with previously stored data, and an additional Memristor serves as an output. The topology of a MAGIC nor gate is similar to the structure of a common Memristor-based crossbar memory array. A MAGIC nor gate can therefore be placed within memory, providing opportunities for novel non-von Neumann computer architectures. Other MAGIC gates also exist (e.g., and , or , not , and nand ) and are described in this brief.

  • MAGIC - Memristor-aided logic
    IEEE Transactions on Circuits and Systems II: Express Briefs, 2014
    Co-Authors: Shahar Kvatinsky, Dmitry Belousov, Slavik Liman, Avinoam Kolodny, Guy Satat, Nimrod Wald, Eby G. Friedman, Uri C. Weiser
    Abstract:

    Memristors are passive components with a varying resistance that depends on the previous voltage applied across the device. While Memristors are naturally used as memory, Memristors can also be used for other applications, including logic circuits. In this brief, a Memristor-only logic family, i.e., Memristor-aided logic (MAGIC), is presented. In each MAGIC logic gate, Memristors serve as an input with previously stored data, and an additional Memristor serves as an output. The topology of a MAGIC nor gate is similar to the structure of a common Memristor-based crossbar memory array. A MAGIC nor gate can therefore be placed within memory, providing opportunities for novel non-von Neumann computer architectures. Other MAGIC gates also exist (e.g., and, or, not, and nand) and are described in this brief.

  • The desired Memristor for circuit designers
    IEEE Circuits and Systems Magazine, 2013
    Co-Authors: Shahar Kvatinsky, Avinoam Kolodny, Eby G. Friedman, Uri C. Weiser
    Abstract:

    Memristors are two-terminal devices with varying resistance, where the behavior is dependent on the history of the device. In recent years, different physical phenomena of resistive switching have been linked with the theoretical concept of a Memristor, and several emerging memory devices (e.g., Phase Change Memory, Resistive RAM, STT-MRAM) are now considered as Memristors. Memristors hold promise for use in diverse applications such as memory, digital logic, analog circuits, and neuromorphic systems. Important characteristics of Memristors include high speed, low power, good scalability, data retention, endurance, and compatibility with conventional CMOS in terms of manufacturing and operating voltages. One interesting property of some Memristors is a nonlinear response to current or voltage. Nonlinear Memristors exhibit a current or voltage threshold, such that the resistance is affected only by currents or voltages which exceed the threshold, while the resistance of a linear Memristor changes with small perturbations in device current. Different applications exploit different characteristics of a Memristor. In this article, the desired characteristics for different applications are presented from the viewpoint of an integrated circuit designer. Understanding the desired characteristics for different applications can assist device and material engineers in providing the appropriate behavior when developing memristive devices, thereby optimizing these devices for different applications.

  • Models of Memristors for SPICE simulations
    2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, 2012
    Co-Authors: Shahar Kvatinsky, Avinoam Kolodny, Keren Talisveyberg, Dmitry Fliter, Uri C. Weiser, Eby G. Friedman
    Abstract:

    Memristors are novel devices which can be used in applications such as memory, logic, analog circuits, and neuromorphic systems. Several Memristor technologies have been developed such as ReRAM (Resistive RAM), MRAM (Magnetoresistance RAM), and PCM (Phase Change Memory). To design circuits with Memristors, the behavior of the Memristor needs to be described by a mathematical model. While the model for Memristors should be sufficiently accurate as compared to the behavior of physical devices, the model must also be computationally efficient. Several models for Memristors have been proposed — the linear ion drift model, the nonlinear ion drift model, the Simmons tunnel barrier model, and the ThrEshold Adaptive Memristor (TEAM) model. In this paper, the different Memristor models are described and a Verilog-A implementation for these models, including the relevant window functions, are presented. These models are suitable for EDA tools such as SPICE.

  • Memristor-based IMPLY logic design procedure
    Proceedings - IEEE International Conference on Computer Design: VLSI in Computers and Processors, 2011
    Co-Authors: Shahar Kvatinsky, Avinoam Kolodny, Uri C. Weiser, Eby G. Friedman
    Abstract:

    Memristors can be used as logic gates. No design methodology exists, however, for Memristor-based combinatorial logic. In this paper, the design and behavior of a memristive-based logic gate - an IMPLY gate - are presented and design issues such as the tradeoff between speed (fast write times) and correct logic behavior are described, as part of an overall design methodology. A Memristor model is described for determining the write time and state drift. It is shown that the widely used Memristor model - a linear ion drift Memristor - is impractical for characterizing an IMPLY logic gate, and a different Memristor model is necessary such as a Memristor with a current threshold.

Leon Chua - One of the best experts on this subject based on the ideXlab platform.

  • If it's pinched it's a Memristor
    Memristors and Memristive Systems, 2014
    Co-Authors: Leon Chua
    Abstract:

    This paper presents an in-depth review of the Memristor from a rigorous circuit-theoretic\n perspective, independent of the material the device is made of. From an experimental perspective, a\n Memristor is best defined as any two-terminal device that exhibits a pinched hysteresis loop in the\n voltage – current plane when driven by any periodic voltage or current signal that elicits a\n periodic response of the same frequency. This definition greatly broadens the scope of memristive\n devices to encompass even non-semiconductor devices, both organic and inorganic, from many unrelated\n disciplines, including biology, botany, brain science, etc. For pedagogical reasons, the broad\n terrain of Memristors is partitioned into three classes of increasing generality, dubbed Ideal\n Memristors , Generic Memristors , and Extended Memristors . Each class is distinguished from the\n others via unique fingerprints and signatures. This paper clarifies many confusing issues, such as\n non-volatility, dc V–I curves, high-frequency v–i curves, local activity, as well as nonlinear\n dynamical and bifurcation phenomena that are the hallmarks of memristive devices. Above all, this\n paper addresses several fundamental issues and questions that many Memristor researchers do not\n comprehend but are afraid to ask.

  • Memristor, Hodgkin–Huxley, and Edge of Chaos
    Nanotechnology, 2013
    Co-Authors: Leon Chua
    Abstract:

    From a pedagogical point of view, the Memristor is defined in this tutorial as any 2-terminal device obeying a state-dependent Ohm's law. This tutorial also shows that from an experimental point of view, the Memristor can be defined as any 2-terminal device that exhibits the fingerprints of 'pinched' hysteresis loops in the v-i plane. It also shows that Memristors endowed with a continuum of equilibrium states can be used as non-volatile analog memories. This tutorial shows that Memristors span a much broader vista of complex phenomena and potential applications in many fields, including neurobiology. In particular, this tutorial presents toy Memristors that can mimic the classic habituation and LTP learning phenomena. It also shows that sodium and potassium ion-channel Memristors are the key to generating the action potential in the Hodgkin-Huxley equations, and that they are the key to resolving several unresolved anomalies associated with the Hodgkin-Huxley equations. This tutorial ends with an amazing new result derived from the new principle of local activity, which uncovers a minuscule life-enabling 'Goldilocks zone', dubbed the edge of chaos, where complex phenomena, including creativity and intelligence, may emerge. From an information processing perspective, this tutorial shows that synapses are locally-passive Memristors, and that neurons are made of locally-active Memristors.

  • Memristor, hodgkin-huxley, and edge of chaos
    Nanotechnology, 2013
    Co-Authors: Leon Chua
    Abstract:

    From a pedagogical point of view, the Memristor is defined in this tutorial as any 2-terminal device obeying a state-dependent Ohm's law. This tutorial also shows that from an experimental point of view, the Memristor can be defined as any 2-terminal device that exhibits the fingerprints of 'pinched' hysteresis loops in the v-i plane. It also shows that Memristors endowed with a continuum of equilibrium states can be used as non-volatile analog memories. This tutorial shows that Memristors span a much broader vista of complex phenomena and potential applications in many fields, including neurobiology. In particular, this tutorial presents toy Memristors that can mimic the classic habituation and LTP learning phenomena. It also shows that sodium and potassium ion-channel Memristors are the key to generating the action potential in the Hodgkin-Huxley equations, and that they are the key to resolving several unresolved anomalies associated with the Hodgkin-Huxley equations. This tutorial ends with an amazing new result derived from the new principle of local activity, which uncovers a minuscule life-enabling 'Goldilocks zone', dubbed the edge of chaos, where complex phenomena, including creativity and intelligence, may emerge. From an information processing perspective, this tutorial shows that synapses are locally-passive Memristors, and that neurons are made of locally-active Memristors. © 2013 IOP Publishing Ltd.

  • Memristor bridge synapses
    Proceedings of the IEEE, 2012
    Co-Authors: Hyongsuk Kim, Changju Yang, Maheshwar Pd Sah, Leon Chua, Tamás Roska, Leon O. Chua
    Abstract:

    In this paper, we propose a Memristor bridge circuit consisting of four identical Memristors that is able to perform zero, negative, and positive synaptic weightings. To- gether with three additional transistors, the Memristor bridge weighting circuit is able to perform synaptic operation for neural cells. It is compact as both weighting and weight prog- ramming are performed in a Memristor bridge synapse. It is power efficient, since the operation is based on pulsed input signals. Its input terminals are utilized commonly for applying both weight programming and weight processing signals via time sharing. In this paper, features of the Memristor bridge synapses are investigated using the TiO2 Memristor model via simulations.

  • Memristor-based multilevel memory
    2010 12th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA 2010), 2010
    Co-Authors: Hyongsuk Kim, Changju Yang, Maheshwar Pd Sah, Leon Chua, Leon O. Chua
    Abstract:

    A method to utilize the Memristor as a multilevel memory has been proposed. There are several roadblocks in the practical use of Memristors for multilevel memory. A difficulty comes from the nonlinearity in the ¿ vs. q curve which makes it difficult to determine the proper pulse width for desired resistance values. Another one comes from the property of the Memristor which integrates any kind of signals including noise that appeared at the Memristor and causes Memristors to be perturbed from their original values. The proposed method enables the Memristor to be used as multilevel memory using a reference resistance array by forcing the Memristor to stick at a set of predetermined fixed reference resistance values. We propose the write-in (programming) circuit and the readout/restoration circuit which share the information storing technique using the reference resistance array.