156 research outputs found
Reliable Modeling of Ideal Generic Memristors via State-Space Transformation
The paper refers to problems of modeling and computer simulation of generic memristors caused by the so-called window functions, namely the stick effect, nonconvergence, and finding fundamentally incorrect solutions. A profoundly different modeling approach is proposed, which is mathematically equivalent to window-based modeling. However, due to its numerical stability, it definitely smoothes the above problems away
Differential Equations of Ideal Memristors
Ideal memristor is a resistor with a memory, which adds dynamics to its behavior. The most usual characteristics describing this dynamics are the constitutive relation (i.e. the relation between flux and charge), or Parameter-vs-state- map (PSM), mostly represented by the memristance-to-charge dependence. One of the so far unheeded tools for memristor description is its differential equation (DEM), composed exclusively of instantaneous values of voltage, current, and their derivatives. The article derives a general form of DEM that holds for any ideal memristor and shows that it is always a nonlinear equation of the first order; the PSM forms are found for memristors which are governed by DEMs of the Bernoulli and the Riccati types; a classification of memristors according to the type of their dynamics with respect to voltage and current is carried out
Reliable SPICE Simulations of Memristors, Memcapacitors and Meminductors
Memory circuit elements, namely memristive, memcapacitive and meminductive systems, are gaining considerable attention due to their ubiquity and use in diverse areas of science and technology. Their modeling within the most widely used environment, SPICE, is thus critical to make substantial progress in the design and analysis of complex circuits. Here, we present a collection of models of different memory circuit elements and provide a methodology for their accurate and reliable modeling in the SPICE environment. We also provide codes of these models written in the most popular SPICE versions (PSpice, LTspice, HSPICE) for the benefit of the reader. We expect this to be of great value to the growing community of scientists interested in the wide range of applications of memory circuit elements
First order devices, hybrid memristors, and the frontiers of nonlinear circuit theory
Several devices exhibiting memory effects have shown up in nonlinear circuit
theory in recent years. Among others, these circuit elements include Chua's
memristors, as well as memcapacitors and meminductors. These and other related
devices seem to be beyond the, say, classical scope of circuit theory, which is
formulated in terms of resistors, capacitors, inductors, and voltage and
current sources. We explore in this paper the potential extent of nonlinear
circuit theory by classifying such mem-devices in terms of the variables
involved in their constitutive relations and the notions of the differential-
and the state-order of a device. Within this framework, the frontier of first
order circuit theory is defined by so-called hybrid memristors, which are
proposed here to accommodate a characteristic relating all four fundamental
circuit variables. Devices with differential order two and mem-systems are
discussed in less detail. We allow for fully nonlinear characteristics in all
circuit elements, arriving at a rather exhaustive taxonomy of C^1-devices.
Additionally, we extend the notion of a topologically degenerate configuration
to circuits with memcapacitors, meminductors and all types of memristors, and
characterize the differential-algebraic index of nodal models of such circuits.Comment: Published in 2013. Journal reference included as a footnote in the
first pag
Memcapacitor and Meminductor Circuit Emulators: A Review
This research was funded by the Japanese KAKENHI through Grant Number JP18k04275 and Spanish Ministry of Education, Culture, and Sport (MECD), through Project TEC2017-89955-P and Grant Numbers: FPU16/01451 and FPU16/04043.In 1971, Prof. L. Chua theoretically introduced a new circuit element, which exhibited a different behavior from that displayed by any of the three known passive elements: the resistor, the capacitor or the inductor. This element was called memristor, since its behavior corresponded to a resistor with memory. Four decades later, the concept of mem-elements was extended to the other two circuit elements by the definition of the constitutive equations of both memcapacitors and meminductors. Since then, the non-linear and non-volatile properties of these devices have attracted the interest of many researches trying to develop a wide range of applications. However, the lack of solid-state implementations of memcapacitors and meminductors make it necessary to rely on circuit emulators for the use and investigation of these elements in practical implementations. On this basis, this review gathers the current main alternatives presented in the literature for the emulation of both memcapacitors and meminductors. Different circuit emulators have been thoroughly analyzed and compared in detail, providing a wide range of approaches that could be considered for the implementation of these devices in future designs.Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT)
Japan Society for the Promotion of Science
Grants-in-Aid for Scientific Research (KAKENHI)
JP18k04275Spanish Ministry of Education, Culture, and Sport (MECD)
TEC2017-89955-P
FPU16/01451
FPU16/0404
Everything You Wish to Know About Memristors But Are Afraid to Ask
This paper classifies all memristors into three classes called Ideal, Generic, or Extended memristors. A subclass of Generic memristors is related to Ideal memristors via a one-to-one mathematical transformation, and is hence called Ideal Generic memristors. The concept of non-volatile memories is defined and clarified with illustrations. Several fundamental new concepts, including Continuum-memory memristor, POP (acronym for Power-Off Plot), DC V-I Plot, and Quasi DC V-I Plot, are rigorously defined and clarified with colorful illustrations. Among many colorful pictures the shoelace DC V-I Plot stands out as both stunning and illustrative. Even more impressive is that this bizarre shoelace plot has an exact analytical representation via 2 explicit functions of the state variable, derived by a novel parametric approach invented by the author
Assessment and Improvement of the Pattern Recognition Performance of Memdiode-Based Cross-Point Arrays with Randomly Distributed Stuck-at-Faults
In this work, the effect of randomly distributed stuck-at faults (SAFs) in memristive crosspoint array (CPA)-based single and multi-layer perceptrons (SLPs and MLPs, respectively) intended for pattern recognition tasks is investigated by means of realistic SPICE simulations. The quasi-static memdiode model (QMM) is considered here for the modelling of the synaptic weights implemented with memristors. Following the standard memristive approach, the QMM comprises two coupled equations, one for the electron transport based on the double-diode equation with a single series resistance and a second equation for the internal memory state of the device based on the so-called logistic hysteron. By modifying the state parameter in the current-voltage characteristic, SAFs of different severeness are simulated and the final outcome is analysed. Supervised ex-situ training and two well-known image datasets involving hand-written digits and human faces are employed to assess the inference accuracy of the SLP as a function of the faulty device ratio. The roles played by the memristor’s electrical parameters, line resistance, mapping strategy, image pixelation, and fault type (stuck-at-ON or stuck-at-OFF) on the CPA performance are statistically analysed following a Monte-Carlo approach. Three different re-mapping schemes to help mitigate the effect of the SAFs in the SLP inference phase are thoroughly investigated.In this work, the effect of randomly distributed stuck-at faults (SAFs) in memristive cross-point array (CPA)-based single and multi-layer perceptrons (SLPs and MLPs, respectively) intended for pattern recognition tasks is investigated by means of realistic SPICE simulations. The quasi-static memdiode model (QMM) is considered here for the modelling of the synaptic weights implemented with memristors. Following the standard memristive approach, the QMM comprises two coupled equations, one for the electron transport based on the double-diode equation with a single series resistance and a second equation for the internal memory state of the device based on the so-called logistic hysteron. By modifying the state parameter in the current-voltage characteristic, SAFs of different severeness are simulated and the final outcome is analysed. Supervised ex-situ training and two well-known image datasets involving hand-written digits and human faces are employed to assess the inference accuracy of the SLP as a function of the faulty device ratio. The roles played by the memristor?s electrical parameters, line resistance, mapping strategy, image pixelation, and fault type (stuck-at-ON or stuck-at-OFF) on the CPA performance are statistically analysed following a Monte-Carlo approach. Three different re-mapping schemes to help mitigate the effect of the SAFs in the SLP inference phase are thoroughly investigated.Fil: Aguirre, Fernando Leonel. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Universitat Autònoma de Barcelona; España. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pazos, Sebastián Matías. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Palumbo, Félix Roberto Mario. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Morell, Antoni. Universitat Autònoma de Barcelona; EspañaFil: Suñé, Jordi. Universitat Autònoma de Barcelona; EspañaFil: Miranda, Enrique. Universitat Autònoma de Barcelona; Españ
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