A Compact CMOS Memristor Emulator Circuit and its Applications

Conceptual memristors have recently gathered wider interest due to their diverse application in non-von Neumann computing, machine learning, neuromorphic computing, and chaotic circuits. We introduce a compact CMOS circuit that emulates idealized memristor characteristics and can bridge the gap between concepts to chip-scale realization by transcending device challenges. The CMOS memristor circuit embodies a two-terminal variable resistor whose resistance is controlled by the voltage applied across its terminals. The memristor 'state' is held in a capacitor that controls the resistor value. This work presents the design and simulation of the memristor emulation circuit, and applies it to a memcomputing application of maze solving using analog parallelism. Furthermore, the memristor emulator circuit can be designed and fabricated using standard commercial CMOS technologies and opens doors to interesting applications in neuromorphic and machine learning circuits.Comment: Submitted to International Symposium of Circuits and Systems (ISCAS) 201

Experimental study of artificial neural networks using a digital memristor simulator

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a fully digital implementation of a memristor hardware simulator, as the core of an emulator, based on a behavioral model of voltage-controlled threshold-type bipolar memristors. Compared to other analog solutions, the proposed digital design is compact, easily reconfigurable, demonstrates very good matching with the mathematical model on which it is based, and complies with all the required features for memristor emulators. We validated its functionality using Altera Quartus II and ModelSim tools targeting low-cost yet powerful field programmable gate array (FPGA) families. We tested its suitability for complex memristive circuits as well as its synapse functioning in artificial neural networks (ANNs), implementing examples of associative memory and unsupervised learning of spatio-temporal correlations in parallel input streams using a simplified STDP. We provide the full circuit schematics of all our digital circuit designs and comment on the required hardware resources and their scaling trends, thus presenting a design framework for applications based on our hardware simulator.Peer ReviewedPostprint (author's final draft

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

Power Dissipation of Memristor-Based Relaxation Oscillators

Recently, many reactance-less memristive relaxation oscillators were introduced, where the charging and discharging processes depend on memristors. In this paper, we investigate the power dissipation in different memristor based relaxation oscillators. General expressions for these memristive circuits as well as the power dissipation formulas for three different topologies are derived analytically. In addition, general expressions for the maximum and minimum power dissipation are calculated. Finally, the calculated expressions are verified using PSPICE simulations showing very good matching

Memristor Platforms for Pattern Recognition Memristor Theory, Systems and Applications

In the last decade a large scientific community has focused on the study of the memristor. The memristor is thought to be by many the best alternative to CMOS technology, which is gradually showing its flaws. Transistor technology has developed fast both under a research and an industrial point of view, reducing the size of its elements to the nano-scale. It has been possible to generate more and more complex machinery and to communicate with that same machinery thanks to the development of programming languages based on combinations of boolean operands. Alas as shown by Moore’s law, the steep curve of implementation and of development of CMOS is gradually reaching a plateau. It is clear the need of studying new elements that can combine the efficiency of transistors and at the same time increase the complexity of the operations. Memristors can be described as non-linear resistors capable of maintaining memory of the resistance state that they reached. From their first theoretical treatment by Professor Leon O. Chua in 1971, different research groups have devoted their expertise in studying the both the fabrication and the implementation of this new promising technology. In the following thesis a complete study on memristors and memristive elements is presented. The road map that characterizes this study departs from a deep understanding of the physics that govern memristors, focusing on the HP model by Dr. Stanley Williams. Other devices such as phase change memories (PCMs) and memristive biosensors made with Si nano-wires have been studied, developing emulators and equivalent circuitry, in order to describe their complex dynamics. This part sets the first milestone of a pathway that passes trough more complex implementations such as neuromorphic systems and neural networks based on memristors proving their computing efficiency. Finally it will be presented a memristror-based technology, covered by patent, demonstrating its efficacy for clinical applications. The presented system has been designed for detecting and assessing automatically chronic wounds, a syndrome that affects roughly 2% of the world population, through a Cellular Automaton which analyzes and processes digital images of ulcers. Thanks to its precision in measuring the lesions the proposed solution promises not only to increase healing rates, but also to prevent the worsening of the wounds that usually lead to amputation and death

Memristores

Mestrado em Engenharia Eletrónica e TelecomunicaçõesThe memristor was proposed by Leon Chua in 1971 only for the sake of mathematical complement, an idea that was not widely accepted by the scientific community. Only decades later, after HP’s announcement in 2008 is that the memristors started to be seen as realizable elements and not as mere mathematical curiosities. These devices feature distinct characteristics from the other known electronic devices. Besides being passive, they are characterized by the following postulates: the existence of a characteristic voltage-current loop with hysteresis and single valued in the origin, gradual decrease of the area defined by the loop with the increasing of the frequency and simply resistive behaviour for infinite frequency. As a memristive device’s response depends greatly on the amplitude and frequency characteristics of the input signal and its own internal characteristics. Therefore there is a clear need to find procedures and attributes that allow to classify and categorize various memristive devices. These attributes, in their essence, similar to the figures of merit of devices like diodes and transistors, will allow in the near future to better choose memristive devices for specific applications. To try to obtain these attributes, a morphologic analysis of the voltage-current loops’ area and length of several theoretical memristive devices models was made in MATLAB changing its internal characteristics, for arrays of frequency and amplitude values of the input signal. Afterwards, a memristor device emulator was built to corroborate the theoretical results obtained. To this end the voltage-current loops for several input values were measured and the calculation of the loops’ areas and lengths was effectuated.O memristor foi proposto por Leon Chua em 1971 apenas por uma questão de complemento matemático, uma ideia que não teve grande aceitação na comunidade científica. Só décadas mais tarde, depois do anúncio da HP em 2008 é que os memristors começaram a ser vistos como elementos realizáveis e não como meras curiosidades matemáticas. Estes dispositivos apresentam características distintas dos demais dispositivos eletrónicos conhecidos. Além de serem elementos passivos, são caracterizados pelos seguintes postulados: existência de uma curva característica tensão-corrente com histerese e valor único na origem, diminuição gradual da área definida por esta curva com o aumento da frequência e comportamento puramente resistivo do memristor quando a frequência tende para infinito. A resposta dos dispositivos memristivos depende bastante das características de amplitude e frequência do sinal de entrada e das suas próprias características internas. Por isso, há uma clara necessidade de descobrir procedimentos e atributos que permitam classificar e categorizar diferentes dispositivos memristivos. Estes atributos, na sua essência, semelhantes às figuras de mérito de dispositivos como díodos ou transístores, permitirão num futuro próximo selecionar dispositivos memristivos para aplicações específicas. Para tentar obter estes atributos, realizou-se uma análise morfológica da área e comprimento das curvas tensão-corrente de vários modelos teóricos de dispositivos memristivos em MATLAB variando as suas características internas, para conjuntos de valores de frequência e amplitude do sinal de entrada. De seguida construiu-se um emulador de um dispositivo memristivo para corroborar os resultados teóricos obtidos. Para tal mediram-se as curvas de tensão-corrente para vários valores de entrada e efetuou-se o cálculo das áreas e comprimentos dessas curvas

MOCAST 2021

The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications

CMOS Realization of All-Positive Pinched Hysteresis Loops

Two novel nonlinear circuits that exhibit an all-positive pinched hysteresis loop are proposed. These circuits employ two NMOS transistors, one of which operates in its triode region, in addition to two first-order filter sections. We show the equivalency to a charge-controlled resistance (memristance) in a decremental state via detailed analysis. Simulation and experimental results verify the proposed theory

Memristors : a journey from material engineering to beyond Von-Neumann computing

Memristors are a promising building block to the next generation of computing systems. Since 2008, when the physical implementation of a memristor was first postulated, the scientific community has shown a growing interest in this emerging technology. Thus, many other memristive devices have been studied, exploring a large variety of materials and properties. Furthermore, in order to support the design of prac-tical applications, models in different abstract levels have been developed. In fact, a substantial effort has been devoted to the development of memristive based applications, which includes high-density nonvolatile memories, digital and analog circuits, as well as bio-inspired computing. In this context, this paper presents a survey, in hopes of summarizing the highlights of the literature in the last decade