Research

12 pages, 3658 KiB

Open AccessArticle

Beyond Memristors: Neuromorphic Computing Using Meminductors

by Frank Zhigang Wang

Micromachines 2023, 14(2), 486; https://0-doi-org.brum.beds.ac.uk/10.3390/mi14020486 - 19 Feb 2023

Cited by 1 | Viewed by 8580

Resistors with memory (memristors), inductors with memory (meminductors) and capacitors with memory (memcapacitors) play different roles in novel computing architectures. We found that a coil with a magnetic core is an inductor with memory (meminductor) in terms of its inductance L(q [...] Read more.

Resistors with memory (memristors), inductors with memory (meminductors) and capacitors with memory (memcapacitors) play different roles in novel computing architectures. We found that a coil with a magnetic core is an inductor with memory (meminductor) in terms of its inductance L(q) being a function of charge q. The history of the current passing through the coil is remembered by the magnetization inside the magnetic core. Such a meminductor can play a unique role (that cannot be played by a memristor) in neuromorphic computing, deep learning and brain-inspired computers since the time constant (

t_{0} = \sqrt{L C}

) of a neuromorphic RLC circuit is jointly determined by the inductance

L

and capacitance

C

, rather than the resistance

R

. As an experimental verification, this newly invented meminductor was used to reproduce the observed biological behavior of amoebae (the memorizing, timing and anticipating mechanisms). In conclusion, a beyond-memristor computing paradigm is theoretically sensible and experimentally practical. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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15 pages, 3512 KiB

Open AccessArticle

RC Bridge Oscillation Memristor Chaotic Circuit for Electrical and Electronic Technology Extended Simulation Experiment

by Gang Dou, Yongcheng Zhang, Hai Yang, Mingqiao Han, Mei Guo and Wendong Gai

Micromachines 2023, 14(2), 410; https://0-doi-org.brum.beds.ac.uk/10.3390/mi14020410 - 09 Feb 2023

Cited by 5 | Viewed by 1658

Abstract

The fourth basic circuit component, the memristor, has been proposed for a long time, but it is not mentioned in the experiment teaching system of Electrical and Electronic Technology. In this paper, an RC bridge oscillation chaotic circuit based on memristor is designed [...] Read more.

The fourth basic circuit component, the memristor, has been proposed for a long time, but it is not mentioned in the experiment teaching system of Electrical and Electronic Technology. In this paper, an RC bridge oscillation chaotic circuit based on memristor is designed to solve this problem. The dynamical behavior of the circuit system is analyzed using Lyapunov exponents spectrum, bifurcation diagram, phase portrait and Poincaré map. A series of complex dynamical behaviors such as symmetric single-scroll coexistence, asymmetrical single-scroll coexistence, symmetric double-scroll coexistence and asymmetrical limit–cycle coexistence exist in the circuit system. This research plays a critical role in enriching students’ knowledge and improving the experiment teaching system of Electrical and Electronic Technology. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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11 pages, 2113 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Novel Memristive Neural Network Circuit and Its Application in Character Recognition

by Xinrui Zhang, Xiaoyuan Wang, Zhenyu Ge, Zhilong Li, Mingyang Wu and Shekharsuman Borah

Micromachines 2022, 13(12), 2074; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13122074 - 25 Nov 2022

Cited by 7 | Viewed by 1600

Abstract

The memristor-based neural network configuration is a promising approach to realizing artificial neural networks (ANNs) at the hardware level. The memristors can effectively simulate the strength of synaptic connections between neurons in neural networks due to their diverse significant characteristics such as nonvolatility, [...] Read more.

The memristor-based neural network configuration is a promising approach to realizing artificial neural networks (ANNs) at the hardware level. The memristors can effectively simulate the strength of synaptic connections between neurons in neural networks due to their diverse significant characteristics such as nonvolatility, nanoscale dimensions, and variable conductance. This work presents a new synaptic circuit based on memristors and Complementary Metal Oxide Semiconductor(CMOS), which can realize the adjustment of positive, negative, and zero synaptic weights using only one control signal. The relationship between synaptic weights and the duration of control signals is also explained in detail. Accordingly, Widrow–Hoff algorithm-based memristive neural network (MNN) circuits are proposed to solve the recognition of three types of character pictures. The functionality of the proposed configurations is verified using SPICE simulation. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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14 pages, 2357 KiB

Open AccessArticle

Reservoir Computing-Based Design of ZnO Memristor-Type Digital Identification Circuits

by Lixun Wang, Yuejun Zhang, Zhecheng Guo, Zhixin Wu, Xinhui Chen and Shimin Du

Micromachines 2022, 13(10), 1700; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13101700 - 10 Oct 2022

Cited by 1 | Viewed by 2247

Abstract

Reservoir Computing (RC) is a network architecture inspired by biological neural systems that maps time-dimensional input features to a high-dimensional space for computation. The key to hardware implementation of the RC system is whether sufficient reservoir states can be generated. In this paper, [...] Read more.

Reservoir Computing (RC) is a network architecture inspired by biological neural systems that maps time-dimensional input features to a high-dimensional space for computation. The key to hardware implementation of the RC system is whether sufficient reservoir states can be generated. In this paper, a laboratory-prepared zinc oxide (ZnO) memristor is reported and modeled. The device is found to have nonlinear dynamic responses and characteristics of simulating neurosynaptic long-term potentiation (LTP) and long-term depression (LTD). Based on this, a novel two-level RC structure based on the ZnO memristor is proposed. Novel synaptic encoding is used to maintain stress activity based on the characteristics of after-discharge and proneness to fatigue during synaptic transmission. This greatly alleviates the limitations of the self-attenuating characteristic reservoir of the duration and interval of the input signal. This makes the reservoir, in combination with a fully connected neural network, an ideal system for time series classification. The experimental results show that the recognition rate for the complete MNIST dataset is 95.08% when 35 neurons are present as hidden layers while achieving low training consumption. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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12 pages, 2987 KiB

Open AccessArticle

Investigation of the Temperature Effect on Electrical Characteristics of Al/SiO₂/n++-Si RRAM Devices

by Piotr Wiśniewski, Mateusz Nieborek, Andrzej Mazurak and Jakub Jasiński

Micromachines 2022, 13(10), 1641; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13101641 - 29 Sep 2022

Cited by 4 | Viewed by 1839

Abstract

In this work, we investigate the effect of temperature on the electrical characteristics of Al/SiO₂/n++-Si RRAM devices. We study the electroforming process and show that forming voltage and time-to-breakdown are well described by Weibull distribution. Experimental current–voltage characteristics of Al-SiO₂ [...] Read more.

In this work, we investigate the effect of temperature on the electrical characteristics of Al/SiO₂/n++-Si RRAM devices. We study the electroforming process and show that forming voltage and time-to-breakdown are well described by Weibull distribution. Experimental current–voltage characteristics of Al-SiO₂-(n++Si) structures are presented and discussed at different temperatures. We show that some intermediate resistance states can be observed at higher temperatures. In our analysis, we identify Space Charge Limited Conduction (SCLC) as the dominating transport mechanism regardless of the operating temperature. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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18 pages, 603 KiB

Open AccessArticle

Principle and Application of Frequency-Domain Characteristic Analysis of Fractional-Order Memristor

by Bo Yu, Yifei Pu, Qiuyan He and Xiao Yuan

Micromachines 2022, 13(9), 1512; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13091512 - 12 Sep 2022

Viewed by 1241

Abstract

Scaling fractional-order memristor circuit is important for realizing a fractional-order memristor. However, the effective operating-frequency range, operation order, and fractional-order memristance of the scaling fractional-order memristor circuit have not been studied thoroughly; that is, the fractional-order memristance in the effective operating-frequency range has [...] Read more.

Scaling fractional-order memristor circuit is important for realizing a fractional-order memristor. However, the effective operating-frequency range, operation order, and fractional-order memristance of the scaling fractional-order memristor circuit have not been studied thoroughly; that is, the fractional-order memristance in the effective operating-frequency range has not been calculated quantitatively. The fractional-order memristance is a similar and equally important concept as memristance, memcapacitance, and meminductance. In this paper, the frequency-domain characteristic-analysis principle of the fractional-order memristor is proposed based on the order- and F-frequency characteristic functions. The reasons for selecting the order- and F-frequency characteristic functions are explained. Subsequently, the correctness of the frequency-domain characteristic analysis using the order- and F-frequency characteristic functions is verified from multiple perspectives. Finally, the principle of the frequency-domain characteristic analysis is applied to the recently realized chain-scaling fractional-order memristor circuit. The results of this study indicate that the principle of the frequency-domain characteristic analysis of the fractional-order memristor can successfully calculate the fractional-order memristance of the chain-scaling fractional-order memristor circuit. The proposed principle of frequency-domain characteristic analysis can also be applied to mem-elements, such as memristors, memcapacitors, and meminductors. The main contribution of this study is the principle of the frequency-domain characteristic analysis of the fractional-order memristor based on the order- and F-frequency characteristic functions. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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20 pages, 5995 KiB

Open AccessArticle

Generation of Multi-Lobe Chua Corsage Memristor and Its Neural Oscillation

by Yue Liu, Hui Li, Shu-Xu Guo and Herbert Ho-Ching Iu

Micromachines 2022, 13(8), 1330; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13081330 - 17 Aug 2022

Cited by 3 | Viewed by 1279

Abstract

The Chua corsage memristor (CCM) is considered as one of the candidates for the realization of biological neuron models due to its rich neuromorphic behaviors. In this paper, a universal model for m-lobe CCM memristor is proposed. Moreover, a novel small-signal equivalent [...] Read more.

The Chua corsage memristor (CCM) is considered as one of the candidates for the realization of biological neuron models due to its rich neuromorphic behaviors. In this paper, a universal model for m-lobe CCM memristor is proposed. Moreover, a novel small-signal equivalent circuit with one capacitor is derived based on the proposed model to determine the edge of chaos and obtain the zero-pole diagrams and analyze the frequency response and oscillation mechanism of the m-lobe CCM system, which are discussed in detail. In view of existence of the edge of chaos, the frequency response and the oscillation mechanism of the simplest oscillator is analysed using the proposed model. Finally, the proposed model has exhibited some essential neural oscillation, including the stable limit cycle, supercritical Hopf bifurcation, spiking and bursting oscillation. This study also reveals a previously undiscovered behavior of bursting oscillation in a CCM system. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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18 pages, 1077 KiB

Open AccessArticle

Memristive Cluster Based Compact High-Density Nonvolatile Memory Design and Application for Image Storage

by Jingru Sun, Meiqi Jiang, Qi Zhou, Chunhua Wang and Yichuang Sun

Micromachines 2022, 13(6), 844; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13060844 - 28 May 2022

Cited by 5 | Viewed by 1681

Abstract

As a new type of nonvolatile device, the memristor has become one of the most promising technologies for designing a new generation of high-density memory. In this paper, a 4-bit high-density nonvolatile memory based on a memristor is designed and applied to image [...] Read more.

As a new type of nonvolatile device, the memristor has become one of the most promising technologies for designing a new generation of high-density memory. In this paper, a 4-bit high-density nonvolatile memory based on a memristor is designed and applied to image storage. Firstly, a memristor cluster structure consisting of a transistor and four memristors is designed. Furthermore, the memristor cluster is used as a memory cell in the crossbar array structure to realize the memory design. In addition, when the designed non-volatile memory is applied to gray scale image storage, only two memory cells are needed for the storage of one pixel. Through the Pspice circuit simulation, the results show that compared with the state-of-the-art technology, the memory designed in this paper has better storage density and read–write speed. When it is applied to image storage, it achieves the effect of no distortion and fast storage. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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11 pages, 3103 KiB

Open AccessFeature PaperArticle

Design of the Threshold-Controllable Memristor Emulator Based on NDR Characteristics

by Mi Lin, Wenyao Luo, Luping Li, Qi Han and Weifeng Lyu

Micromachines 2022, 13(6), 829; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13060829 - 26 May 2022

Viewed by 1889

Abstract

Due to the high manufacturing cost of memristors, an equivalent emulator has been employed as one of the mainstream approaches of memristor research. A threshold-type memristor emulator based on negative differential resistance (NDR) characteristics is proposed, with the core part being the R-HBT [...] Read more.

Due to the high manufacturing cost of memristors, an equivalent emulator has been employed as one of the mainstream approaches of memristor research. A threshold-type memristor emulator based on negative differential resistance (NDR) characteristics is proposed, with the core part being the R-HBT network composed of transistors. The advantage of the NDR-based memristor emulator is the controllable threshold, where the state of the memristor can be changed by setting the control voltage, which makes the memristor circuit design more flexible. The operation frequency of the memristor emulator is about 250 kHz. The experimental results prove the feasibility and correctness of the threshold-controllable memristor emulator circuit. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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17 pages, 601 KiB

Open AccessArticle

Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme

by Wei Yao, Fei Yu, Jin Zhang and Ling Zhou

Micromachines 2022, 13(5), 726; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13050726 - 30 Apr 2022

Cited by 6 | Viewed by 1354

Abstract

This paper investigates the asymptotic synchronization of memristive Cohen-Grossberg neural networks (MCGNNs) with time-varying delays under event-triggered control (ETC). First, based on the designed feedback controller, some ETC conditions are provided. It is demonstrated that ETC can significantly reduce the update times of [...] Read more.

This paper investigates the asymptotic synchronization of memristive Cohen-Grossberg neural networks (MCGNNs) with time-varying delays under event-triggered control (ETC). First, based on the designed feedback controller, some ETC conditions are provided. It is demonstrated that ETC can significantly reduce the update times of the controller and decrease the computing cost. Next, some sufficient conditions are derived to ensure the asymptotic synchronization of MCGNNs with time-varying delays under the ETC method. Finally, a numerical example is provided to verify the correctness and effectiveness of the obtained results. Full article

(This article belongs to the Special Issue Novel Computing Architectures and Digital Circuit Designs Using Memristors and Memristive Systems)

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