The Experts below are selected from a list of 5187 Experts worldwide ranked by ideXlab platform
Leon O. Chua - One of the best experts on this subject based on the ideXlab platform.
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analog self timed programming circuits for aging Memristors
IEEE Transactions on Circuits and Systems Ii-express Briefs, 2021Co-Authors: Aidana Irmanova, Akshay Kumar Maan, Alex Pappachen James, Leon O. ChuaAbstract:Reliable programming crossbar Memristors to the required resistive states is the challenge that hinders VLSI deployment of the memristive neural network circuits, as current memristive devices face the variability issues of resistive switching. There is also a need for on-chip control circuitry that detects malfunctioning memristive nodes in the crossbar due to the memristor aging. Program and Verify ( $P\&V$ ) schemes can be used for both controlling resistive switching as well as evaluating the functionality of Memristors. In this brief, we propose a novel analog circuit design for the $P\&V$ approach of row-by-row programming bipolar Memristors in a 1T1M crossbar configuration. The proposed control circuit (CC) is self-timed and performs both read and program operations, decreasing the overall programming complexity. CC design is verified with Spice simulations using low power 22nm high-k CMOS models and Modified S memristor model for large scale simulations. Parasitic of wire lines under thermal variation and CMOS variability were included for programming 1T1M crossbar partitions of the sizes $16\times 16$ , $32\times 32$ , $64\times 64$ , $128\times 128$ .
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everything you wish to know about Memristors but are afraid to ask
Radioengineering, 2015Co-Authors: Leon O. ChuaAbstract: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.
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Memory elements in the electrical network of Mimosa pudica L.
Plant Signaling & Behavior, 2014Co-Authors: Alexander G Volkov, Jada Reedus, Colee M. Mitchell, Clayton Tuckett, Maya I Volkova, Vladislav S Markin, Leon O. ChuaAbstract: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.
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Memristors in the electrical network of aloe vera l
Plant Signaling & Behavior, 2014Co-Authors: Alexander G Volkov, Jada Reedus, Colee M. Mitchell, Maya I Volkova, Vladislav S Markin, Clayton Tucket, Victoria Fordetuckett, Leon O. ChuaAbstract:A memristor is a resistor with memory, which is a non-linear passive two-terminal electrical element relating magnetic flux linkage and electrical charge. Here we found that Memristors exist in vivo. The electrostimulation of the Aloe vera 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 periodic sinusoidal or triangle electrostimulating waves. Memristive behavior of an electrical network in the Aloe vera is linked to the properties of voltage gated ion channels: the K+ 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.
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Memristor Networks
2014Co-Authors: Andrew Adamatzky, Leon O. ChuaAbstract: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.
Xiao-ping Wang - One of the best experts on this subject based on the ideXlab platform.
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memristor based circuit design for multilayer neural networks
IEEE Transactions on Circuits and Systems I-regular Papers, 2018Co-Authors: Yang Zhang, Xiao-ping WangAbstract: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.
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a new crossbar architecture based on two serial Memristors with threshold
International Joint Conference on Neural Network, 2015Co-Authors: Xiao-ping Wang, Min Chen, Yi ShenAbstract:This paper presents a memory crossbar based on two serial Memristors with threshold characteristic to eliminate the effect of sneak paths, which is a key issue in crossbar memory system leading to great degradation in their performance and power efficiency. At first, we analyze the threshold characteristic of memristor and propose a memristor model with threshold. Based on this model, the paper presents the design and simulation of a non-volatile memory system utilizing two serial Memristors with different polarities as a memory cell. This scheme solves the sneak-path problem by taking advantage of the threshold characteristic and the performance with having always high resistance state in all the memory cells, which is validated by simulation results. The scheme also possesses the superior properties of remarkable compatibility and high density.
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a novel design for memristor based logic switch and crossbar circuits
IEEE Transactions on Circuits and Systems, 2015Co-Authors: Yang Zhang, Xiao-ping Wang, Yi Shen, Lina CaoAbstract:Recently, it has been demonstrated that Memristors can be utilized as logic gates, control switches as well as memory elements. In this paper, we analyze the different AND, OR, and NOT logic gates which are based on Memristors. In addition, a novel design for a memristor-based switch is presented, which can be used in the peripheral read/write circuits of the memristor-based memory. Moreover, methods of consecutive read with long refresh intervals and fast write for the proposed design are also discussed. Another highlight of this work is the analysis of the proposed memristor-based crossbar architecture which has a series of excellent features, such as good-compatibility, high-density, non-volatility, low-power, and good-scalability. Simulation results also show that the proposed memory array has superior performances compared to other memristor-based arrays proposed in the existing technical literature.
Zhigang Zeng - One of the best experts on this subject based on the ideXlab platform.
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general memristor with applications in multilayer neural networks
Neural Networks, 2018Co-Authors: Zheng Yan, Shiping Wen, Tingwen Huang, Xudong Xie, Zhigang ZengAbstract:Abstract Memristor describes the relationship between charge and flux. Although several window functions for Memristors based on the HP linear and nonlinear dopant drift models have been studied, most of them are inadequate to capture the full characteristics of Memristors. To address this issue, this paper proposes a unified window function to describe a general memristor with restrictions of its parameters given. Compared with other window functions, the proposed function demonstrates high validity and accuracy. In order to make the simulation results have high consistency with the results of actual circuit, we apply the new window function to the simulation of a memristor-based multilayer neural network (MNN) circuit. The overall accuracy will vary with the change of control parameters in the window function. It implies that the proposed model can guide the design of actual memristor-based circuits.
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multistability of periodic delayed recurrent neural network with Memristors
Neural Computing and Applications, 2013Co-Authors: Zhigang ZengAbstract:This paper discusses the recurrent neural network (RNN) with Memristors as connection weights. Memristor is a nonlinear resistor. Memristance varies periodically with time when the sinusoidal voltage source is applied. According to this property of memristor, it shows that coefficients of RNN with Memristors are periodic functions with respect to time t. By dividing the state space and using contraction mapping theorem, one sufficient condition is obtained for multiperiodicity. And the periodic orbits located in saturation regions are locally exponentially stable limit cycles. At last, one example is given for verifying the validity of our result.
Yang Zhang - One of the best experts on this subject based on the ideXlab platform.
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memristor based circuit design for multilayer neural networks
IEEE Transactions on Circuits and Systems I-regular Papers, 2018Co-Authors: Yang Zhang, Xiao-ping WangAbstract: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.
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a novel design for memristor based logic switch and crossbar circuits
IEEE Transactions on Circuits and Systems, 2015Co-Authors: Yang Zhang, Xiao-ping Wang, Yi Shen, Lina CaoAbstract:Recently, it has been demonstrated that Memristors can be utilized as logic gates, control switches as well as memory elements. In this paper, we analyze the different AND, OR, and NOT logic gates which are based on Memristors. In addition, a novel design for a memristor-based switch is presented, which can be used in the peripheral read/write circuits of the memristor-based memory. Moreover, methods of consecutive read with long refresh intervals and fast write for the proposed design are also discussed. Another highlight of this work is the analysis of the proposed memristor-based crossbar architecture which has a series of excellent features, such as good-compatibility, high-density, non-volatility, low-power, and good-scalability. Simulation results also show that the proposed memory array has superior performances compared to other memristor-based arrays proposed in the existing technical literature.
Shiping Wen - One of the best experts on this subject based on the ideXlab platform.
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general memristor with applications in multilayer neural networks
Neural Networks, 2018Co-Authors: Zheng Yan, Shiping Wen, Tingwen Huang, Xudong Xie, Zhigang ZengAbstract:Abstract Memristor describes the relationship between charge and flux. Although several window functions for Memristors based on the HP linear and nonlinear dopant drift models have been studied, most of them are inadequate to capture the full characteristics of Memristors. To address this issue, this paper proposes a unified window function to describe a general memristor with restrictions of its parameters given. Compared with other window functions, the proposed function demonstrates high validity and accuracy. In order to make the simulation results have high consistency with the results of actual circuit, we apply the new window function to the simulation of a memristor-based multilayer neural network (MNN) circuit. The overall accuracy will vary with the change of control parameters in the window function. It implies that the proposed model can guide the design of actual memristor-based circuits.