Exponential and fixed‐time stabilization of memristive neural networks with mixed delays
Sign Up to like & getrecommendations! Published in 2021 at "Mathematical Methods in the Applied Sciences"
DOI: 10.1002/mma.7260
Abstract: In this paper, we study a class of memristive neural networks with mixed delays. The existence of its equilibrium point is proved without the boundedness and initial value of the activation function, and a criterion… read more here.
Keywords: neural networks; mixed delays; networks mixed; memristive neural ... See more keywords
Exponential Stability and Sampled-Data Synchronization of Delayed Complex-Valued Memristive Neural Networks
Sign Up to like & getrecommendations! Published in 2019 at "Neural Processing Letters"
DOI: 10.1007/s11063-019-10082-0
Abstract: This paper is devoted to the global exponential stability (GES) and synchronization control of delayed complex-valued memristive neural networks (CVMNNs). The criterion on the existence, uniqueness and GES of the equilibrium point (EP) for delayed… read more here.
Keywords: neural networks; valued memristive; memristive neural; complex valued ... See more keywords
H∞ state estimation for memristive neural networks with multiple fading measurements
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.11.033
Abstract: The attention of this paper is mainly concentrated on the H ∞ state estimator's design problem for a kind of discrete-time memristive neural networks (MNNs) with multiple fading measurements. The phenomenon of multiple fading measurements… read more here.
Keywords: neural networks; memristive neural; multiple fading; state estimation ... See more keywords
Mixed H2/H∞ stabilization design for memristive neural networks
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DOI: 10.1016/j.neucom.2019.07.002
Abstract: Abstract This study considers the multiobjective stabilization design problem for memristive neural networks (MNNs). Initially, by using a set of logical switched functions, the original MNN is transformed into another model which is easy to… read more here.
Keywords: mixed stabilization; neural networks; memristive neural; stabilization design ... See more keywords
Synchronization of delayed memristive neural networks by establishing novel Lyapunov functional
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.08.060
Abstract: Abstract This paper inquires into the synchronization for delayed chaotic memristive neural networks. First, a novel criterion is proposed to determine whether a quadratic function is negative or not on a closed interval without regard… read more here.
Keywords: synchronization delayed; neural networks; novel lyapunov; memristive neural ... See more keywords
Synchronization of coupled memristive neural networks with actuator saturation and switching topology
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.11.034
Abstract: Abstract This study inspects the synchronization problem for a class of coupled memristive neural networks against parameter uncertainties, actuator saturation and switching topology, where the saturation effect is incorporated in the control design. The main… read more here.
Keywords: neural networks; memristive neural; coupled memristive; topology ... See more keywords
Intrinsic variation effect in memristive neural network with weight quantization
Sign Up to like & getrecommendations! Published in 2022 at "Nanotechnology"
DOI: 10.1088/1361-6528/ac7651
Abstract: To analyze the effect of the intrinsic variations of the memristor device on the neuromorphic system, we fabricated 32 × 32 Al2O3/TiO x -based memristor crossbar array and implemented 3 bit multilevel conductance as weight… read more here.
Keywords: neural network; network; weight quantization; variation effect ... See more keywords
Loading-Aware Reliability Improvement of Ultra-Low Power Memristive Neural Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2021.3084867
Abstract: In this paper, a method for offline training of inverter-based memristive neural networks (IM-NNs), called ERIM, is presented. In this method, the output voltage of the inverter is modeled very accurately by considering the loading… read more here.
Keywords: neural networks; improvement ultra; aware reliability; reliability improvement ... See more keywords
Global Mittag-Leffler Stabilization of Fractional-Order Memristive Neural Networks.
Sign Up to like & getrecommendations! Published in 2017 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2015.2506738
Abstract: According to conventional memristive neural network theories, neurodynamic properties are powerful tools for solving many problems in the areas of brain-like associative learning, dynamic information storage or retrieval, etc. However, as have often been noted… read more here.
Keywords: order memristive; order; stabilization; neural networks ... See more keywords
Dissipativity Analysis for Stochastic Memristive Neural Networks With Time-Varying Delays: A Discrete-Time Case
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2016.2631624
Abstract: In this paper, the dissipativity problem of discrete-time memristive neural networks (DMNNs) with time-varying delays and stochastic perturbation is investigated. A class of logical switched functions are put forward to reflect the memristor-based switched property… read more here.
Keywords: discrete time; neural networks; varying delays; time varying ... See more keywords
Gain-Scheduled Finite-Time Synchronization for Reaction–Diffusion Memristive Neural Networks Subject to Inconsistent Markov Chains
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2020.3009081
Abstract: An innovative class of drive-response systems that are composed of Markovian reaction–diffusion memristive neural networks, where the drive and response systems follow inconsistent Markov chains, is proposed in this article. For this kind of nonlinear… read more here.
Keywords: finite time; reaction diffusion; neural networks; memristive neural ... See more keywords