Journal ArticleDOI
Dynamic behaviors of memristor-based recurrent neural networks with time-varying delays
Ailong Wu,Zhigang Zeng +1 more
TLDR
A general class of memristor-based recurrent neural networks with time-varying delays with exponential convergence and conditions on the nondivergence and global attractivity are established by using local inhibition.About:
This article is published in Neural Networks.The article was published on 2012-12-01. It has received 177 citations till now. The article focuses on the topics: Recurrent neural network & Memristor.read more
Citations
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Journal ArticleDOI
Finite-Time Synchronization of Coupled Memrisive Neural Network via Robust Control
Hui Zhao,Mingwen Zheng +1 more
TL;DR: This paper proposes that CMNN is transformed into a class of neural networks with interval parameters under the framework of Filippov solution and overcame the problem of mismatched parameters and be less conservative than those existing methods.
Dissertation
Processing hidden Markov models using recurrent neural networks for biological applications
TL;DR: Rallabandi et al. as discussed by the authors presented a novel hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov Models (HMMs).
Journal ArticleDOI
Fixed-TimeAdaptive Neural Control for Strict Feedback Nonlinear Systems via Event-Triggered Mechanism
TL;DR: This article investigates an event-trigger-based fixed-time adaptive tracking control problem for strict feedback nonlinear systems with external disturbances and introduces a relative fixed event-triggered control scheme to save communication resources.
Book ChapterDOI
Memristor Theory and Concepts
TL;DR: In this chapter, the fundamental concepts and the theoretical background of memristor are briefly illustrated to provide a background for the Memristor models and emulator circuits to be presented in this book.
Book ChapterDOI
Towards a Model for Self-Disclosure on Social Network Sites
TL;DR: In this article , the authors have used the partial least squares structural equation modeling technique for the analysis of the relationships postulated to explain self-disclosure in social network sites, and the preliminary findings revealed that the derived model explains 32.9% of the user's selfdisclosure intention on social networks.
References
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Journal ArticleDOI
The missing memristor found
TL;DR: It is shown, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage.
Journal ArticleDOI
Memristor-The missing circuit element
TL;DR: In this article, the memristor is introduced as the fourth basic circuit element and an electromagnetic field interpretation of this relationship in terms of a quasi-static expansion of Maxwell's equations is presented.
Book
Differential Equations with Discontinuous Righthand Sides
TL;DR: The kind and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in regional and theoretical economics, algebraic geometry interacts with physics, and such new emerging subdisciplines as "experimental mathematics", "CFD", "completely integrable systems", "chaos, synergetics and large-scale order", which are almost impossible to fit into the existing classification schemes.
Journal ArticleDOI
Circuit Elements With Memory: Memristors, Memcapacitors, and Meminductors
TL;DR: It is argued that capacitive and inductive elements, namely, capacitors and inductors whose properties depend on the state and history of the system, are common at the nanoscale, where the dynamical properties of electrons and ions are likely to depend upon the history ofThe system, at least within certain time scales.
Journal ArticleDOI
Experimental demonstration of associative memory with memristive neural networks
TL;DR: This work has demonstrated experimentally the formation of associative memory in a simple neural network consisting of three electronic neurons connected by two memristor-emulator synapses and opens up new possibilities in the understanding of neural processes using memory devices.