300 research outputs found

    Low Barrier Nanomagnet Design for Binary Stochastic Neurons: Design Challenges for Real Nanomagnets with Fabrication Defects

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    Much attention has been focused on the design of low barrier nanomagnets (LBM), whose magnetizations vary randomly in time owing to thermal noise, for use in binary stochastic neurons (BSN) which are hardware accelerators for machine learning. The performance of BSNs depend on two important parameters: the correlation time associated with the random magnetization dynamics in a LBM, and the spin-polarized pinning current which stabilizes the magnetization of a LBM in a chosen direction within a chosen time. Here, we show that common fabrication defects in LBMs make these two parameters unpredictable since they are strongly sensitive to the defects. That makes the design of BSNs with real LBMs very challenging. Unless the LBMs are fabricated with extremely tight control, the BSNs which use them could be unreliable or suffer from poor yield.Comment: Accepted for publication in IEEE Magnetics Letter

    IEEE Access Special Section Editorial: Recent Advances on Hybrid Complex Networks: Analysis and Control

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    Complex networks typically involve multiple disciplines due to network dynamics and their statistical nature. When modeling practical networks, both impulsive effects and logical dynamics have recently attracted increasing attention. Hence, it is of interest and importance to consider hybrid complex networks with impulsive effects and logical dynamics. Relevant research is prevalent in cells, ecology, social systems, and communication engineering. In hybrid complex networks, numerous nodes are coupled through networks and their properties usually lead to complex dynamic behaviors, including discrete and continuous dynamics with finite values of time and state space. Generally, continuous and discrete sections of the systems are described by differential and difference equations, respectively. Logical networks are used to model the systems where time and state space take finite values. Although interesting results have been reported regarding hybrid complex networks, the analysis methods and relevant results could be further improved with respect to conservative impulsive delay inequalities and reproducibility of corresponding stability or synchronization criteria. Therefore, it is necessary to devise effective approaches to improve the analysis method and results dealing with hybrid complex networks

    Towards a new methodology for design, modelling, and verification of reconfigurable distributed control systems based on a new extension to the IEC 61499 standard

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    In order to meet user requirements and system environment changes, reconfigurable control systems must dynamically adapt their structure and behaviour without disrupting system operation. IEC 61499 standard provides limited support for the design and verification of such systems. In fact, handling different reconfiguration scenarios at runtime is difficult since function blocks in IEC 61499 cannot be changed at run-time. Hence, this thesis promotes an IEC 61499 extension called reconfigurable function block (RFB) that increases design readability and smoothly switches to the most appropriate behaviour when a reconfiguration event occurs. To ensure system feasibility after reconfiguration, in addition to the qualitative verification, quantitative verification based on probabilistic model checking is addressed in a new RFBA approach. The latter aims to transform the designed RFB model automatically into a generalised reconfigurable timed net condition/event system model (GRTNCES) using a newly developed environment called RFBTool. The GR-TNCES fits well with RFB and preserves its semantic. Using the probabilistic model checker PRISM, the generated GR-TNCES model is checked using defined properties specified in computation tree logic. As a result, an evaluation of system performance and an estimation of reconfiguration risks are obtained. The RFBA methodology is applied on a distributed power system case study.Dynamische Anforderungen und Umgebungen erfordern rekonfigurierbare Anlagen und Steuerungssysteme. Rekonfiguration ermöglicht es einem System, seine Struktur und sein Verhalten an interne oder externe Änderungen anzupassen. Die Norm IEC 61499 wurde entwickelt, um (verteilte) Steuerungssysteme auf Basis von Funktionsbausteinen zu entwickeln. Sie bietet jedoch wenig Unterstützung für Entwurf und Verifikation. Die Tatsache, dass eine Rekonfiguration das System-Ausführungsmodell verändert, erschwert die Entwicklung in IEC 61499 zusätzlich. Daher schlägt diese Dissertation rekonfigurierbare Funktionsbausteine (RFBs) als Erweiterung der Norm vor. Ein RFB verarbeitet über einen Master-Slave-Automaten Rekonfigurationsereignisse und löst das entsprechende Verhalten aus. Diese Hierarchie trennt das Rekonfigurationsmodell vom Steuerungsmodell und vereinfacht so den Entwurf. Die Funktionalität des Entwurfs muss verifiziert werden, damit die Ausführbarkeit des Systems nach einer Rekonfiguration gewährleistet ist. Hierzu wird das entworfene RFB-Modell automatisch in ein generalised reconfigurable timed net condition/event system übersetzt. Dieses wird mit dem Model-Checker PRISM auf qualitative und quantitative Eigenschaften überprüft. Somit wird eine Bewertung der Systemperformanz und eine Einschätzung der Rekonfigurationsrisiken erreicht. Die RFB-Methodik wurde in einem Softwarewerkzeug umgesetzt und in einer Fallstudie auf ein dezentrales Stromnetz angewendet

    Data based identification and prediction of nonlinear and complex dynamical systems

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    We thank Dr. R. Yang (formerly at ASU), Dr. R.-Q. Su (formerly at ASU), and Mr. Zhesi Shen for their contributions to a number of original papers on which this Review is partly based. This work was supported by ARO under Grant No. W911NF-14-1-0504. W.-X. Wang was also supported by NSFC under Grants No. 61573064 and No. 61074116, as well as by the Fundamental Research Funds for the Central Universities, Beijing Nova Programme.Peer reviewedPostprin
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