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- ItemRound robin comparison on quantitative nanometer scale magnetic field measurements by magnetic force microscopy(Amsterdam : Elsevier B.V., 2020) Hu, X.; Dai, G.; Sievers, S.; Fernández-Scarioni, A.; Corte-León, H.; Puttock, R.; Barton, C.; Kazakova, O.; Ulvr, M.; Klapetek, P.; Havlíček, M.; Nečas, D.; Tang, Y.; Neu, V.; Schumacher, H.W.Magnetic force microscopy (MFM) can be considered as a standard tool for nano-scale investigation of magnetic domain structures by probing the local stray magnetic field landscape of the measured sample. However, this generally provides only qualitative data. To quantify the stray magnetic fields, the MFM system must be calibrated. To that end, a transfer function (TF) approach was proposed, that, unlike point probe models, fully considers the finite extent of the MFM tip. However, albeit being comprehensive, the TF approach is not yet well established, mainly due to the ambiguities concerning the input parameters and the measurement procedure. Additionally, the calibration process represents an ill-posed problem which requires a regularization that introduces further parameters. In this paper we propose a guideline for quantitative stray field measurements by standard MFM tools in ambient conditions. All steps of the measurement and calibration procedure are detailed, including reference sample and sample under test (SUT) measurements and the data analysis. The suitability of the reference sample used in the present work for calibrated measurements on a sub-micron scale is discussed. A specific regularization approach based on a Pseudo-Wiener Filter is applied and combined with criteria for the numerical determination of a unique regularization parameter. To demonstrate the robustness of such a defined approach, a round robin comparison of magnetic field measurements was conducted by four laboratories. The guideline, the reference sample and the results of the round robin are discussed.
- ItemDigital IIR filters design using differential evolution algorithm with a controllable probabilistic population size(San Francisco, CA : Public Library of Science (PLoS), 2012) Zhu, W.; Fang, J.-A.; Tang, Y.; Zhang, W.; Du, W.Design of a digital infinite-impulse-response (IIR) filter is the process of synthesizing and implementing a recursive filter network so that a set of prescribed excitations results a set of desired responses. However, the error surface of IIR filters is usually non-linear and multi-modal. In order to find the global minimum indeed, an improved differential evolution (DE) is proposed for digital IIR filter design in this paper. The suggested algorithm is a kind of DE variants with a controllable probabilistic (CPDE) population size. It considers the convergence speed and the computational cost simultaneously by nonperiodic partial increasing or declining individuals according to fitness diversities. In addition, we discuss as well some important aspects for IIR filter design, such as the cost function value, the influence of (noise) perturbations, the convergence rate and successful percentage, the parameter measurement, etc. As to the simulation result, it shows that the presented algorithm is viable and comparable. Compared with six existing State-of-the-Art algorithms-based digital IIR filter design methods obtained by numerical experiments, CPDE is relatively more promising and competitive.
- ItemIdentifying controlling nodes in neuronal networks in different scales(San Francisco, CA : Public Library of Science (PLoS), 2012) Tang, Y.; Gao, H.; Zou, W.; Kurths, J.Recent studies have detected hubs in neuronal networks using degree, betweenness centrality, motif and synchronization and revealed the importance of hubs in their structural and functional roles. In addition, the analysis of complex networks in different scales are widely used in physics community. This can provide detailed insights into the intrinsic properties of networks. In this study, we focus on the identification of controlling regions in cortical networks of cats' brain in microscopic, mesoscopic and macroscopic scales, based on single-objective evolutionary computation methods. The problem is investigated by considering two measures of controllability separately. The impact of the number of driver nodes on controllability is revealed and the properties of controlling nodes are shown in a statistical way. Our results show that the statistical properties of the controlling nodes display a concave or convex shape with an increase of the allowed number of controlling nodes, revealing a transition in choosing driver nodes from the areas with a large degree to the areas with a low degree. Interestingly, the community Auditory in cats' brain, which has sparse connections with other communities, plays an important role in controlling the neuronal networks.
- ItemRestoration of rhythmicity in diffusively coupled dynamical networks(London : Nature Publishing Group, 2015) Zou, W.; Senthilkumar, D.V.; Nagao, R.; Kiss, I.Z.; Tang, Y.; Koseska, A.; Duan, J.; Kurths, J.
- ItemSynchronization in output-coupled temporal Boolean networks(London : Nature Publishing Group, 2014) Lu, J.; Zhong, J.; Tang, Y.; Huang, T.; Cao, J.; Kurths, J.This paper presents an analytical study of synchronization in an array of output-coupled temporal Boolean networks. A temporal Boolean network (TBN) is a logical dynamic system developed to model Boolean networks with regulatory delays. Both state delay and output delay are considered, and these two delays are assumed to be different. By referring to the algebraic representations of logical dynamics and using the semi-tensor product of matrices, the output-coupled TBNs are firstly converted into a discrete-time algebraic evolution system, and then the relationship between the states of coupled TBNs and the initial state sequence is obtained. Then, some necessary and sufficient conditions are derived for the synchronization of an array of TBNs with an arbitrary given initial state sequence. Two numerical examples including one epigenetic model are finally given to illustrate the obtained results.