Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
Volume 8, Issue 1
Displaying 1-8 of 8 articles from this issue
Special Issue on Recent Progress in Nonlinear Theory and Its Applications
  • Guanrong Chen, Tetsushi Ueta
    Article type: FOREWORD
    2017 Volume 8 Issue 1 Pages 1
    Published: 2017
    Released on J-STAGE: January 01, 2017
    JOURNAL FREE ACCESS
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  • Yoshitaka Itoh, Yuta Tada, Masaharu Adachi
    Article type: Paper
    2017 Volume 8 Issue 1 Pages 2-14
    Published: 2017
    Released on J-STAGE: January 01, 2017
    JOURNAL FREE ACCESS
    We describe a method for reconstructing bifurcation diagrams with Lyapunov exponents for chaotic systems using only time-series data. The reconstruction of bifurcation diagrams is a problem of time-series prediction and predicts oscillatory patterns of time-series data when parameters change. Therefore, we expect the reconstruction of bifurcation diagram could be used for real-world systems that have variable environmental factors, such as temperature, pressure, and concentration. In the conventional method, the accuracy of the reconstruction can be evaluated only qualitatively. In this paper, we estimate Lyapunov exponents for reconstructed bifurcation diagrams so that we can quantitatively evaluate the reconstruction. We also present the results of numerical experiments that confirm that the features of the reconstructed bifurcation diagrams coincide with those of the original ones.
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  • Hisashi Kada, Kei Kondo, Shota Sumino, Isao T. Tokuda
    Article type: Paper
    2017 Volume 8 Issue 1 Pages 15-24
    Published: 2017
    Released on J-STAGE: January 01, 2017
    JOURNAL FREE ACCESS
    As an experimental analogy of synchronized hands clapping (Néda et al., 2000), sound-coupled electronic metronomes are introduced. Clicking sounds generated from the driving metronome serve as the sounds of hands clapping, whereas a microphone attached to the driven electronic metronome detects the clicking sounds. In contrast to popular experimental systems of synchronization, e.g., mechanical metronomes put on a same beam, which directly connects oscillators through a material medium, the present system utilizes sound as an indirect coupling medium. In cases of both unidirectional and bidirectional couplings, our experiments showed that the two electronic metronomes are synchronized in such a way that a slow metronome catches up with a fast one. Phase slips, which give rise to intermittent switching between synchronized and desynchronized rhythms, were also observed, resembling the hands clapping in a concert hall. Our mathematical model based on phase oscillators with positive interaction function elucidates the observed results very well. Our system may provide a basic experimental framework for studying synchronization in sound-coupled oscillators including the rhythmic applause.
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  • Takashi Kohno, Munehisa Sekikawa, Kazuyuki Aihara
    Article type: Paper
    2017 Volume 8 Issue 1 Pages 25-37
    Published: 2017
    Released on J-STAGE: January 01, 2017
    JOURNAL FREE ACCESS
    A silicon neuronal network is a neuro-mimetic system that aims to realize an electronic-circuit version of the nervous system by connecting silicon neuron circuits via silicon synapse circuits. In our previous works, we proposed a qualitative-modeling-based design approach that provides a solution to the trade off in the silicon neuron circuits between the power consumption and the variety of supported neuronal activities. By this approach, we developed an analog silicon neuron circuit that can be configured to Class I, Class II, regular spiking, elliptic bursting, and square-wave bursting modes with power consumption less than 72 nW. Simulation and experimental results for the first 4 modes are reported.
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  • Yuichi Tanji, Hiroto Kamei
    Article type: Paper
    2017 Volume 8 Issue 1 Pages 38-48
    Published: 2017
    Released on J-STAGE: January 01, 2017
    JOURNAL FREE ACCESS
    With the behavioral models of Class-E switching-mode circuits, we can simulate the steady state behaviors of original circuits efficiently. However, if the dynamical systems, which approximate the behaviors of the original circuits, include impulse modes, the behavioral models cannot be easily obtained. In this paper, we show that the behavioral models are given by using Weierstrass canonical form, even if impulse modes happen. Since the proposed method is quite general, this procedures would be widely applied to behavioral modeling of various kinds of power converters. We demonstrate effectiveness of the proposed models with some examples.
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  • Di He
    Article type: Paper
    2017 Volume 8 Issue 1 Pages 49-57
    Published: 2017
    Released on J-STAGE: January 01, 2017
    JOURNAL FREE ACCESS
    In this research, a novel wireless positioning approach which combines the conventional multilateration method and the dynamic stochastic resonance (SR) system is proposed, and it can be easily used in the wireless sensor networks (WSN) node positioning. According to the fact that the wireless signal will attenuate through the wireless channel, which will lead to the degradation of received signal-to-noise ratio (SNR), the conventional quartic double-well bistable SR is introduced to improve the receiving SNR. In the theoretical analyses, it is certified that by choosing the appropriate SR noise and corresponding driving parameters, the SNR gain of the received signal can be obtained, and then the positioning accuracy of WSN will be enhanced. Both computer simulations and real application results show the advantage over the traditional multilateration poisoning method especially under low SNR circumstances.
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  • Yukihiro Tadokoro
    Article type: Paper
    2017 Volume 8 Issue 1 Pages 58-66
    Published: 2017
    Released on J-STAGE: January 01, 2017
    JOURNAL FREE ACCESS
    A theoretical nonlinear filtering method that can estimate a weak signal buried in strong non-Gaussian noise has been proposed in previous studies. This method is attractive because it maximizes the signal-to-noise ratio at the filter output. A mathematical expression for the probability density function (PDF) of the noise is necessary to determine the characteristics of the filter in this method. To enhance the usability of this filtering method, the present study proposes an estimation method for the PDF. Kernel density estimation is considered, and the design framework of two key parameters, the kernel function and bandwidth, is introduced. Employing the Epanechnikov kernel reduces the computational complexity, and the proposed bandwidth achieves a filtering performance close to the theoretical limit. A well-known optimal bandwidth, which minimizes the estimation error, is expected to achieve the best filtering performance, but our proposed method improves upon this performance. In a numerical evaluation, several typical examples of noise types are considered, and the effectiveness of the proposed method is confirmed.
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  • Hiroshi Fujisaki
    Article type: Paper
    2017 Volume 8 Issue 1 Pages 67-78
    Published: 2017
    Released on J-STAGE: January 01, 2017
    JOURNAL FREE ACCESS
    We have previously defined the discretized Markov transformations and the full-length sequences based on such transformations. In view of basic properties of the normalized cross- and auto-correlation functions for the de Bruijn sequences that can be regarded as the full-length sequences based on the discretized dyadic transformation, we obtain correlational properties of the full-length sequences based on the discretized golden mean transformation. We generalize this result and give the correlational properties of the discretized Markov β-transformations with the alphabet Σ={0,1,···,k-1} and the set F={(k-1)(k-1)} of forbidden blocks (k≥2), whose underlying transformations exhibit the most fundamental class of greedy β-expansions of real numbers. We also apply the generalized result to evaluate the auto-correlation function for the optimum binary spreading sequences of Markov chains based on discretized β-transformations.
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