京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18991号 / 工博第4033号 / 新制||工||1621(附属図書館) / 31942 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 引原 隆士, 教授 土居 伸二, 教授 小林 哲生 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19309号 / 工博第4106号 / 新制||工||1633(附属図書館) / 32311 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 引原 隆士, 准教授 三谷 友彦, 教授 岡部 寿男, 教授 土居 伸二, / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Fast neural oscillations known as beta (12-30Hz) and gamma (30-100Hz) rhythms are recorded across several brain areas of various species. They have been linked to diverse functions like perception, attention, cognition, or interareal brain communication. The majority of the tasks performed by the brain involves communication between brain areas. To efficiently perform communication, mathematical models of brain activity require representing neural oscillations as sustained and coherent rhythms. However, some recordings show that fast oscillations are not sustained or coherent. Rather they are noisy and appear as short and random epochs of sustained activity called bursts. Therefore, modeling such noisy oscillations and investigating their ability to show interareal coherence and phase synchronization are important questions that need to be addressed. In this thesis, we propose theoretical models of noisy oscillations in the gamma and beta bands with the same properties as those observed in in \textit{vivo}. Such models should exhibit dynamic and statistical features of the data and support dynamic phase synchronization. We consider networks composed of excitatory and inhibitory populations. Noise is the result of the finite size effect of the system or the synaptic inputs. The associated dynamics of the Local Field Potentials (LFPs) are modeled as linear equations, sustained by additive and/or multiplicative noises. Such oscillatory LFPs are also known as noise-induced or quasi-cycles oscillations. The LFPs are better described using the envelope-phase representation. In this framework, a burst is defined as an epoch during which the envelope magnitude exceeds a given threshold. Fortunately, to the lowest order, the envelope dynamics are uncoupled from the phase dynamics for both additive and multiplicative noises. For additive noise, we derive the mean burst duration via a mean first passage time approach and uncover an optimal range of parameters for healthy rhythms. Multiplicative noise is shown theoretically to further synchronize neural activities and better explain pathologies with an excess of neural synchronization. We used the stochastic averaging method (SAM) as a theoretical tool to derive the envelope-phase equations. The SAM is extended to extract the envelope-phase equations of two coupled brain areas. The goal is to tackle the question of phase synchronization of noise-induced oscillations with application to interareal brain communication. The results show that noise and propagation delay are essential ingredients for dynamic phase synchronization of quasi-cycles. This suggests that the noisy oscillations recorded in \textit{vivo} and modeled here as quasi-cycles are good candidates for such neural communication. We further extend the use of the SAM to describe several coupled networks subject to white and colored noises across the Hopf bifurcation ie in both quasi-cycle and limit cycle regimes. This allows the description of multiple brain areas in the envelope-phase framework. The SAM constitutes an appropriate and flexible theoretical tool to describe a large class of stochastic oscillatory phenomena through the envelope-phase framework.

京都大学 / 新制・課程博士 / 博士(理学) / 甲第24458号 / 理博第4957号 / 新制||理||1708(附属図書館) / 京都大学大学院理学研究科生物科学専攻 / (主査)教授 高橋 淑子, 准教授 佐藤 ゆたか, 教授 中務 真人 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

A rising level of industrialization and advances in Industry 4.0 have resulted in Industrial Internet of Things (IIoT) gaining immense significance in today’s industrial automation systems. IIoT promises to achieve improved productivity, reliability, and revenues by connecting time-constrained embedded systems to “the Internet”. New opportunities bring with them challenges, and in particular for industrial networks, massively interconnected IIoT devices communicating in real-time,  require synchronized operation of devices for the ordering of information collected throughout a  network. Thus,   a   time or clock synchronization service that aligns the devices’ clocks in the network to ensure accurate timestamping and orderly event executions, has gained great importance. Achieving adequate clock synchronization in the industrial domain is challenging due to heterogeneous communication networks and exposure to harsh environmental conditions bringing interference to the communication networks. The investigative study based on existing literature and the envisioned architecture of the future industrial automation system unveils that the key requirements for future industrial networks are to have a cost-effective, accurate, scalable, secured, easy to deploy and maintain clock synchronization solution. Today’s industrial automation systems employ clock synchronization solutions from a wide plethora of hardware and software based solutions. The most economical, highly scalable, maintainable software-based clock synchronization means are best candidates for the identified future requirements as their lack in accuracy compared to hardware solutions could be compensated by predictive software strategies.  Thus, the thesis’s overall goal is to enhance the accuracy of software-based clock synchronization in heterogeneous industrial networks using predictable software strategies. The first step towards developing an accurate clock synchronization for heterogeneous industrial networks with real-time requirements is to investigate communication parameters affecting time synchronization accuracy. Towards this goal, we investigated actual industrial network data for packet delay profiles and their impact on clock synchronization performance.  We further analyzed wired and wireless local area networks to identify key network parameters for clock synchronization and proposed an enhanced clock synchronization algorithm CoSiNeT for field IoT devices in industrial networks. CoSiNeT matches well with state-of-the-practice SNTP and state-of-the-art method SPoT in good network conditions in terms of accuracy and precision;  however,  it outperforms them in scenarios with degrading network conditions.

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Synchronization and estimation of unknown constant parameters for Lorenz-type transmitter are studied under the assumption that one of the three state variables is not transmitted and that transmitter parameters are not known apriori. An adaptive algorithm is proposed to estimate both the state and system parameters. Since Lorenz system shows the property of sensitivity to initial conditions and evolves in different mode with parameter variation, an equivalent system is introduced. The adaptive observer is designed based on this equivalent system without any requirement on initial conditions of the observer. It is shown by Lyapunov arguments and persistent excitation analysis that exponential stability of state and parameter estimation is guaranteed. Simulation results are included to demonstrate properties of the algorithm. In a practical communication system, the received signals presented at the receiver part differ from those which were transmitted due to the effects of noise. The proposed synchronization scheme is robust with regard to external bounded disturbance. When an additive white gaussian noise (AWGN) channel model is considered, estimates of state and parameter converge except for small errors. The results show promise in either coherent detection or the message decoding in telecommunication systems.

A study on phase synchronization in large populations of nonlinear dynamical systems is presented in this thesis. Using the well-known Rossler system as a prototypical model, phase synchronization in one oscillator with periodic external forcing and in two-coupled nonidentical oscillators was explored at first. The study was further extended to consider three-dimensional lattices and globally coupled populations of nonidentical oscillators, in which the mathematical formulation that represents phase synchronization in the generalized N-coupled Rossler system was derived and several computer programs that perform numerical simulations were developed. The results show the effects of coupling dimension, coupling strength, population size, and system parameter on phase synchronization of the various Rossler systems, which may be applicable to studying phase synchronization in other nonlinear dynamical systems as well.

This dissertation analyzes the fundamental limits for the determination of the network structure of loosely coupled oscillators based on observing the behavior of the network, specifically, node synchronization. The determination of the requisite characteristics and underlying behaviors necessary for the application of a theoretical mechanism for determining the underlying network topology in a network of loosely coupled natural oscillators are the desired outcome. To that end, this effort defines an analytical framework where key components of networks of coupled oscillators are isolated in order to determine the relationships between the various components. The relationship between the number of nodes in a network, the number of connections in the network, the number of connections of a given node, the distribution of the phases of the network, and the resolution of measurement of the components of the network, and system noise is investigated.