Studies on the dynamics of chaotic multi-wavelet reentrant propagation using a hybrid cellular automaton model of excitable tissue

There is a compelling body of evidence implicating continuous propagation (reentry) sustained by multiple meandering wavelets in the pathology of advanced human atrial fibrillation (AF). This forms the basis for many current therapies such as the Cox MAZE procedure and its derivatives, which aim to create non-conducting lesions in order to "transect" these circuits before they form. Nevertheless, our ability to successfully treat persistent and permanent AF using catheter ablation remains inadequate due to current limitations of clinical mapping technology as well as an incomplete understanding of how to place lesions in order to maximize circuit transection and, more importantly, minimize AF burden. Here, we used a hybrid cellular automaton model to study the dynamics of chaotic, multi-wavelet reentry (MWR) in excitable tissue. First, we used reentry as an exemplar to investigate a hysteretic disease mechanism in a multistable nonlinear system. We found that certain interactions with the environment can cause persistent changes to system behavior without altering its structure or properties, thus leading to a disconnect between clinical symptoms and the underlying state of disease. Second, we developed a novel analytical method to characterize the spatiotemporal dynamics of MWR. We identified a heterogeneous spatial distribution of reentrant pathways that correlated with the spatial distribution of cell activation frequencies. Third, we investigated the impact of topological and geometrical substrate alterations on the dynamics of MWR. We demonstrated a multi-phasic relationship between obstacle size and the fate of individual episodes. Notably, for a narrow range of sizes, obstacles appeared to play an active role in rapidly converting MWR to stable structural reentry. Our studies indicate that reentrant-pathway distributions are non-uniform in heterogeneous media (such as the atrial myocardium) and suggest a clinically measurable correlate for identifying regions of high circuit density, supporting the feasibility of patient-specific targeted ablation. Moreover, we have elucidated the key mechanisms of interaction between focal obstacles and MWR, which has implications for the use of spot ablation to treat AF as some recent studies have suggested

Effects of the local dynamics in the synchronization of neural models

Orientador: Prof. Dr. Sergio Roberto LopesTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Física. Defesa : Curitiba, 24/02/2022Inclui referênciasResumo: O comportamento cooperativo de neurônios e áreas neuronais associadas ao comportamento de sincronização se apresenta como mecanismo fundamental para o funcionamento cerebral. Além disso, níveis anormais de sincronização têm sido relacionados a estados patológicos. Ao longo desta tese, abordam-se diferentes fenômenos de sincronização que surgem por meio da dinâmica coletiva de modelos de neurônios acoplados em um a rede. Primeiramente, mostra-se um a forte correlação entre a dinâmica individual do neurônio com o comportamento global da sincronização da rede, em que a periodicidade observada no neurônio isolado é refletida em um a sincronização de fase ao considerar um acoplamento fraco. Em segundo lugar, estuda-se o papel da biestabilidade na sincronização de um a rede de neurônios idênticos, acoplados através de um esquema de campo médio. Mostra-se que a simples existência de dois estados estáveis distintos pode levar a rede a diferentes estados de sincronização, dependendo da inicialização do sistema. Por fim, é investigado o mecanismo de sincronização explosiva de um a rede neural complexa composta por neurônios não-idênticos. A presença deste regime é acompanhada por um loop de histerese na dinâmica da rede, à medida que o parâmetro de acoplamento é adiabaticamente aumentado e reduzido. Demonstra-se que as transições de sincronização abruptas estão associadas a rotas para o caos e que os mecanismos dinâmicos para a região de biestabilidade são dados em termos de um a bifurcação de sela-nó e um a crise de fronteira. Portanto, os resultados desta tese mostram uma riqueza de comportamentos de sincronização associados a pequenas mudanças na dinâmica neuronal, trazendo novos insights para o estudo teórico das redes neurais.Abstract: The cooperative behavior of neurons and neuronal areas associated with the synchronization behavior proves to be a fundamental neural mechanism. In addition, abnormal levels of synchronization have been related to unhealthy neural behaviors. Throughout this thesis, it is explored different synchronization phenomena which emerge through the collective dynamics of models of neurons coupled in a network. Firstly, it is shown a strong correlation between the individual dynamics of the neuron with the global behavior of the synchronization, in which the periodicity seen in the isolated neuron is reflected in a phase synchronization in the weak coupling region. Secondly, it is studied the role of bistability in the synchronization of a network of identical neurons coupled through a mean-field scheme. It is shown that the simple existence of two distinct stable states can lead the network to different states of synchronization, depending on the initialization of the system. Lastly, it is investigated the mechanism for explosive synchronization of a complex neural network composed of non-identical neurons. The presence of this regime is accompanied by a hysteresis loop on the network dynamics as the coupling parameter is adiabatically increased and decreased. It is shown that the abrupt synchronization transitions are associated with routes to chaos. The dynamical mechanisms for the bistability region, are given in terms of a saddle-node bifurcation and a boundary crisis. Therefore, the results of this thesis show a richness of synchronization behaviors associated with small changes of the neuronal dynamics bringing new insights to the theoretical study of neural networks

18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems: Proceedings

Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I Table of Contents ........................ Page III Symposium Committees .............. Page IV Special Thanks ............................. Page V Conference program (incl. page numbers of papers) ................... Page VI Conference papers Invited talks ................................ Page 1 Regular Papers ........................... Page 14 Wednesday, May 26th, 2010 ......... Page 15 Thursday, May 27th, 2010 .......... Page 110 Friday, May 28th, 2010 ............... Page 210 Author index ............................... Page XII

Chaotification as a Means of Broadband Vibration Energy Harvesting with Piezoelectric Materials

Computing advances and component miniaturization in circuits coupled with stagnating battery technology have fueled growth in the development of high efficiency energy harvesters. Vibration-to-electricity energy harvesting techniques have been investigated extensively for use in sensors embedded in structures or in hard-to-reach locations like turbomachinery, surgical implants, and GPS animal trackers. Piezoelectric materials are commonly used in harvesters as they possess the ability to convert strain energy directly into electrical energy and can work concurrently as actuators for damping applications. The prototypical harvesting system places two piezoelectric patches on both sides of the location of maximum strain on a cantilever beam. While efficient around resonance, performance drops dramatically should the driving frequency drift away from the beam\u27s fundamental frequency. To date, researchers have worked to improve harvesting capability by modifying material properties, using alternative geometries, creating more efficient harvesting circuits, and inducing nonlinearities. These techniques have partially mitigated the resonance excitation dependence for vibration-based harvesting, but much work remains. In this dissertation, an induced nonlinearity destabilizes a central equilibrium point, resulting in a bistable potential function governing the cantilever beam system. Depending on the environment, multiple stable solutions are possible and can coexist. Typically, researchers neglect chaos and assume that with enough energy in the ambient environment, large displacement trajectories can exist uniquely. When subjected to disturbances a system can fall to coexistent lower energy solutions including aperiodic, chaotic oscillations. Treating chaotic motion as a desirable behavior of the system allows frequency content away from resonance to produce motion about a theoretically infinite number of unstable periodic orbits that can be stabilized through control. The extreme sensitivity to initial conditions exhibited by chaotic systems paired with a pole placement control strategy pioneered by Ott, Grebogi, and Yorke permits small perturbations to an accessible system parameter to alter the system response dramatically. Periodic perturbation of the system trajectories in the vicinity of isolated unstable orbit points can therefore stabilize low-energy chaotic oscillations onto larger trajectory orbits more suitable for energy harvesting. The periodic perturbation-based control method rids the need of a system model. It only requires discrete displacement, velocity, or voltage time series data of the chaotic system driven by harmonic excitation. While the analysis techniques are not fundamentally limited to harmonic excitation, this condition permits the use of standard discrete mapping techniques to isolate periodic orbits of interest. Local linear model fits characterize the orbit and admit the necessary control perturbation calculations from the time series data. This work discusses the feasibility of such a method for vibration energy harvesting, displays stable solutions under various control algorithms, and implements a hybrid bench-top experiment using MATLAB and LabVIEW FPGA. In conclusion, this work discusses the limitations for wide-scale use and addresses areas of further work; both with respect to chaotic energy harvesting and parallel advances required within the field as a whole

Design and Control of Power Converters for High Power-Quality Interface with Utility and Aviation Grids

Power electronics as a subject integrating power devices, electric and electronic circuits, control, and thermal and mechanic design, requires not only knowledge and engineering insight for each subarea, but also understanding of interface issues when incorporating these different areas into high performance converter design.Addressing these fundamental questions, the dissertation studies design and control issues in three types of power converters applied in low-frequency high-power transmission, medium-frequency converter emulated grid, and high-frequency high-density aviation grid, respectively, with the focus on discovering, understanding, and mitigating interface issues to improve power quality and converter performance, and to reduce the noise emission.For hybrid ac/dc power transmission,• Analyze the interface transformer saturation issue between ac and dc power flow under line unbalances.• Proposed both passive transformer design and active hybrid-line-impedance-conditioner to suppress this issue.For transmission line emulator,• Propose general transmission line emulation schemes with extension capability.• Analyze and actively suppress the effects of sensing/sampling bias and PWM ripple on emulation considering interfaced grid impedance.• Analyze the stability issue caused by interaction of the emulator and its interfaced impedance. A criterion that determines the stability and impedance boundary of the emulator is proposed.For aircraft battery charger,• Investigate architectures for dual-input and dual-output battery charger, and a three-level integrated topology using GaN devices is proposed to achieve high density.• Identify and analyze the mechanisms and impacts of high switching frequency, di/dt, dv/dt on sensing and power quality control; mitigate solutions are proposed.• Model and compensate the distortion due to charging transition of device junction capacitances in three-level converters.• Find the previously overlooked device junction capacitance of the nonactive devices in three-level converters, and analyze the impacts on switching loss, device stress, and current distortion. A loss calculation method is proposed using the data from the conventional double pulse tester.• Establish fundamental knowledge on performance degradation of EMI filters. The impacts and mechanisms of both inductive and capacitive coupling on different filter structures are understood. Characterization methodology including measuring, modeling, and prediction of filter insertion loss is proposed. Mitigation solutions are proposed to reduce inter-component coupling and self-parasitics

Communications

The communications sector of an economy comprises a range of technologies, physical media, and institutions/rules that facilitate the storage of information through means other than a society\u27s oral tradition and the transmission of that information over distances beyond the normal reach of human conversation. This chapter provides data on the historical evolution of a disparate range of industries and institutions contributing to the movement and storage of information in the United States over the past two centuries. These include the U.S. Postal Service, the newspaper industry, book publishing, the telegraph, wired and cellular telephone service, radio and television, and the Internet

Cooperative Control of Nonlinear Multi-Agent Systems

Multi-agent systems have attracted great interest due to their potential applications in a variety of areas. In this dissertation, a nonlinear consensus algorithm is developed for networked Euler-Lagrange multi-agent systems. The proposed consensus algorithm guarantees that all agents can reach a common state in the workspace. Meanwhile, the external disturbances and structural uncertainties are fundamentally considered in the controller design. The robustness of the proposed consensus algorithm is then demonstrated in the stability analysis. Furthermore, experiments are conducted to validate the effectiveness of the proposed consensus algorithm. Next, a distributed leader-follower formation tracking controller is developed for networked nonlinear multi-agent systems. The dynamics of each agent are modeled by Euler-Lagrange equations, and all agents are guaranteed to track a desired time-varying trajectory in the presence of noise. The fault diagnosis strategy of the nonlinear multi-agent system is also investigated with the help of differential geometry tools. The effectiveness of the proposed controller is verified through simulations. To further extend the application area of the multi-agent technique, a distributed robust controller is then developed for networked Lipschitz nonlinear multi-agent systems. With the appearance of system uncertainties and external disturbances, a sampled-data feedback control protocol is carried out through the Lyapunov functional approach. The effectiveness of the proposed controller is verified by numerical simulations. Other than the robustness and sampled-data information exchange, this dissertation is also concerned with the event-triggered consensus problem for the Lipschitz nonlinear multi-agent systems. Furthermore, the sufficient condition for the stochastic stabilization of the networked control system is proposed based on the Lyapunov functional method. Finally, simulation is conducted to demonstrate the effectiveness of the proposed control algorithm. In this dissertation, the cooperative control of networked Euler-Lagrange systems and networked Lipschitz systems is investigated essentially with the assistance of nonlinear control theory and diverse controller design techniques. The main objective of this work is to propose realizable control algorithms for nonlinear multi-agent systems

Ultra low power wearable sleep diagnostic systems

Sleep disorders are studied using sleep study systems called Polysomnography that records several biophysical parameters during sleep. However, these are bulky and are typically located in a medical facility where patient monitoring is costly and quite inefficient. Home-based portable systems solve these problems to an extent but they record only a minimal number of channels due to limited battery life. To surmount this, wearable sleep system are desired which need to be unobtrusive and have long battery life. In this thesis, a novel sleep system architecture is presented that enables the design of an ultra low power sleep diagnostic system. This architecture is capable of extending the recording time to 120 hours in a wearable system which is an order of magnitude improvement over commercial wearable systems that record for about 12 hours. This architecture has in effect reduced the average power consumption of 5-6 mW per channel to less than 500 uW per channel. This has been achieved by eliminating sampled data architecture, reducing the wireless transmission rate and by moving the sleep scoring to the sensors. Further, ultra low power instrumentation amplifiers have been designed to operate in weak inversion region to support this architecture. A 40 dB chopper-stabilised low power instrumentation amplifiers to process EEG were designed and tested to operate from 1.0 V consuming just 3.1 uW for peak mode operation with DC servo loop. A 50 dB non-EEG amplifier continuous-time bandpass amplifier with a consumption of 400 nW was also fabricated and tested. Both the amplifiers achieved a high CMRR and impedance that are critical for wearable systems. Combining these amplifiers with the novel architecture enables the design of an ultra low power sleep recording system. This reduces the size of the battery required and hence enables a truly wearable system.Open Acces