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检索条件"任意字段=Conference on Complexity and Nonlinear Dynamics"

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Multiscale Diffusion Entropy Analysis for the Detection of Crucial Events in Cardiac Pathology

Multiscale Diffusion Entropy Analysis for the Detection of C...

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45th Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Nasrat, Sara A. Mahmoodi, Korosh Khandoker, Ahsan H. Grigolini, Paolo Jelinek, Herbert F. Khalifa Univ Sci & Technol Biomed Engn Dept Abu Dhabi U Arab Emirates Univ North Texas Ctr Nonlinear Sci Denton TX 76203 USA

ISBN: (纸本)9798350324471

The significance of crucial events in explaining the dynamics of a physiological system has only been recently emerging. Crucial events are yet to be fully understood and implemented in clinical applications of physiological signal processing. This paper proposes the application of modified diffusion entropy (MDEA) and novel multiscale diffusion entropy analyses (MSDEA) on measuring the temporal complexity of the ECG time series to improve crucial events detection performance. Thirty samples of each of three groups of ECG datasets from PhysioNet with recordings of cardiac arrhythmia (ARR), congestive heart failure (CHF) and normal sinus rhythm (NSR) were analyzed using MDEA with stripes followed by MSDEA. Healthy NSR ECGs showed an approximate 15% greater inverse power law (IPL) and scaling delta indices than pathologic CHF and ARR signals. Additionally, the scaling indices for the pathologic groups showed higher standard deviations, indicating that crucial events determined by MDEA reveal latent differences in ECG complexity that could better be investigated across multiple time scales of temporally decomposed signals using MSDEA which combines multiscale entropy (MSE) and MDEA. Hence, MSDEA showed an improved, clearer discrimination between the healthy and pathological cardiac signals (p<0.0005) characterized by a range of NSR complexity indices twice the range of the pathological values associated with ARR and CHF across twenty temporal scales as well as more reliable trend lines (R-2>=0.95). Clinical Relevance- This research proposes a novel and enhanced diagnostic discrimination across healthy and pathologic cardiac conditions based on biomedical signal processing of ECG recordings utilizing the principle of crucial events detection.

关键词： Electrocardiograms

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Using Spectral Submanifolds for nonlinear Periodic Control 61

Using Spectral Submanifolds for Nonlinear Periodic Control

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IEEE 61st conference on Decision and Control (CDC)

作者： Mahlknecht, Florian Alora, John Irvin Jain, Shobhit Schmerling, Edward Bonalli, Riccardo Haller, George Pavone, Marco Stanford Univ Dept Aeronaut & Astronaut Stanford CA 94305 USA Swiss Fed Inst Technol Inst Mech Syst CH-8092 Zurich Switzerland Univ Paris Saclay Lab Signals & Syst Cent Supelec CNRS Paris France

ISBN: (纸本)9781665467612

Very high dimensional nonlinear systems arise in many engineering problems due to semi-discretization of the governing partial differential equations, e.g. through finite element methods. The complexity of these systems present computational challenges for direct application to automatic control. While model reduction has seen ubiquitous applications in control, the use of nonlinear model reduction methods in this setting remains difficult. The problem lies in preserving the structure of the nonlinear dynamics in the reduced order model for high-fidelity control. In this work, we leverage recent advances in Spectral Submanifold (SSM) theory to enable model reduction under well-defined assumptions for the purpose of efficiently synthesizing feedback controllers.

关键词： Automation

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Modeling bacteria pairwise interactions in human microbiota by Sparse Identification of nonlinear dynamics (SINDy)

Modeling bacteria pairwise interactions in human microbiota ...

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45th Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Gutierrez-Vilchis, Abel Perfecto-Avalos, Yocanxochitl Garcia-Gonzalez, Alejandro Tecnol Monterrey Sch Med & Hlth Sci Av Ramon Corona 2514 Zapopan 45201 Jal Mexico Tecnol Monterrey Sch Engn & Sci Av Ramon Corona 2514 Zapopan 45201 Jal Mexico

ISBN: (纸本)9798350324471

The gut microbiota is a community of high complexity;its composition changes due to ecological interactions, these are studied to understand the relationship with the human health. External stimuli like the administration of probiotics, prebiotics, or drugs are known to modify these interactions. The high complexity of microbiota composition can be studied by considering pairwise interactions. Pairwise interactions in bacterial communities consider each species' directionality and impact on one another, e.g., commensalism (unidirectional positive interaction) or competition (bidirectional negative interaction). These interactions can either be interspecies or intraspecies. The Lotka- Volterra (LV) model has been implemented to characterize these bacteria interactions, considering the ecological relationship among the different species presented. One of the main challenges is determining the specific interaction parameters in LV structure from experimental data. This study implemented a novel approach based on the sparse identification of nonlinear dynamic method (SINDy). One of the assumptions in SINDy method implies the knowledge of the data derivative structure. To fulfill this requirement, a differential neural network algorithm was implemented. We assessed the performance of this approach considering both a simulated and experimental interspecies scenario. A two-species bacterial LV model was simulated in the initial validation stage, and the resulting kinetic growth data was recorded. This data was utilized for training a differential neural network algorithm, which was used to derive a time-derivative structure for the dataset. After this step, SINDy method was implemented to calculate the interaction parameters. Three conditions were evaluated in intraspecies competition, obtaining an average identification parametric error of less than 2%. For experimental data, parametric analysis results are sensitive to detect the influence of a drug presence over the int

关键词： Bacteria

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On the Sample complexity of Stability Constrained Imitation Learning 4

On the Sample Complexity of Stability Constrained Imitation ...

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4th Annual conference on Learning for dynamics and Control (L4DC)

作者： Tu, Stephen Robey, Alexander Zhang, Tingnan Matni, Nikolai

We study the following question in the context of imitation learning for continuous control: how are the underlying stability properties of an expert policy reflected in the sample complexity of an imitation learning task? We provide the first results showing that a granular connection can be made between the expert system's incremental gain stability, a novel measure of robust convergence between pairs of system trajectories, and the dependency on the task horizon T of the resulting generalization bounds. As a special case, we delineate a class of systems for which the number of trajectories needed to achieve epsilon-suboptimality is sublinear in the task horizon T, and do so without requiring (strong) convexity of the loss function in the policy parameters. Finally, we conduct numerical experiments demonstrating the validity of our insights on both a simple nonlinear system with tunable stability properties, and on a high-dimensional quadrupedal robotic simulation.

关键词： Imitation learning incremental stability behavior cloning statistical learning

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Dynamic Modeling and Sliding Mode Control of an Over-Actuated Quadrotor with Variable Hedral Angle of Propeller Axes 2

Dynamic Modeling and Sliding Mode Control of an Over-Actuate...

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2nd International conference on Unmanned Vehicle Systems (UVS-Oman)

作者： Gavgani, Ali Kafili Talaeizadeh, Amin Heidarzadeh, Siamak Alasty, Aria Pishkenari, Hossein Nejat Sharif Univ Technol Adv Res Lab Control & Agr Robot Sharif AgRoLab Dept Mech Engn Tehran Iran

ISBN: (纸本)9798350372557

The conventional quadrotor, characterized by four control inputs to control six degrees of freedom, is inherently under-actuated, resulting in limited independent control over pitch and roll angles. In this study, we present a configuration that incorporates four additional control inputs for manipulating the angles of the propeller axes. This addresses the previously mentioned limitations and offers additional advantages. Also, it can exhibit enhanced stability during altitude reduction by mitigating the vortex ring state. We derive the dynamic model for this system using Newthon-Euler's method. To address unmodeled dynamics, uncertainties, disturbances, and the inherent complexity of these systems, we utilize a nonlinear robust sliding mode controller. An affining process is performed to account for the non-affine nature of the dynamic equations. We introduce an optimization criteria aimed at maximizing battery life, leveraging the over-actuation of the system. This controller is applied to a dynamic system, infused with various uncertainties, such as inaccurate actuators, high-delayed servo motors, uncertain physical parameters, and wind disturbances. These factors collectively challenge the robustness of the control strategy. Additionally, the controller is implemented on a MATLAB Simscape Multibody model. Given that the controller is model-based, the consistency of the obtained results validates the accuracy of the derived dynamic equations. This research aligns with the project SAC-1, one of the objectives of our lab, Sharif AgRoLab.

关键词： Tilt rotor Robust control nonlinear control Thrust vectoring UAV Battery life

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Towards modeling and influencing the dynamics of human learning 23

Towards modeling and influencing the dynamics of human learn...

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18th Annual ACM/IEEE International conference on Human-Robot Interaction, HRI 2023

作者： Tian, Ran Tomizuka, Masayoshi Dragan, Anca D. Bajcsy, Andrea Uc Berkeley United States

ISBN: (纸本)9781450399647

Humans have internal models of robots (like their physical capabilities), the world (like what will happen next), and their tasks (like a preferred goal). However, human internal models are not always perfect: for example, it is easy to underestimate a robot's inertia. Nevertheless, these models change and improve over time as humans gather more experience. Interestingly, robot actions infuence what this experience is, and therefore infuence how people's internal models change. In this work we take a step towards enabling robots to understand the infuence they have, leverage it to better assist people, and help human models more quickly align with reality. Our key idea is to model the human's learning as a nonlinear dynamical system which evolves the human's internal model given new observations. We formulate a novel optimization problem to infer the human's learning dynamics from demonstrations that naturally exhibit human learning. We then formalize how robots can infuence human learning by embedding the human's learning dynamics model into the robot planning problem. Although our formulations provide concrete problem statements, they are intractable to solve in full generality. We contribute an approximation that sacrifces the complexity of the human internal models we can represent, but enables robots to learn the nonlinear dynamics of these internal models. We evaluate our inference and planning methods in a suite of simulated environments and an in-person user study, where a 7DOF robotic arm teaches participants to be better teleoperators. While infuencing human learning remains an open problem, our results demonstrate that this infuence is possible and can be helpful in real human-robot interaction. © 2023 Copyright held by the owner/author(s).

关键词： dynamics

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Aspects of Assessing the Absolute Stability of Control Systems Containing nonlinear Components

Aspects of Assessing the Absolute Stability of Control Syste...

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2024 Systems of Signal Synchronization, Generating and Processing in Telecommunications, SYNCHROINFO 2024

作者： Yablochnikov, S.L. Yablochnikova, I.O. Dzobelova, V.B. Medvedeva, L.V. Moscow Technical University of Communications and Informatics Plekhanov Russian University of Economics Financial University under the Government of the Russian Federation Moscow Russia Moscow Technical University of Communications and Informatics National University of Oil and Gas 'Gubkin University' Moscow Russia North Ossetian State University Named after Kosta Levanovich Khetagurov Vladikavkaz Russia Peter the Great St. Petersburg Polytechnic University Saint-Petersburg Russia

ISBN: (纸本)9798350373448

In the process of designing various systems, including those that ensure synchronization of a set of different processes, quite often it is necessary to adequately assess the influence of individual nonlinear components on the dynamics of the functioning of these systems, as well as their stability. Such natural nonlinearities, caused by the nature, structure and (or) design of the above components, cannot be successfully formalized by synthesizing models in the form of sufficiently accurate equations. Moreover, the adequacy of such a synthesis of the corresponding mathematical models, in fact, cannot be assessed and confirmed by carrying out a set of full-scale experiments due to their complexity, as well as the possibility of forming various situations with unpredictable negative consequences. Therefore, the authors of this study, based on a system analysis of existing approaches, proposed and justified a number of solutions that allow us to evaluate asymptotic and absolute stability, as well as determine the boundaries of such stability of control systems containing essentially nonlinear components. The results of this scientific research can find practical application in the design of a large set of control systems for various objects and processes. © 2024 IEEE.

关键词： Control system stability

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Brained-inspired optical computing unit based on transient nonlinear dynamics of single-mode fibers

Brained-inspired optical computing unit based on transient n...

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2024 conference on Lasers and Electro-Optics, CLEO 2024

作者： Perron, Nicolas Fischer, Bennet Chemnitz, Mario Zhu, Yi Roztocki, Piotr MacLellan, Benjamin Di Lauro, Luigi Aadhi, A. Rimoldi, Cristina Falk, Tiago H. Morandotti, Roberto Institut National de la recherche scientifique 1650 Bd Lionel-Boulet VarennesQCJ3X 1P7 Canada Leibniz Institute of Photonic Technology Albert-Einstein-Straße 9 Jena07745 Germany Ki3 Photonics Technologies 2547 Rue Sicard MontrealQCH1V 2Y8 Canada Dipartimento di Elettronica e Telecomunicazioni Politecnico di Torino Corso Duca degli Abruzzi 24 Torino10129 Italy

We developed and studied a hardware-based neuromorphic wave computer using optical nonlinearities. Here, we showcase the low-power consumption, robustness, and scalable complexity of soliton-based spectral broadening ... 详细信息

ISBN: (纸本)9781957171395

关键词： Solitons

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An Improved Jellyfish Image Classification Using the EfficientNetB3-Architectured DCNN 12

An Improved Jellyfish Image Classification Using the Efficie...

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12th International conference on Information and Communication Technology, ICoICT 2024

作者： Maxmillian Firdaus, Gian Dwi Sulistiyo, Mahmud Mohd Zarifie Hashim, Nik School of Computing Telkom Univesity Bandung Indonesia Fakulti Kejuruteraan Elektronik Dan Kejuruteraan Komputer Universiti Teknikal Malaysia Melaka Malaysia

ISBN: (纸本)9798350363432

In recent years, deep learning has significantly advanced the field of computer vision with its ability to process data through multiple nonlinear transformation layers, mirroring the neural network of the human brain. Jellyfish play a crucial role in marine ecosystems, and their population dynamics are indicative of environmental changes, making their classification of utmost importance. Traditional manual classification methods are labor-intensive and require expert knowledge, which necessitates the need for an automated system. This study leverages the power of Deep Convolutional Neural Networks (DCNNs) using the EfficientNetB3 architecture to address the challenge of jellyfish image classification. Prior research has demonstrated success in using various CNN architectures for marine life classification and detection, with some optimizing algorithms for improved detection accuracy. This research employs the EfficientNetB3 model, chosen for its balance between complexity and performance efficiency, and applies it to a dataset of 900 jellyfish images across 6 classes from Kaggle. The model's performance is evaluated based on its classification accuracy, demonstrating that the EfficientNetB3 DCNNs outperform standard CNNs in image classification tasks. The findings suggest that with further refinements in architecture and data domain specialization, such models can offer significant insights and contribute to the field of marine organism monitoring. © 2024 IEEE.

关键词： Population dynamics

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Does Anything Beat a GARCH(1,1)? Evidence from Crypto Markets 2nd

Does Anything Beat a GARCH(1,1)? Evidence from Crypto Mark...

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2nd International conference on nonlinear dynamics and Applications, ICNDA 2024

作者： Queiroz, Rhenan Gomes dos Santos David, Sergio Adriani Institute of Mathematics and Computer Sciences University of Sao Paulo Av. Trabalhador são-carlense 400 SP Sao Carlos13560-970 Brazil Systems Dynamics Group University of Sao Paulo Av. Duque de Caxias Norte 225 SP Pirassununga13635-900 Brazil

ISBN: (纸本)9783031691454

We leverage the emerging cryptocurrency markets as an independent testing ground to evaluate the hypothesis that the GARCH(1,1) model serves as an effective and generalizable volatility model due to its simplicity and parsimony. Our investigation extends to five variations of the standard GARCH model across six cryptocurrency markets: Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), Binance Coin (BNB), Ripple (XRP), and Chainlink (LNK). Consistent with findings from conventional financial markets, our analysis endorses the GARCH(1,1) model as a suitable prior for cryptocurrency volatility modeling, demonstrating superior performance in four out of the six markets examined. Specifically for Bitcoin, incorporating an E-GARCH model to account for asymmetric volatility responses to positive and negative market movements offers significant modeling advantages, despite the increased complexity and associated model risk. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Decentralized finance

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