Results 31 to 40 of about 14,438 (228)

Finite-Time Lyapunov Functions and Impulsive Control Design

open access: yesComplexity, 2020
In this paper, we introduce finite-time Lyapunov functions for impulsive systems. The relaxed sufficient conditions for asymptotic stability of an equilibrium of an impulsive system are given via finite-time Lyapunov functions.
Huijuan Li, Qingxia Ma
doaj   +1 more source

Programmable Chaotic Suspension Electrolysis for Scalable Manufacturing of Vacancy‐Tunable Electrolytic MnO2

open access: yesAdvanced Science, EarlyView.
Programmable chaotic suspension electrolysis bridges laboratory synthesis and industrial manufacturing of high‐performance MnO2 cathodes. This scalable strategy enables tunable oxygen vacancies and a robust γ/β tunnel framework, delivering superior electrochemical performance and thermal stability.
Zhihao Wu   +16 more
wiley   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

open access: yesAdvanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows   +7 more
wiley   +1 more source

Large-Signal Stability Modeling for the Grid-Connected VSC Based on the Lyapunov Method

open access: yesEnergies, 2018
In this paper, a Lyapunov-based method is used in order to determine the stability boundaries of the grid-connected voltage source converter (VSC). To do so, a state space model of the VSC is used to form the Lyapunov function of the system.
Bahram Shakerighadi   +3 more
doaj   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

open access: yesAdvanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison   +4 more
wiley   +1 more source

BACKPROPAGATION TRAINING ALGORITHM WITH ADAPTIVE PARAMETERS TO SOLVE DIGITAL PROBLEMS [PDF]

open access: yesICTACT Journal on Soft Computing, 2011
An efficient technique namely Backpropagation training with adaptive parameters using Lyapunov Stability Theory for training single hidden layer feed forward network is proposed.
R. Saraswathi
doaj  

Lyapunov Functions to Caputo Fractional Neural Networks with Time-Varying Delays

open access: yesAxioms, 2018
One of the main properties of solutions of nonlinear Caputo fractional neural networks is stability and often the direct Lyapunov method is used to study stability properties (usually these Lyapunov functions do not depend on the time variable).
Ravi Agarwal   +2 more
doaj   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

open access: yesAI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury   +2 more
wiley   +1 more source

Stochasticity of Galactic Orbits of Star Clusters

open access: yesOpen Astronomy, 2015
The Lyapunov, Lagrange and Poincaré criteria are tested for orbits of 461 open clusters in an axisymmetric potential. Lyapunov exponents and Poincaré sections are computed, and all of the trajectories are found to be stable according to the Lagrange and ...
Smirnova L. V.
doaj   +1 more source

On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools

open access: yesFrontiers in Applied Mathematics and Statistics, 2022
Recurrent neural networks (RNNs) have been successfully applied to a variety of problems involving sequential data, but their optimization is sensitive to parameter initialization, architecture, and optimizer hyperparameters.
Ryan Vogt   +6 more
doaj   +1 more source

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