Results 31 to 40 of about 15,223 (231)
Robotics in Ionizing Radiation Environments: Vulnerabilities, Hardening, and Future Directions
Advanced Robotics Research, EarlyView.Radiation exposure causes cumulative degradation in robotic sensors, actuators, and electronic logic, often leading to undetected failures. This study maps component vulnerabilities, evaluates hardening and shielding strategies, and identifies testing gaps that must be addressed to enable next‐generation radiation‐tolerant robotic systems.
Francis A. K. Djirackor +4 more
wiley +1 more source
Large-Signal Stability Modeling for the Grid-Connected VSC Based on the Lyapunov Method
Energies, 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
Analytical Prediction of Critical Transitions in Oscillator Networks With Non‐Local Links
Advanced Science, EarlyView.An analytical framework reveals how global coupling, second‐harmonic strength, noise, and network structure govern oscillator‐based Ising dynamics. Spectral reduction predicts stability boundaries, while Fokker–Planck analysis captures one‐ to two‐cluster transitions and identifies conditions favoring low‐energy configurations.
Qiang Li +5 more
wiley +1 more source
BACKPROPAGATION TRAINING ALGORITHM WITH ADAPTIVE PARAMETERS TO SOLVE DIGITAL PROBLEMS [PDF]
ICTACT 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
Axioms, 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
Device Stochasticity Directly Implements Bayesian Sampling in Spiking Neurons
Advanced Science, EarlyView.Brain‐inspired stochastic spiking turns device noise into Bayesian uncertainty for robust, low‐power neuromorphic computing. ABSTRACT Device stochasticity is considered a non‐ideality in neuromorphic hardware, although stochastic neural activity supports probabilistic computation in biological systems.
Huannan Zheng, Jingli Liu, Kezhou Yang
wiley +1 more source
Stochasticity of Galactic Orbits of Star Clusters
Open 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
Frontiers 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
Advanced Electronic Materials, EarlyView.Resistively switching TiN/Hf0.5Zr0.5/Au valance‐change memory devices show period‐doubling bifurcations, arising from competing influences of filamentary counter‐eightwise filamentary switching and eigthwise electrochemical oxygen exchange at the active electrode.
Sebastian Obernberger +4 more
wiley +1 more source
Journal of Applied Mathematics, 2014 We investigate the qualitative behavior of a perturbed causal differential equation that differs in initial position and initial time with respect to the unperturbed causal differential equations.
Coşkun Yakar, Mustafa Bayram Gücen
doaj +1 more source