Results 21 to 30 of about 1,027,590 (285)

The Connection between Bayesian Inference and Information Theory for Model Selection, Information Gain and Experimental Design

Entropy, 2019
We show a link between Bayesian inference and information theory that is useful for model selection, assessment of information entropy and experimental design.
Sergey Oladyshkin, Wolfgang Nowak
doaj   +1 more source

A Hardware Efficient Random Number Generator for Nonuniform Distributions with Arbitrary Precision

International Journal of Reconfigurable Computing, 2012
Nonuniform random numbers are key for many technical applications, and designing efficient hardware implementations of non-uniform random number generators is a very active research field.
Christian de Schryver, Daniel Schmidt, Norbert Wehn, Elke Korn, Henning Marxen, Anton Kostiuk, Ralf Korn   +6 more
doaj   +1 more source

Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions

Sensors
Floating wind turbines (FWTs) operate in offshore environments under harsh and varying operating conditions, making frequent in situ monitoring dangerous for maintenance teams and costly for operators. Remote and automated diagnosis, including the stages
John S. Korolis, Dimitrios M. Bourdalos, John S. Sakellariou   +2 more
doaj   +1 more source

Times Series Averaging and Denoising from a Probabilistic Perspective on Time–Elastic Kernels

International Journal of Applied Mathematics and Computer Science, 2019
In the light of regularized dynamic time warping kernels, this paper re-considers the concept of a time elastic centroid for a set of time series. We derive a new algorithm based on a probabilistic interpretation of kernel alignment matrices.
Marteau Pierre-Francois
doaj   +1 more source

Lagrangian Descriptors for Stochastic Differential Equations: A Tool for Revealing the Phase Portrait of Stochastic Dynamical Systems [PDF]

, 2016
In this paper we introduce a new technique for depicting the phase portrait of stochastic differential equations. Following previous work for deterministic systems, we represent the phase space by means of a generalization of the method of Lagrangian ...
Balibrea-Iniesta, Francisco, Lopesino, Carlos, Mancho, Ana M., Wiggins, Stephen   +3 more
core   +3 more sources

Memristor-based model of neuronal excitability and synaptic potentiation

Frontiers in Neuroscience
In this manuscript, we investigate the memristor-based implementation of neuronal ion channels in a mathematical model and an experimental circuit for a neuronal oscillator. We used a FitzHugh-Nagumo equation system describing neuronal excitability.
Ivan M. Kipelkin, Ivan M. Kipelkin, Svetlana A. Gerasimova, Alexey I. Belov, Davud V. Guseinov, Alexander V. Kruglov, Dmitry A. Serov, Max O. Talanov, Max O. Talanov, Alexey N. Mikhaylov, Alexey N. Mikhaylov, Victor B. Kazantsev, Victor B. Kazantsev   +12 more
doaj   +1 more source

Symbolic Models for Stochastic Switched Systems: A Discretization and a Discretization-Free Approach [PDF]

, 2014
Stochastic switched systems are a relevant class of stochastic hybrid systems with probabilistic evolution over a continuous domain and control-dependent discrete dynamics over a finite set of modes.
Abate, Alessandro, Girard, Antoine, Zamani, Majid   +2 more
core   +3 more sources

Stochastic hamiltonian dynamical systems [PDF]

Reports on Mathematical Physics, 2008
46 pages. A converse to the Critical Action Principle has been added. The discussion on conserved quantities has been extended and linked to the study of the stability of equilibria of the solution ...
Lázaro-Camí, Joan-Andreu, Ortega, Juan-Pablo   +1 more
openaire   +2 more sources

Organizing the interface—Plasma membrane architecture and receptor dynamics in virus‐cell interactions

FEBS Letters, EarlyView.
Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley   +1 more source

A Machine Learning Vibration-Based Methodology for Robust Detection and Severity Characterization of Gear Incipient Faults Under Variable Working Speed and Load

Machines
A machine learning (ML) methodology for the robust detection and severity characterization of incipient gear faults under variable speed and load is postulated. The methodology is trained using vibration signals from a single accelerometer mounted on the
Dimitrios M. Bourdalos, John S. Sakellariou   +1 more
doaj   +1 more source