Results 81 to 90 of about 221,116 (284)
Two stochastic models for simulation of correlated random processes [PDF]
Mathematical models for simulation of correlated stochastic processes with stationary Gaussian ...
Hoshiya, M., Tieleman, H. W.
core +1 more source
Human‐Machine Mutual Trust Based Shared Control Framework for Intelligent Vehicles
This work introduces a bidirectional‐trust‐driven shared control framework for human‐machine co‐driving. The method models human‐to‐machine trust from intention discrepancies and Bayesian skill assessment, and machine‐to‐human trust from integrated ability evaluation.
Zhishuai Yin +4 more
wiley +1 more source
Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera +2 more
wiley +1 more source
Application of Hölder Function to Expansion Intensity of Spatial Phenomena Analysis
The development of methods describing time series using stochastic processes took place in the 20th century. Among others, stationary processes were modelled with Hurst exponent, whereas non‑stationary processes with Hölder function.
Adrianna Damiana Mastalerz-Kodzis +1 more
doaj +1 more source
On a class of nonstationary stochastic processes [PDF]
A new class of nonstationary stochastic processes is introduced and some of the essential properties of its members are investigated. This class is richer than the class of stationary processes and has the potential of modeling some nonstationary time ...
Hardin, Jay C., Miamee, A. G.
core +1 more source
A statistical and machine learning‐assisted surface‐enhanced Raman scattering (SERS) framework is developed for label‐free quantification of low‐abundance analytes, including proteins. Combining digital SERS event counting with binomial regression and an artificial neural network (ANN) trained on full spectra, the approach achieves picomolar detection ...
Eni Kume, James Rice
wiley +1 more source
LÉVY-BASED ERROR PREDICTION IN CIRCULAR SYSTEMATIC SAMPLING
In the present paper, Lévy-based error prediction in circular systematic sampling is developed. A model-based statistical setting as in Hobolth and Jensen (2002) is used, but the assumption that the measurement function is Gaussian is relaxed.
Kristjana Ýr Jónsdóttir +1 more
doaj +1 more source
Modeling and parameter estimation for fractional large‐scale interconnected Hammerstein systems
Abstract This paper addresses the challenge of modeling and identifying large‐scale interconnected systems exhibiting memory effects, hereditary properties, and non‐local interactions. We propose a fractional‐order extension of the Hammerstein architecture that incorporates Grünwald–Letnikov operators to capture complex dynamics through multiple ...
Mourad Elloumi +2 more
wiley +1 more source
Far-From-Equilibrium Time Evolution between Two Gamma Distributions
Many systems in nature and laboratories are far from equilibrium and exhibit significant fluctuations, invalidating the key assumptions of small fluctuations and short memory time in or near equilibrium.
Eun-jin Kim +3 more
doaj +1 more source
Repeating Nuclear Transients From Repeating Partial Tidal Disruption Events
ABSTRACT Extragalactic nuclear transients that exhibit repeating outbursts can be modeled as the repeated dynamical interaction between bound stars and supermassive black holes (SMBHs). A subset of these transients, with recurrence timescales of months‐to‐years, have been explained as accretion flares from the repeated tidal stripping of a star by an ...
Ananya Bandopadhyay +4 more
wiley +1 more source

