Results 101 to 110 of about 6,086,701 (288)
Using Subspace Methods for Estimating ARMA Models for Multivariate Time Series with Conditionally Heteroskedastic Innovations [PDF]
This paper deals with the estimation of linear dynamic models of the ARMA type for the conditional mean for time series with conditionally heteroskedastic innovation process widely used in modelling financial time series.
Dietmar Bauer
core
The method presented in this paper provides a practical sensorless solution for estimating both contact force and contact location using only standard joint encoders and an available robot dynamic model. By reformulating the contact estimation problem using a single scalar equivalent contact parameter, the approach enables fast and robust computation ...
Thanh‐Quan Ta, Shyh‐Leh Chen
wiley +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
—Subspace-based blind and group-blind space–time (ST) multiuser detection (MUD) is invoked for a smart-antenna-aided gen-eralized multicarrier direct-sequence code-division multiple-access (MC DS-CDMA) system communicating over a dispersive ST Rayleigh ...
Lie-liang Yang +5 more
core
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Stochastic hierarchical data-driven optimization: application to plasma-surface kinetics
This work introduces a stochastic hierarchical optimization framework inspired by sloppy model theory for the efficient calibration of physical models. Central to this method is the use of a reduced Hessian approximation, which identifies and targets the
José Afonso, Vasco Guerra, Pedro Viegas
doaj +1 more source
Modeling consonant-vowel coarticulation for articulatory speech synthesis.
A central challenge for articulatory speech synthesis is the simulation of realistic articulatory movements, which is critical for the generation of highly natural and intelligible speech.
Peter Birkholz
doaj +1 more source
Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality [PDF]
A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules.
Harris, C. J. +3 more
core +1 more source
Central kernels of subspaces of
For any closed subspace \(L\) of a complex Banach space \(A\), there exists a greatest M-ideal \(k_n(L)\) of \(A\) contained in \(L\). The space \(k_n (L)\) is called the norm central kernel of \(L\) in \(A\). When \(A\) is a dual space and \(L\) is a weak*-closed subspace, there exists a greatest M-summand \(k(L)\) of \(A\) contained in \(A\). \(k(L)\)
Edwards, C, Hoskin, C
openaire +3 more sources
Towards Human‐Centered Intelligent Inhabitable Spaces: A Review
This review introduces Robot‐Rooms as a new category of architectural‐scale robots that do not operate within a space but actively form and reconfigure the space around their occupants. Drawing from robotics, HCI, architecture, and the arts, an interdisciplinary framework is proposed that maps the enabling technologies and integration challenges ...
Nithesh Kumar +3 more
wiley +1 more source

