Results 81 to 90 of about 298,891 (271)
Self-Adaptive Multi-Sensor Activity Recognition Systems Based on Gaussian Mixture Models
Informatics, 2018 Personal wearables such as smartphones or smartwatches are increasingly utilized in everyday life. Frequently, activity recognition is performed on these devices to estimate the current user status and trigger automated actions according to the user ...
Martin Jänicke +2 more
doaj +1 more source
Advanced Functional Materials, EarlyView.A novel phthalocyanine (PC)‐based metal–organic framework (MOFs) is synthesized using ditopic PC linkers obtained through regioselective statistical condensation. The resulting MOF exhibits significant improvements in electronic absorption, thereby enhancing the material's performance in light harvesting and energy conversion.
Lukas S. Langer +12 more
wiley +1 more source
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models [PDF]
, 2010 11 pages, 2 figures, 3 ...
Nickisch, H., Rasmussen, C.
openaire +4 more sources
Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions
Advanced Functional Materials, EarlyView.DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng +7 more
wiley +1 more source
Kernel Analysis Based on Dirichlet Processes Mixture Models
Entropy, 2019 Kernels play a crucial role in Gaussian process regression. Analyzing kernels from their spectral domain has attracted extensive attention in recent years. Gaussian mixture models (GMM) are used to model the spectrum of kernels.
Jinkai Tian, Peifeng Yan, Da Huang
doaj +1 more source
Statistical Compressive Sensing of Gaussian Mixture Models
, 2010 A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution and achieving accurate reconstruction on average, is introduced ...
Sapiro, Guillermo, Yu, Guoshen
core +1 more source
Advanced Functional Materials, EarlyView.Zinc(II) coordination complexes with tunable aryloxy‐imine ligands exhibit controllable supramolecular self‐assembly into hierarchical fibrous structures. Coordination‐driven stacking, not π–π interactions, enables gelation, dynamic assembly/disassembly, and enhanced nanomechanical properties.
Merlin R. Stühler +10 more
wiley +1 more source
Noise adaptive training for subspace Gaussian mixture models [PDF]
, 2013 Noise adaptive training (NAT) is an effective approach to normalise the environmental distortions in the training data. This paper investigates the model-based NAT scheme using joint uncertainty decoding (JUD) for subspace Gaussian mixture models (SGMMs).
Ghoshal, Arnab, Lu, Liang, Renals, Steve
core +1 more source
Gaussian Mixture Model of Heart Rate Variability
PLoS ONE, 2012 Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians.
BRISCHETTO COSTA, Tommaso +2 more
openaire +6 more sources
Fast‐Responding O2 Gas Sensor Based on Luminescent Europium Metal‐Organic Frameworks (MOF‐76)
Advanced Functional Materials, EarlyView.Luminescent MOF‐76 materials based on Eu(III) and mixed Eu(III)/Y(III) show rapid and reversible changes in emission intensity in response to O2 with very short response times. The effect is based on triplet quenching of the linker ligands that act as photosensitizers. Average emission lifetimes of a few milliseconds turn out to be mostly unaffected by
Zhenyu Zhao +5 more
wiley +1 more source