Results 91 to 100 of about 6,752,036 (307)
Consistent dictionary learning for signal declipping [PDF]
, 2018 Clipping, or saturation, is a common nonlinear distortion in signal processing. Recently, declipping techniques have been proposed based on sparse decomposition of the clipped signals on a fixed dictionary, with additional constraints on the amplitude
Wang, Wenwu +7 more
core +1 more source
Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems
Advanced Electronic Materials, EarlyView.Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang +9 more
wiley +1 more source
IEEE Access, 2020 Wireless sensor networks (WSNs) is composed of a large number of tiny sensors. These energy-constrained sensors are deployed in a variety of environments to collect data such as temperature, humidity, and light intensity.
Junying Chen +3 more
doaj +1 more source
K-plane clustering algorithm for analysis dictionary learning
, 2013 Analysis dictionary learning (ADL) aims to adapt dictionar-ies from training data based on an analysis sparse represen-tation model. In a recent work, we have shown that, to ob-tain the analysis dictionary, one could optimise an objective function ...
Wang, H +7 more
core +1 more source
Sparse and spurious: dictionary learning with noise and outliers [PDF]
, 2015 This is a substantially revised version of a first draft that appeared as a preprint titled "Local stability and robustness of sparse dictionary learning in the presence of noise", http://hal.inria.fr/hal-00737152International audienceA popular approach ...
Gribonval, Rémi +2 more
core +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Edulab: Majalah Ilmiah Laboratorium Pendidikan, 2020 This study aims to determine how the application of Al-Ma'any online dictionary media and whether there is a difference between learning that uses Al-Ma'any online dictionary media and those who do not use Al-Ma'any online dictionary media for Mahārah of
Aidah Fitriya
doaj +1 more source
Approximate Guarantees for Dictionary Learning
CoRR, 2019 Accepted for presentation at the Conference on Learning Theory (COLT ...
Aditya Bhaskara, Wai Ming Tai
openaire +4 more sources
The Interoperability Challenge in DFT Workflows Across Implementations
Advanced Intelligent Discovery, EarlyView.Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin +4 more
wiley +1 more source