Results 131 to 140 of about 1,446,045 (274)

Radio Tomographic Imaging Based on Low-Rank and Sparse Decomposition

open access: yesIEEE Access, 2019
Imaging artifacts induced by the multipath interference in Radio-Frequency sensing network usually significantly degrade the performance of Radio Tomographic Imaging (RTI) and thereby has become a major challenge in the Device-Free Localization (DFL ...
Jiaju Tan   +4 more
doaj   +1 more source

Bayesian sequential compressed sensing in sparse dynamical systems

open access: yes2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2010
While the theory of compressed sensing provides means to reliably and efficiently acquire a sparse high-dimensional signal from a small number of its linear projections, sensing of dynamically changing sparse signals is still not well understood. We pursue a Bayesian approach to the problem of sequential compressed sensing and develop methods to ...
Dino Sejdinovic   +2 more
openaire   +1 more source

Energy‐Aware Perturbation Optimization for Memristor‐Array Convolutional Neural Networks

open access: yesAdvanced Intelligent Systems, EarlyView.
Memristor‐array inference becomes more energy efficient when layer inputs are reshaped before computation. Sinusoidal perturbation encoding with dual‐threshold screening reduces active voltage pulses and contracts ADC input‐current ranges, jointly lowering crossbar and peripheral energy while preserving accuracy across hardware MNIST validation, deep ...
Ao Xu   +6 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

open access: yesAdvanced Intelligent Systems, EarlyView.
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

Compressive Sensing Based Bayesian Sparse Channel Estimation for OFDM Communication Systems: High Performance and Low Complexity

open access: yesThe Scientific World Journal, 2014
In orthogonal frequency division modulation (OFDM) communication systems, channel state information (CSI) is required at receiver due to the fact that frequency-selective fading channel leads to disgusting intersymbol interference (ISI) over data ...
Guan Gui   +3 more
doaj   +1 more source

Preferential trading in agriculture: New insights from a structural gravity analysis and machine learning

open access: yesAmerican Journal of Agricultural Economics, EarlyView.
Abstract Preferential trade agreements (PTAs) contain various non‐tariff provisions, yet identifying their trade effects remains challenging because these commitments are high‐dimensional and strongly correlated within agreements. We estimated a theory‐consistent structural gravity model with domestic flows for 26 agricultural subsectors over 1988–2017
Dongin Kim, Sandro Steinbach
wiley   +1 more source

Wavelet-Based Compressed Sensing for Polarimetric SAR Tomography [PDF]

open access: yes, 2013
Tomographic synthetic aperture radar (SAR) imaging has been recently formulated in a wavelet-based compressed sensing (CS) framework. This paper reviews the underlying sparsity-driven algorithms for single-channel as well as polarimetric tomography, and ...
Nannini, Matteo   +2 more
core  

Linking community structure and climate vulnerability in desert plant assemblages of southern California

open access: yesAmerican Journal of Botany, EarlyView.
Abstract Premise Desert plant assemblages in southern California provide an opportunity to link patterns of community structure with climate‐driven vulnerability in a rapidly changing environment. California sustains an exceptionally diverse flora of approximately 4300 plant species, with 31% identified as endemic.
Hector Zumbado‐Ulate   +4 more
wiley   +1 more source

EDICS: DSP-RECO Bayesian Compressive Sensing

open access: yes, 2008
The data of interest are assumed to be represented as N-dimensional real vectors, and these vectors are compressible in some linear basis B, implying that the signal can be reconstructed accurately using only a small number M ≪ N of basis-function ...
Ya Xue, Shihao Ji, Lawrence Carin
core  

Nanostructured Deep Eutectic Systems in Healthcare: From Bioactive Solvents to Intelligent Biointerfaces, Wearables, and AI‐Driven Design

open access: yesAdvanced NanoBiomed Research, EarlyView.
Beyond the green solvent paradigm, this review redefines Deep Eutectic Systems (DES) as programmable supramolecular nanoassemblies. We survey their biomedical convergence: stabilizing thermolabile mRNA to enable cold chain‐free logistics, reshaping transdermal microneedle delivery, enabling long‐term wearables via eutectogels, and utilizing Generative ...
Jeesu Moon, Min Seo Kim, Jae‐Seung Lee
wiley   +1 more source

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