Results 101 to 110 of about 1,492,451 (279)

Robust multipath exploitation radar imaging in urban sensing based on Bayesian compressive sensing

, 2014
—In through-the-wall radar imaging applications, exploitation of group sparsity of the targets under multipath propagation allows high-resolution ghost-free imaging.
Yimin D. Zhang, Fauzia Ahmad, Moeness G. Amin, Qisong Wu   +3 more
core   +1 more source

Emergence of Unconventional Magnetic Order in Strain‐Engineered RuO2/TiO2 Superlattices

Advanced Science, EarlyView.
Epitaxial strain activates unconventional magnetism in rutile RuO2, absent in bulk or relaxed RuO2. Polarized neutron reflectometry with atomic‐layer resolution directly reveals finite magnetization confined to RuO2 layers in fully strained RuO2/TiO2 superlattices on TiO2 (110).
Seung Gyo Jeong, Seungjun Lee, Jin Young Oh, Bonnie Y. X. Lin, Anand Santhosh, Sehwan Song, Sungkyun Park, James M. LeBeau, Alexander J. Grutter, Woo Seok Choi, Tony Low, Valeria Lauter, Bharat Jalan   +12 more
wiley   +1 more source

Sparse Bayesian Generative Modeling for Compressive Sensing

Advances in Neural Information Processing Systems 37
This work addresses the fundamental linear inverse problem in compressive sensing (CS) by introducing a new type of regularizing generative prior. Our proposed method utilizes ideas from classical dictionary-based CS and, in particular, sparse Bayesian learning (SBL), to integrate a strong regularization towards sparse solutions.
Benedikt Böck, Sadaf Syed, Wolfgang Utschick   +2 more
openaire   +3 more sources

Q‐LEAP: Millisecond Hyperdimensional Optimization for Full‐Spectrum Optical Metamaterials

Advanced Science, EarlyView.
Q‐LEAP integrates physics‐informed residual machine learning with factorization‐machine‐encoded quantum annealing to design full‐spectrum optical metamaterials. It explores a 2108 design space and, in a single 2.56 ms annealing step, reaches 85.83% of the theoretical FoM limit, enabling selective 5‐8 µm emission with 3–5 and 8–14 µm suppression and ∼40×
Zikang Guo, Yunwen Wu, Yuhui Guo, Shenghong Ju   +3 more
wiley   +1 more source

Bayesian compressive sensing for ultra-wideband channel models

2012 35th International Conference on Telecommunications and Signal Processing (TSP), 2012
Considering the sparse structure of ultra-wideband (UWB) channels, compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS, the inclusion of Bayesian framework has shown potential to improve signal recovery as statistical information related to signal parameters is considered.
Ozgor, Mehmet, Erküçük, Serhat, Erküçük, Serhat, Cirpan, Hakan Ali   +3 more
openaire   +3 more sources

Failure Detection in Linear Arrays through Compressive Sensing [PDF]

, 2013
An array diagnosis method based on Bayesian Compressive Sensing is validated in the case for linear layouts. A set of numerical representative examples are presented with the aim of providing some insights on the method features and ...
Oliveri, Giacomo, Rocca, Paolo, Massa, Andrea   +2 more
core  

Wavelet-Based Compressed Sensing for SAR Tomography of Forested Areas [PDF]

, 2012
Synthetic aperture radar (SAR) tomography is a 3-D imaging modality that is commonly tackled by spectral estimation techniques. Thus, the backscattered power along the cross-range direction can be readily obtained by computing the Fourier spectrum of a ...
Nannini, Matteo, Aguilera, Esteban, Reigber, Andreas   +2 more
core   +1 more source

Hardware Acceleration of Stochastic Neural Networks Enabled by Bit‐Cell Level Co‐Design of Magnetic Tunnel Junctions

Advanced Science, EarlyView.
An MTJ‐based probabilistic processing‐in‐memory architecture unites nonvolatile storage, local entropy generation, and stochastic computation within each memory cell. Stored multi‐bit weights are converted directly into programmable stochastic bitstreams, enabling neural‐network inference, adaptive Ising optimization, and uncertainty‐aware Bayesian ...
Qiuyuan Wang, Dooyong Koh, Brooke McGoldrick, Tudor Mocioi, Yabin Fan, Marc Baldo, Luqiao Liu   +6 more
wiley   +1 more source

Bayesian compressive sensing

, 2007
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  

Enhancing Specific Stiffness of Nano‐Architected Materials Through Generative AI and Active Learning

Advanced Science, EarlyView.
A structure‐centric generative framework searches voxelated design space directly, coupling a variational autoencoder with multi‐objective optimization and active learning to progressively expand the validated design domain. The discovered nano‐architectures, realized as pyrolytic carbon by two‐photon lithography, deliver 18–23% higher stiffness and 26–
Jinwook Yeo, Peter Serles, Donggeun Park, Julia R. Greer, Seunghwa Ryu   +4 more
wiley   +1 more source