Results 111 to 120 of about 1,531 (279)

Bayesian Learning-Assisted Compressive Sensing Improves Multi-Target Parameter Estimation in 5G-NR Inspired ISAC

IEEE Open Journal of Vehicular Technology
Integrated sensing and communication (ISAC) has emerged as a key technology for 6G communication systems, enabling both spectrum and hardware sharing between radar and communication systems.
Prabhanshu Yadav, Kunal Kumar Singh, Suraj Srivastava, Lajos Hanzo   +3 more
doaj   +1 more source

Non-Convex Priors In Bayesian Compressed Sensing

, 2009
Publication in the conference proceedings of EUSIPCO, Glasgow, Scotland ...
S. Derin Babacan, Luis Mancera, Rafael Molina 0001, Aggelos K. Katsaggelos   +3 more
openaire   +2 more sources

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

The Effect of Primary User Bandwidth on Bayesian Compressive Sensing Based Spectrum Sensing [PDF]

, 2016
The application of compressive sensing (CS) theory has found great interest in wideband spectrum sensing. Although most studies have considered perfect reconstruction of the primary user signal it is actually more important to assess the presence or ...
Cirpan, Hakan Ali, Erküçük, Serhat, Başaran, Mehmet   +2 more
core   +1 more source

Simultaneous Bayesian Compressive Sensing And Blind Deconvolution

, 2012
Publication in the conference proceedings of EUSIPCO, Bucharest, Romania ...
Leonidas Spinoulas, Bruno Amizic, Miguel Vega, Rafael Molina 0001, Aggelos K. Katsaggelos   +4 more
openaire   +3 more sources

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Cluster Expansion Models Via Bayesian Compressive Sensing [PDF]

, 2013
The steady march of new technology depends crucially on our ability to discover and design new, advanced materials. Partially due to increases in computing power, computational methods are now having an increased role in this discovery process.
Nelson, Lance Jacob
core   +1 more source

Bayesian Compressive Sensing for DOA Estimation using the Difference Coarray [PDF]

, 2020
-In this paper, we utilize Bayesian Compressive Sensing (BCS) for direction-of-arrival (DOA) estimation based on the coarray. This enables estimation of more sources than the number of physical antennas. We adopt the covariance vectorization technique to
Xiangrong Wang, Moeness G Amin, Fauzia Ahmad, Elias Aboutanios   +3 more
core  

Sensor Deployment in Bayesian Compressive Sensing Based Environmental Monitoring [PDF]

, 2014
Sensor networks play crucial roles in the environmental monitoring. So far, the large amount of resource consumption in traditional sensor networks has been a huge challenge for environmental monitoring.
Yan, Shulin, Wu, Chao, Shulin Yan, Guo, Yike, Wu, D., Di Wu, Yike Guo, Chao Wu   +7 more
core   +1 more source