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pro vyhledávání: '"Dubey, Amartansh"'
Indoor imaging is a critical task for robotics and internet-of-things. WiFi as an omnipresent signal is a promising candidate for carrying out passive imaging and synchronizing the up-to-date information to all connected devices. This is the first re
Externí odkaz:
http://arxiv.org/abs/2401.04317
Radio Tomographic Imaging (RTI) is a phaseless imaging approach that can provide shape reconstruction and localization of objects using received signal strength (RSS) measurements. RSS measurements can be straightforwardly obtained from wireless netw
Externí odkaz:
http://arxiv.org/abs/2311.09633
Inverse scattering problems, such as those in electromagnetic imaging using phaseless data (PD-ISPs), involve imaging objects using phaseless measurements of wave scattering. Such inverse problems can be highly non-linear and ill-posed under extremel
Externí odkaz:
http://arxiv.org/abs/2207.07244
Autor:
Dubey, Amartansh, Murch, Ross
In this work we present a novel linear iterative solution to an electromagnetic inverse scattering problem with phaseless data for strongly scattering, lossy media. It is based on an extended Rytov approximation that significantly widens the validity
Externí odkaz:
http://arxiv.org/abs/2205.12578
We propose a correction to the conventional Rytov approximation (RA) and investigate its performance for predicting wave scattering under strong scattering conditions. An important motivation for the correction and investigation is to help in the dev
Externí odkaz:
http://arxiv.org/abs/2204.02180
A physics assisted deep learning framework to perform accurate indoor imaging using phaseless Wi-Fi measurements is proposed. It is able to image objects that are large (compared to wavelength) and have high permittivity values, that existing radio f
Externí odkaz:
http://arxiv.org/abs/2111.02667
Imaging objects with high relative permittivity and large electrical size remains a challenging problem in the field of inverse scattering. In this work we present a phaseless inverse scattering method that can accurately image and reconstruct object
Externí odkaz:
http://arxiv.org/abs/2110.03211
Akademický článek
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Autor:
Deshmukh, Samruddhi, Dubey, Amartansh
One of the major challenges in multivariate analysis is the estimation of population covariance matrix from sample covariance matrix (SCM). Most recent covariance matrix estimators use either shrinkage transformations or asymptotic results from Rando
Externí odkaz:
http://arxiv.org/abs/1912.03718
Publikováno v:
In Mechanical Systems and Signal Processing November 2021 160
