335 citations · 496 across the 15 of their papers we have counts for
15 papers
Near-field Anchor-free Localization using Reconfigurable Intelligent Surfaces
Srikar Sharma Sadhu, Praful D. Mankar, Santosh Nannuru
Near-field localization is expected to play a crucial role in enabling a plethora of applications under the paradigm of 6G networks. The conventional localization methods rely on c…
Real-time identification and control of influential pandemic regions using graph signal variation
Sudeepini Darapu, Subrata Ghosh, Dibakar Ghosh +2
The global spread of pandemics is facilitated by the mobility of populations, transforming localized infections into widespread phenomena. To contain it, timely identification of i…
Near-field 5D Pose Estimation using Reconfigurable Intelligent Surfaces
Srikar Sharma Sadhu, Praful D. Mankar, Santosh Nannuru
The advent of 6G is expected to enable many use cases which may rely on accurate knowledge of the location and orientation of user equipment (UE). The conventional localization met…
Graph learning methods to extract empathy supporting regions in a naturalistic stimuli fMRI
Sasanka GRS, Ayushi Agrawal, Santosh Nannuru +1
Functional MRI (fMRI) research, employing naturalistic stimuli like movies, explores brain network interactions in complex cognitive processes such as empathy. The empathy network…
Impact of Diffusion on synchronization pattern of epidemics in nonidentical metapopulation networks
Anika Roy, Ujjwal Shekhar, Aditi Bose +4
In a prior study, a novel deterministic compartmental model known as the SEIHRK model was introduced, shedding light on the pivotal role of test kits as an intervention strategy fo…
Localization of DOA trajectories -- Beyond the grid
Ruchi Pandey, Santosh Nannuru
The direction of arrival (DOA) estimation algorithms are crucial in localizing acoustic sources. Traditional localization methods rely on block-level processing to extract the dire…
Improving trajectory localization accuracy via direction-of-arrival derivative estimation
Ruchi Pandey, Shreyas Jaiswal, Huy Phan +1
Sound source localization is crucial in acoustic sensing and monitoring-related applications. In this paper, we do a comprehensive analysis of improvement in sound source localizat…
Identifying Influential Pandemic Regions Using Graph Signal Variation
Sudeepini Darapu, Subrata Ghosh, Abhishek Senapati +2
Developing methods to analyse infection spread is an important step in the study of pandemic and containing them. The principal mode for geographical spreading of pandemics is the…
Particle Flow Gaussian Sum Particle Filter
Karthik Comandur, Yunpeng Li, Santosh Nannuru
Particle flow Gaussian particle flow (PFGPF) uses an invertible particle flow to generate a proposal density. It approximates the predictive and posterior distributions as Gaussian…
Particle Flow Gaussian Particle Filter
Karthik Comandur, Yunpeng Li, Santosh Nannuru
State estimation in non-linear models is performed by tracking the posterior distribution recursively. A plethora of algorithms have been proposed for this task. Among them, the Ga…
Parametric Models for DOA Trajectory Localization
Ruchi Pandey, Santosh Nannuru
Directions of arrival (DOA) estimation or localization of sources is an important problem in many applications for which numerous algorithms have been proposed. Most localization m…
Sparse Bayesian Learning for DOA Estimation in Heteroscedastic Noise
Peter Gerstoft, Santosh Nannuru, Christoph F. Mecklenbräuker +1
The paper considers direction of arrival (DOA) estimation from long-term observations in a noisy environment. In such an environment the noise source might evolve, causing the stat…
Sparse Bayesian learning with uncertainty models and multiple dictionaries
Santosh Nannuru, Kay L. Gemba, Peter Gerstoft +2
Sparse Bayesian learning (SBL) has emerged as a fast and competitive method to perform sparse processing. The SBL algorithm, which is developed using a Bayesian framework, approxim…
Multi Snapshot Sparse Bayesian Learning for DOA Estimation
Peter Gerstoft, Christoph F. Mecklenbräuker, Angeliki Xenaki
The directions of arrival (DOA) of plane waves are estimated from multi-snapshot sensor array data using Sparse Bayesian Learning (SBL). The prior source amplitudes is assumed inde…
Multisensor CPHD filter
Santosh Nannuru, Stephane Blouin, Mark Coates +1
The single sensor probability hypothesis density (PHD) and cardinalized probability hypothesis density (CPHD) filters have been developed in the literature using the random finite…