Zobrazeno 1 - 10
of 398
pro vyhledávání: '"Romberg, Justin"'
Data acquisition in array signal processing (ASP) is costly, as high angular and range resolutions require large antenna apertures and wide frequency bandwidths. Data requirements grow multiplicatively with viewpoints and frequencies, increasing coll
Externí odkaz:
http://arxiv.org/abs/2410.19801
We propose new algorithms to efficiently average a collection of points on a Grassmannian manifold in both the centralized and decentralized settings. Grassmannian points are used ubiquitously in machine learning, computer vision, and signal processi
Externí odkaz:
http://arxiv.org/abs/2410.08956
We introduce a new method for robust beamforming, where the goal is to estimate a signal from array samples when there is uncertainty in the angle of arrival. Our method offers state-of-the-art performance on narrowband signals and is naturally appli
Externí odkaz:
http://arxiv.org/abs/2406.16304
Autor:
Mukherjee, Mandovi, Mao, Xiangyu, Rahman, Nael, DeLude, Coleman, Driscoll, Joe, Sharma, Sudarshan, Behnam, Payman, Kamal, Uday, Woo, Jongseok, Kim, Daehyun, Khan, Sharjeel, Tong, Jianming, Seo, Jamin, Sinha, Prachi, Swaminathan, Madhavan, Krishna, Tushar, Pande, Santosh, Romberg, Justin, Mukhopadhyay, Saibal
A near memory hardware accelerator, based on a novel direct path computational model, for real-time emulation of radio frequency systems is demonstrated. Our evaluation of hardware performance uses both application-specific integrated circuits (ASIC)
Externí odkaz:
http://arxiv.org/abs/2406.08714
Autor:
DeLude, Coleman, Driscoll, Joe, Mukherjee, Mandovi, Rahman, Nael, Kamal, Uday, Mao, Xiangyu, Khan, Sharjeel, Sivaraman, Hariharan, Huang, Eric, McHarg, Jeffrey, Swaminathan, Madhavan, Pande, Santosh, Mukhopadhyay, Saibal, Romberg, Justin
In this paper we consider the problem of developing a computational model for emulating an RF channel. The motivation for this is that an accurate and scalable emulator has the potential to minimize the need for field testing, which is expensive, slo
Externí odkaz:
http://arxiv.org/abs/2406.08710
The classical iteratively reweighted least-squares (IRLS) algorithm aims to recover an unknown signal from linear measurements by performing a sequence of weighted least squares problems, where the weights are recursively updated at each step. Variet
Externí odkaz:
http://arxiv.org/abs/2406.02769
Multi-task reinforcement learning (RL) aims to find a single policy that effectively solves multiple tasks at the same time. This paper presents a constrained formulation for multi-task RL where the goal is to maximize the average performance of the
Externí odkaz:
http://arxiv.org/abs/2405.02456
Tracking signals in dynamic environments presents difficulties in both analysis and implementation. In this work, we expand on a class of subspace tracking algorithms which utilize the Grassmann manifold -- the set of linear subspaces of a high-dimen
Externí odkaz:
http://arxiv.org/abs/2402.10352
A wide range of real-world applications can be formulated as Multi-Agent Path Finding (MAPF) problem, where the goal is to find collision-free paths for multiple agents with individual start and goal locations. State-of-the-art MAPF solvers are mainl
Externí odkaz:
http://arxiv.org/abs/2401.05860
In this paper we revisit the classical problem of estimating a signal as it impinges on a multi-sensor array. We focus on the case where the impinging signal's bandwidth is appreciable and is operating in a broadband regime. Estimating broadband sign
Externí odkaz:
http://arxiv.org/abs/2312.03922