Zobrazeno 1 - 10
of 18 660
pro vyhledávání: '"Sheetal, A."'
Dynamic Nuclear Polarization (DNP) is transforming NMR and MRI by significantly enhancing sensitivity through the transfer of polarization from electron spins to nuclear spins via microwave irradiation. However, the use of monochromatic continuous-wa
Externí odkaz:
http://arxiv.org/abs/2410.19170
This paper presents a mathematical analysis of the evolution of a mixture of two incompressible, isothermal fluids flowing through a porous medium in a three dimensional bounded domain. The model is governed by a coupled system of convective Brinkman
Externí odkaz:
http://arxiv.org/abs/2410.13731
Autor:
Jain, Sheetal, Zhou, Zhengbang, Horsley, Ezekiel, Heath, Christopher J. S., Shakouri, Mohsen, Xiao, Qunfeng, Chen, Ning, Chen, Weifeng, King, Graham, Kim, Young-June
We carried out a comprehensive crystal structure characterization of Ti-doped lithium ruthenate (Li$_2$Ti$_x$Ru$_{1-x}$O$_3$), to investigate the effect of Ti-doping on the structural phase transition. Experimental tools sensitive to the average stru
Externí odkaz:
http://arxiv.org/abs/2410.12022
Designing a cognitive radar system capable of adapting its parameters is challenging, particularly when tasked with tracking a ballistic missile throughout its entire flight. In this work, we focus on proposing adaptive algorithms that select wavefor
Externí odkaz:
http://arxiv.org/abs/2410.10591
This work addresses the persistent challenges of substantial training time and GPU resource requirements even when training lightweight encoder-vocoder models for Textless NLP. We reduce training steps significantly while improving performance by a)
Externí odkaz:
http://arxiv.org/abs/2409.19015
We propose a minimal power white box adversarial attack for Deep Learning based Automatic Modulation Classification (AMC). The proposed attack uses the Golden Ratio Search (GRS) method to find powerful attacks with minimal power. We evaluate the effi
Externí odkaz:
http://arxiv.org/abs/2409.11454
Autor:
Devapriya, Dahlia, Kalyani, Sheetal
In reconfigurable intelligent surface (RIS) aided systems, the joint optimization of the precoder matrix at the base station and the phase shifts of the RIS elements involves significant complexity. In this paper, we propose a complex-valued, geometr
Externí odkaz:
http://arxiv.org/abs/2409.11270
Learning rate is a crucial parameter in training of neural networks. A properly tuned learning rate leads to faster training and higher test accuracy. In this paper, we propose a Lipschitz bandit-driven approach for tuning the learning rate of neural
Externí odkaz:
http://arxiv.org/abs/2409.09783
The performance of the standard Online Robust Principal Component Analysis (OR-PCA) technique depends on the optimum tuning of the explicit regularizers and this tuning is dataset sensitive. We aim to remove the dependency on these tuning parameters
Externí odkaz:
http://arxiv.org/abs/2409.07275
Source enumeration, the task of estimating the number of sources from the signal received by the array of antennas, is a critical problem in array signal processing. Numerous methods have been proposed to estimate the number of sources under white or
Externí odkaz:
http://arxiv.org/abs/2409.06563