Zobrazeno 1 - 10
of 51 681
pro vyhledávání: '"Electrical Engineering and Systems Science - Signal Processing"'
In a classification task, counterfactual explanations provide the minimum change needed for an input to be classified into a favorable class. We consider the problem of privately retrieving the exact closest counterfactual from a database of accepted
Externí odkaz:
http://arxiv.org/abs/2411.10429
Autor:
Sangston, K. James
This work examines the problem of extending the one-dimensional analytic signal, which is ubiquitous throughout signal processing, to higher dimensional signals. Bulow et al. and Felsberg et al. have previously used techniques from Clifford algebra a
Externí odkaz:
http://arxiv.org/abs/2411.10412
In this paper, we address task-oriented (or goal-oriented) communications where an encoder at the transmitter learns compressed latent representations of data, which are then transmitted over a wireless channel. At the receiver, a decoder performs a
Externí odkaz:
http://arxiv.org/abs/2411.10385
Modern cryptography, such as Rivest Shamir Adleman (RSA) and Secure Hash Algorithm (SHA), has been designed by humans based on our understanding of cryptographic methods. Neural Network (NN) based cryptography is being investigated due to its ability
Externí odkaz:
http://arxiv.org/abs/2411.10287
Autor:
Sangston, K. James
We use the theory of Bernstein functions, completely monotonic functions, and Levy processes to define a positive random process $\tau(t)$. For radar clutter one may think of $\tau(t)$ as the instantaneous power of the scattered radar signal that is
Externí odkaz:
http://arxiv.org/abs/2411.10263
Low latency and high data rate performance are essential in wireless communication systems. This paper explores trade-offs between latency and data rates for optical wireless communication. We introduce a latency-optimized model utilizing compound co
Externí odkaz:
http://arxiv.org/abs/2411.10259
Autor:
Schmalen, Laurent, Lauinger, Vincent, Ney, Jonas, Wehn, Norbert, Matalla, Patrick, Randel, Sebastian, von Bank, Alexander, Edelmann, Eike-Manuel
In this paper, we highlight recent advances in the use of machine learning for implementing equalizers for optical communications. We highlight both algorithmic advances as well as implementation aspects using conventional and neuromorphic hardware.<
Externí odkaz:
http://arxiv.org/abs/2411.10101
Autor:
Iacovelli, Giovanni, Sheemar, Chandan Kumar, Khan, Wali Ullah, Mahmood, Asad, Alexandropoulos, George C., Querol, Jorge, Chatzinotas, Symeon
In this article, we propose the integration of the Holographic Multiple Input Multiple Output (HMIMO) as a transformative solution for next generation Non-Terrestrial Networks (NTNs), addressing key challenges, such as high hardware costs, launch exp
Externí odkaz:
http://arxiv.org/abs/2411.10014
Foundation deep learning (DL) models are general models, designed to learn general, robust and adaptable representations of their target modality, enabling finetuning across a range of downstream tasks. These models are pretrained on large, unlabeled
Externí odkaz:
http://arxiv.org/abs/2411.09996
Autor:
Sanjari, Pouria, Aflatouni, Firooz
Metasurfaces can manipulate the amplitude and phase of electromagnetic waves, offering applications ranging from antenna design and cloaking to imaging and communication. Additionally, temporal, and non-linear metasurfaces have the potential to adjus
Externí odkaz:
http://arxiv.org/abs/2411.09965