Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Hamadouche, Anis"'
Autor:
Hamadouche, Anis, Sellathurai, Mathini
This paper addresses the optimisation challenges in Ultra-Massive MIMO communication systems, focusing on array selection and beamforming in dynamic and diverse operational contexts. We introduce a novel array selection criterion that incorporates an
Externí odkaz:
http://arxiv.org/abs/2407.20135
Autor:
Hamadouche, Anis, Sellathurai, Mathini
In this paper, we present an advanced model for Channel State Information (CSI) tracking, leveraging a dynamical system approach to adapt CSI dynamically based on exogenous contextual information. This methodology allows for continuous updates to the
Externí odkaz:
http://arxiv.org/abs/2407.20123
This paper introduces a novel reconfigurable and power-efficient FPGA (Field-Programmable Gate Array) implementation of an operator splitting algorithm for Non-Terrestial Network's (NTN) relay satellites model predictive orientation control (MPC). Ou
Externí odkaz:
http://arxiv.org/abs/2406.00402
In this paper, we improve upon our previous work[24,22] and establish convergence bounds on the objective function values of approximate proximal-gradient descent (AxPGD), approximate accelerated proximal-gradient descent (AxAPGD) and approximate pro
Externí odkaz:
http://arxiv.org/abs/2306.16964
We propose Dual-Feedback Generalized Proximal Gradient Descent (DFGPGD) as a new, hardware-friendly, operator splitting algorithm. We then establish convergence guarantees under approximate computational errors and we derive theoretical criteria for
Externí odkaz:
http://arxiv.org/abs/2306.16935
We analyse the convergence of an approximate, fully inexact, ADMM algorithm under additive, deterministic and probabilistic error models. We consider the generalized ADMM scheme that is derived from generalized Lagrangian penalty with additive (smoot
Externí odkaz:
http://arxiv.org/abs/2210.02094
We analyse the convergence of the proximal gradient algorithm for convex composite problems in the presence of gradient and proximal computational inaccuracies. We derive new tighter deterministic and probabilistic bounds that we use to verify a simu
Externí odkaz:
http://arxiv.org/abs/2203.02204
Akademický článek
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Autor:
Hamadouche, Anis
Publikováno v:
In Journal of Process Control March 2020 87:130-137
Publikováno v:
In Journal of Process Control November 2017 59:28-36