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Ali H. Sayed
Researcher at École Polytechnique Fédérale de Lausanne
Publications - 766
Citations - 39568
Ali H. Sayed is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Adaptive filter & Optimization problem. The author has an hindex of 81, co-authored 728 publications receiving 36030 citations. Previous affiliations of Ali H. Sayed include Harbin Engineering University & University of California, Los Angeles.
Papers
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Journal ArticleDOI
User Selection Methods for Multiuser Two-Way Relay Communications Using Space Division Multiple Access
Jingon Joung,Ali H. Sayed +1 more
TL;DR: A multiuser two-way relay system using space division multiple access (SDMA) communications is designed and an optimal scheduling method is devised that maximizes the sum rate while ensuring fairness among users.
Proceedings ArticleDOI
Distributed Diffusion Adaptation Over Graph Signals
TL;DR: The objective of this work is to propose diffusion strategies for adaptively learning from streaming graph signals that are able to process dynamic or streaming data.
Journal ArticleDOI
A Robust Finger Tracking Method for Multimodal Wearable Computer Interfacing
TL;DR: This paper presents a vision-based robust finger tracking algorithm combined with audio-based control commands that is integrated into a multimodal unobtrusive user interface, wherein the interface may be used to segment out objects of interest in the environment by encircling them with the user's pointing fingertip.
Book ChapterDOI
LMS is H∞ Optimal
TL;DR: In this paper, the celebrated LMS (Least-means-squares) adaptive algorithm is shown to be H ∞ optimal, i.e., it minimizes the energy gain from the disturbances to the predicted errors.
Proceedings ArticleDOI
Diffusion LMS over multitask networks with noisy links
TL;DR: This work analyzes the theoretical performance of the single-task diffusion LMS when it is run, intentionally or unintentionally, in a multitask environment in the presence of noisy links and introduces an improved strategy that allows the agents to promote or reduce exchanges of information with their neighbors.