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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
More filters
Journal ArticleDOI
Inertia properties of indefinite quadratic forms
TL;DR: It is shown that a complete link between both solutions can be established by invoking a fundamental set of inertia conditions, which turn out to mark the differences between the two estimation problems in indefinite metric spaces.
Journal ArticleDOI
RLS-Laguerre lattice adaptive filtering: error-feedback, normalized, and array-based algorithms
Ricardo Merched,Ali H. Sayed +1 more
TL;DR: This paper develops several lattice structures for RLS-Laguerre adaptive filtering including a posteriori and a priori based lattice filters with error-feedback, array-based lattICE filters, and normalized lattice filter structures.
Journal ArticleDOI
Steady-state and tracking analyses of the sign algorithm without the explicit use of the independence assumption
N.R. Yousef,Ali H. Sayed +1 more
TL;DR: The author begins by discussing the fundamental energy relation, then goes on to consider steady state analysis and tracking analysis, and adaptive filtering is also mentioned in the study.
Book ChapterDOI
Asynchronous Adaptive Networks
Ali H. Sayed,Xiaochuan Zhao +1 more
TL;DR: In this paper, the authors extended the results to asynchronous networks where agents are subject to various sources of uncertainties that influence their behavior, including randomly changing topologies, random link failures, random data arrival times, and agents turning on and off randomly.
Proceedings ArticleDOI
Reputation design for adaptive networks with selfish agents
TL;DR: In order to encourage cooperation among selfish agents, a reputation scheme is designed that enables agents to utilize the historic summary of other agents' past actions to predict future returns that would result from being cooperative i.e., from sharing information with other agents.