E
E. Paldi
Researcher at Yale University
Publications - 19
Citations - 1579
E. Paldi is an academic researcher from Yale University. The author has contributed to research in topics: Sensor array & Direction of arrival. The author has an hindex of 10, co-authored 19 publications receiving 1450 citations. Previous affiliations of E. Paldi include Technion – Israel Institute of Technology.
Papers
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Journal ArticleDOI
Vector-sensor array processing for electromagnetic source localization
Arye Nehorai,E. Paldi +1 more
TL;DR: The authors present a new approach for localizing electromagnetic sources using sensors where the output of each is a vector consisting of the complete six electric and magnetic field components.
Journal ArticleDOI
Acoustic vector-sensor array processing
Arye Nehorai,E. Paldi +1 more
TL;DR: The authors derive a compact expression for the Cramer-Rao bound on the estimation errors of the source direction-of-arrival (DOA) parameters in the multi-source multi-vector-sensor model.
Journal ArticleDOI
Detection and localization of vapor-emitting sources
Arye Nehorai,Boaz Porat,E. Paldi +2 more
TL;DR: Methods for detecting and localizing vapor-emitting sources using chemical sensor arrays usingchemical sensor arrays are developed and estimation and detection algorithms are developed.
Journal ArticleDOI
New equidistribution estimates of Zhang type
Wouter Castryck,Étienne Fouvry,Gergely Harcos,Emmanuel Kowalski,Philippe Michel,Paul D. Nelson,E. Paldi,János Pintz,Andrew V. Sutherland,Terence Tao,Xiao-Feng Xie +10 more
TL;DR: For arithmetic progressions to large smooth squarefree moduli, with respect to congruence classes obeying Chinese remainder theorem conditions, the authors obtained an exponent of distribution 1/2 + 7/300.
Proceedings ArticleDOI
Vector sensor processing for electromagnetic source localization
Arye Nehorai,E. Paldi +1 more
TL;DR: In this article, a vector sensor based approach is presented for the localization of electromagnetic sources using vector sensors, and a compact expression is derived for the Cramer-Rao bound on the estimation errors of these parameters for the multi-source multi-vector sensor model.