activity
20182021
most citedMachine learning based identification of buried objects using sparse whitened NMF

3 citations · 4 across the 3 of their papers we have counts for

collaborators

5 papers

eess.SP2021

Three-Dimensional Localization of Active Aerial Targets Using a Single Terrestrial Receiver Site

Saber Kaviani, Fereidoon Behnia

This paper proposes a method for the three-dimensional localization of an active aerial target by a single ground based sensor. The proposed method employs the time and frequency d…

eess.SP20191 cited

Robust Wiener filter based time gating method for detection of shallow buried objects

Ali Gharamohammadi, Fereidoon Behnia, Arash Shokouhmand

In detecting shallow buried underground objects, reflected power from ground, i.e. ground surface clutter makes the task extremely difficult. In order to remove ground clutter, con…

eess.SP20193 cited

Machine learning based identification of buried objects using sparse whitened NMF

Ali Gharamohammadi, Fereidoon Behnia, Arash Shokouhmand

In this paper, a whitening-based algorithm has been applied to sparse non-negative matrix factorization (NMF) as a preprocessing practice enhancing the identification of buried obj…

eess.SP2018

Optimum window length of Savitzky-Golay filters with arbitrary order

Mohammad Sadeghi, Fereidoon Behnia

One of the widely used denoising methods in different domains is the Savitzky-Golay (SG) filter. The SG filter has two design parameters: window length and the filter order. As the…

eess.SP2018

NLOS Mitigation Using Sparsity Feature And Iterative Methods

Abbas Abolfathi, Fereidoon Behnia, Farokh Marvasti

Well-known methods are employed to localize mobile station (MS) using line of sight (LOS) measurements. These methods may result in large error if they are fed with non LOS (NLOS)…