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Hamidreza Amindavar

Researcher at Amirkabir University of Technology

Publications -  255
Citations -  1996

Hamidreza Amindavar is an academic researcher from Amirkabir University of Technology. The author has contributed to research in topics: Heteroscedasticity & Clutter. The author has an hindex of 20, co-authored 244 publications receiving 1681 citations. Previous affiliations of Hamidreza Amindavar include University of Washington & Islamic Azad University.

Papers
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Pade approximations of probability density functions

TL;DR: In this paper, the authors demonstrate how to employ a limited number of exactly specified moments to approximate the probability density and distribution functions of various random variables, using the technique of Pade approximations.
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Robust Multiplicative Patchwork Method for Audio Watermarking

TL;DR: Simulation results show that MPM is robust against various common attacks such as noise addition, filtering, echo, MP3 compression, etc. and provides more robustness and inaudibility of the watermark insertion.
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Multiuser Scheduling for Asymmetric FSO/RF Links in Satellite-UAV-Terrestrial Networks

TL;DR: This letter investigates the multiuser downlink transmission performance of an asymmetric free space optical (FSO)/radio frequency (RF) link and derives a closed-form expression for ergodic capacity (EC) of the considered system, where the RF link exploits transmit beamforming based on statistical channel state information (CSI) to obtain better performance than single antenna scenarios in existing works.
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A new time-delay estimation in multipath

TL;DR: This paper addresses a new approach to time-delay estimation based upon the autocorrelation estimator (AE), and develops an algorithm to estimate the parameters of a multipath environment based on the new generalization.
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Speckle Suppression in SAR Images Using the 2-D GARCH Model

TL;DR: A novel Bayesian-based speckle suppression method for Synthetic Aperture Radar ( SAR) images is presented that preserves the structural features and textural information of the scene.