← Search

Hamidreza Amindavar

6 accepted papers

2018

Learning-Based Design of Measurement Matrix with Inter-Column Correlation for Compressive Sensing

ICASSP 2018accepted

In this paper, a new approach for the design of measurement matrix, Φ, for compressive sensing (CS) in a generic context is proposed. In accordance with well-known classical CS theory, we take the elements of Φ to be random, yet, we include correlations within the elements of the individual columns…

Cited by 0SourceScholar
2017

ARIMA-GARCH modeling for epileptic seizure prediction

ICASSP 2017accepted

This paper provides a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autoregressive conditional heteroskedasticity, Generalized autoregres…

Cited by 0SourceScholar
2017

Copula application in nonlinear/non-Gaussian Bayesian tracking in the case of correlated sensors

ICASSP 2017accepted

One of the most important challenges in target tracking is the modeling of correlated and non-Gaussian random processes. In this paper, a new target tracking approach by means of particle filtering in environments with highly correlated sensors, is discussed. The goal is to provide an accurate model…

Cited by 0SourceScholar
2017

UWB radar signal processing in measurement of heartbeat features

ICASSP 2017accepted

In this paper, a new signal processing algorithm in ultra wideband (UWB) radar as a non-contact sensor with the ability to precisely monitor heartbeat and respiration features is introduced. Exploiting harmonic series representation model that fits completely the return signal from a human chest-wal…

Cited by 0SourceScholar
2016

On parameter estimation of symmetric alpha-stable distribution

ICASSP 2016accepted

In this paper, a novel approach has been proposed for estimating the parameters of symmetric alpha-stable distribution with 1 ≤ α ≤ 2. Alpha-stable distribution can model the statistical behavior of non-Gaussian heavy tailed signals and noises with impulsive components. There are some serious consid…

Cited by 0SourceScholar
2015

A new alpha and gamma based mixture approximation for heavy-tailed Rayleigh distribution

ICASSP 2015accepted

In this paper, a novel bi-parameter mixture approximation for modeling the statistical properties of heavy-tailed Rayleigh distribution is developed. Heavy-tailed Rayleigh distribution is basically the amplitude PDF of bi-variate isotropic α-stable distribution which appears in the envelope distribu…

Cited by 0SourceScholar