Hojjat Akhondi Asl

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In this letter, we present a possible extension of the theory of sampling signals with finite rate of innovation (FRI) to the case of multichannel acquisition systems. The essential issue of a multichannel system is that each channel introduces different unknown delays and gains that need to be estimated for the calibration of the channels. We pose both the(More)
In this paper we present a novel approach for sampling and reconstructing any K-sided convex and bilevel polygon with the use of exponential splines [1]. It will be shown that with K+1 projections we are able to perfectly reconstruct a K-sided bilevel polygon from its samples. We will also investigate the multichannel sampling scenario, consisting of a bank(More)
The novelty of this paper is divided into two technical sections; first we propose a novel algorithm for system identification with known input sparse signal, based on the Finite Rate of Innovation sampling theory. Then we consider the problem of simultaneously estimating the input sparse signal and also the linear system and propose a novel iterative(More)
We here place a recent joint anomaly detection and classification approach based on sparse error coding methodology into multi-scale wavelet basis framework. The model is extended to incorporate an overcomplete wavelet basis into the dictionary matrix whereupon anomalies at specified multiple levels of scale are afforded equal importance. This enables, for(More)
The robust principal component analysis (PCA) method has shown very promising results in seismic ambient noise attenuation when dealing with outliers in the data. However, the model assumes a general Gaussian distribution plus sparse outliers for the noise. In seismic data however, the noise standard variation could vary from one place to another leading to(More)
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