Person

Saeid Haghighatshoar

This person is no longer with EPFL

Related publications (16)

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Multi Terminal Probabilistic Compressed Sensing

Saeid Haghighatshoar

Abstract—In this paper, the ‘Approximate Message Passing’ (AMP) algorithm, initially developed for compressed sensing of signals under i.i.d. Gaussian measurement matrices, has been extended to a multi-terminal setting (MAMP algorithm). It has been shown t ...

2014

Compressed Sensing of Memoryless Sources

Saeid Haghighatshoar

Compressed sensing is a new trend in signal processing for efficient sampling and signal acquisition. The idea is that most real-world signals have a sparse representation in an appropriate basis and this can be exploited to capture the sparse signal by ta ...

EPFL2014

Multi Terminal Probabilistic Compressed Sensing

Saeid Haghighatshoar

In this paper, the 'Approximate Message Passing' (AMP) algorithm, initially developed for compressed sensing of signals under i.i.d. Gaussian measurement matrices, has been extended to a multi-terminal setting (MAMP algorithm). It has been shown that simil ...

Ieee2014

A New Entropy Power Inequality for Integer-Valued Random Variables

Emmanuel Abbé, Saeid Haghighatshoar

The entropy power inequality (EPI) yields lower bounds on the differential entropy of the sum of two independent real-valued random variables in terms of the individual entropies. Versions of the EPI for discrete random variables have been obtained for spe ...

Institute of Electrical and Electronics Engineers2014

A Fast Hadamard Transform for Signals with Sub-linear Sparsity

Martin Vetterli, Robin Scheibler, Saeid Haghighatshoar

A new iterative low complexity algorithm has been presented for computing the Walsh-Hadamard transform (WHT) of an N dimensional signal with a K-sparse WHT, where N is a power of two and K = O(N^α), scales sub- linearly in N for some 0 < α < 1. Assuming a ...

2013

Adaptive sensing using deterministic partial Hadamard matrices

Emre Telatar, Emmanuel Abbé, Saeid Haghighatshoar

This paper investigates the construction of determin- istic measurement matrices preserving the entropy of a random vector with a given probability distribution. In particular, it is shown that for a random vector with i.i.d. discrete components, this is a ...

Ieee2012