7 accepted papers
Over the last few years, several works have proposed deep learning architectures to learn dynamical systems from observation data with no or little knowledge of the underlying physics. A line of work relies on learning representations where the dynamics of the underlying phenomenon can be described…
In this paper, we design an iterative channel estimation and data detection algorithm in delay-Doppler domain for orthogonal time frequency space (OTFS) system by taking advantage of the sparse nature of the channel in this domain. The proposed algorithm iterates between message-passing-aided data d…
Kalman filters are widely used for real-time estimation of dynamic systems, and they sometimes need to be implemented on energy-constrained devices. A Kalman filter implementation from unreliable memories is considered, where the flipping probability of a bit in a memory cell directly depends on its…
This paper addresses the problem of adaptive blind sparse source separation in the time domain of an over-determined instantaneous noisy mixture. A two-step approach is proposed: first, the data are projected on the signal subspace estimated using the principal subspace tracker FAPI. In the second s…
The identification and separation of contributions associated with different sources or processes is a general problem in signal and image processing. Here, we focus on the decomposition of multiple linear relationships and introduce a non-negative formulation. The proposed models can be viewed as g…
Canonical correlation analysis (CCA) is a well-known technique used to characterize the relationship between two sets of multidimensional variables by finding linear combinations of variables with maximal correlation. Sparse CCA or regularized CCA are two widely used variants of CCA because of the i…
In this paper, a blind equalizer based on probability density function (pdf) fitting is proposed. It does not require any prior information about the transmission channel or the emitted constellation. We also investigate Automatic Modulation Classification (AMC) for Quadrature Amplitude Modulation (…