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14 papers · 1 filter
On the Impact of Sampling on Deep Sequential State Estimation
Helena Calatrava, Ricardo Augusto Borsoi, Tales Imbiriba +1
State inference and parameter learning in sequential models can be successfully performed with approximation techniques that maximize the evidence lower bound to the marginal log-l…
A TBLMI Framework for Harmonic Robust Control
Flora Vernerey, Pierre Riedinger, Jamal Daafouz
The primary objective of this paper is to demonstrate that problems related to stability and robust control in the harmonic context can be effectively addressed by formulating them…
Improving MIMO channel estimation via receive power feedback
Chao Zhang, Hang Zou, Samson Lasaulce +1
Estimating the channel state is known to be an important problem in wireless networks. To this end, it matters to exploit all the available information to improve channel estimatio…
Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral Unmixing
Ricardo Augusto Borsoi, Deniz Erdoğmuş, Tales Imbiriba
Although considerable effort has been dedicated to improving the solution to the hyperspectral unmixing problem, non-idealities such as complex radiation scattering and endmember v…
A harmonic framework for the identification of linear time-periodic systems
Flora Vernerey, Pierre Riedinger, Andrea Iannelli +1
This paper presents a novel approach for the identification of linear time-periodic (LTP) systems in continuous time. This method is based on harmonic modeling and consists in conv…
On factorization of rank-one auto-correlation matrix polynomials
Konstantin Usevich, Julien Flamant, Marianne Clausel +1
This article characterizes the rank-one factorization of auto-correlation matrix polynomials. We establish a sufficient and necessary uniqueness condition for uniqueness of the fac…