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Sparse modeling and estimation of complex signals is not uncommon in practice. However, historically , much attention has been drawn to real-valued system models, lacking the research of sparse signal modeling and estimation for complex-valued models. This paper introduces a unifying sparse Bayesian formalism that generalizes to complex-as well as(More)
—In this paper, we present a Bayesian channel estimation algorithm for multicarrier receivers based on pilot symbol observations. The inherent sparse nature of wireless multipath channels is exploited by modeling the prior distribution of multipath components' gains with a hierarchical representation of the Bessel K probability density function; a highly(More)
In sparse Bayesian learning (SBL), Gaussian scale mixtures (GSMs) have been used to model sparsity-inducing priors that realize a class of concave penalty functions for the regression task in real-valued signal models. Motivated by the relative scarcity of formal tools for SBL in complex-valued models, this paper proposes a GSM model-the Bessel K model-that(More)
The effect of caseinomacropeptide (CMP) (the [106-169] fragment of kappa-casein produced during digestion of milk protein), was studied in anesthetized rats using bile diversion for a pure pancreatic juice collection system. Intraduodenal administration of CMP induced a dose-related specific stimulation of pancreatic secretion which was nearly abolished by(More)
Traditionally, the dictionary matrices used in sparse wireless channel estimation have been based on the discrete Fourier transform, following the assumption that the channel frequency response (CFR) can be approximated as a linear combination of a small number of multipath components, each one being contributed by a specific propagation path. In practical(More)
General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. ? Users may download and print one copy of any publication from(More)
—Existing methods for sparse channel estimation typically provide an estimate computed as the solution maximizing an objective function defined as the sum of the log-likelihood function and a penalization term proportional to the ℓ1-norm of the parameter of interest. However, other penalization terms have proven to have strong sparsity-inducing properties.(More)
General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. ? Users may download and print one copy of any publication from(More)
" Whatever you do in life will be insignificant but it is very important that you do it because nobody else will. " This thesis investigates estimation of multipath delay components for OFDM-based communication systems. The state-of-the-art channel estimation algorithm for pilot-aided OFDM systems is the Robust Wiener Filter (RWF). An alternative channel(More)
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