Luis Weruaga

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In this paper, a new method for time–frequency analysis of speech signals is proposed. Given that the fundamental frequency of voiced speech often undergoes rapid fluctuation and in these cases the classical spectrogram suffers from blurring and artifacts, an adaptive analysis basis composed of quadratic chirps is what we consider. The analysis basis of the(More)
The Chirp transform is a powerful analysis tool for variable frequency signals such as speech. The computational load represents the main limitation of its original formulation, discouraging its use in real-time applications. This paper analyzes a fast implementation, based on performing time-warping on the signal under analysis, combined with the Fast(More)
This letter presents the exact normalized least-mean-square (NLMS) algorithm for the l<sub>p</sub>-norm-regularized square error, a popular choice for the identification of sparse systems corrupted by additive noise. The resulting exact lp-NLMS algorithm manifests differences to the original one, such as an independent update for each weight, a new(More)
Active deformable models are simple tools, very popular in computer vision and computer graphics, for solving ill-posed problems or mimic real physical systems. The classical formulation is given in the spatial domain, the motor of the procedure is a second-order linear system, and rigidity and elasticity are the basic parameters for its characterization.(More)
In radiotherapy (RT), organ motion caused by breathing prevents accurate patient positioning, radiation dose, and target volume determination. Most of the motion-compensated trial techniques require collaboration of the patient and expensive equipment. Estimating the motion between two computed tomography (CT) three-dimensional scans at the extremes of the(More)
CAViAR is a mobile software system for indoor environments that provides to the mobile user equipped with a smartphone indoor localization, augmented reality (AR), visual interaction, and indoor navigation. These capabilities are possible with the availability of state of the art AR technologies. The mobile application includes additional features, such as(More)
Embedding a sparse penalty in conventional Least Mean Square (LMS) adaptive algorithms is an established strategy to enhance the performance and robustness against noise in the estimation of sparse plants, such as wireless mul-tipath channels. In this paper we review the most prominent NLMS-based algorithms with &#x2113;<sub>p</sub>-norm constraint,(More)