In this paper, we study the problem of recognizing an unknown probability density function from one of its sample which is of interest in signal and image processing or telecommun...
Guilhem Coq, X. Li, Olivier Alata, Y. Pousset, Chr...
Dataflow descriptions have been used in a wide range of Digital Signal Processing (DSP) applications, such as multi-media processing, and wireless communications. Among various f...
In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new ...
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
Modulation filtering is a technique for filtering slowly-varying envelopes of frequency subbands of a nonstationary signal, ideally without affecting the signal’s phase and ...
While spoken term detection (STD) systems based on word indices provide good accuracy, there are several practical applications where it is infeasible or too costly to employ an L...
We address covariance estimation under mean-squared loss in the Gaussian setting. Specifically, we consider shrinkage methods which are suitable for high dimensional problems wit...
Letter units, or graphemes, have been reported in the literature as a surprisingly effective substitute to the more traditional phoneme units, at least in languages that enjoy a s...
This paper addresses source separation from a linear mixture under two assumptions: source sparsity and orthogonality of the mixing matrix. We propose efficient sparse separation...