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Application layer multicast (ALM) is an effective group communication method. The ALM tree is usually built in a distributed manner because of its good scalability. However, the distributed ALM solution sometimes produces a low performance delivery tree. In this paper, we propose an ALM tree optimization solution, named ALMTO, for multicast applications, in particular, those with a large number of...
Mask estimate is regarded as the main goal for using the computational auditory scene analysis method to enhance speech contaminated by noises. This paper presents extended robust principal component analysis (RPCA) methods, referred to as NRPCA and ISNRPCA, to estimate mask effectively. The perceptually motivated cochleagram is decomposed into sparse and low-rank components via NRPCA or ISNRPCA,...
We study a nonparametric decentralized detection problem in which sensors send information to a fusion center that uses a support vector machine to make decisions about a public hypothesis. However, the same sensor information may also be used by the fusion center to infer about a private hypothesis, which the sensors wish to protect. To ensure information privacy (as opposed to data privacy), sensors...
A robust version of non-negative matrix factorization (RNMF) with generalized Kullback-Leibler divergence designed for the task of unsupervised monaural speech enhancement is proposed. RNMF tackles unsupervised speech enhancement problem through factorizing the magnitude spectrum of mixture into the sum of a non-negative sparse matrix and a non-negative low-rank matrix. The parameters of nonnegative...
Most application layer multicast (ALM) protocols build the delivery tree by the distributed way, which is necessary for large-scale group applications because of its good scalability. However, it is difficult for the distributed way to obtain high performance. To address the above problem, we study a VM-assisted ALM tree optimization solution (called ALMTO). The proposed solution uses cloud virtual...
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