3 accepted papers
Subspace clustering is a popular method for clustering unlabelled data. However, the computational cost of the subspace clustering algorithm can be unaffordable when dealing with a large data set. Using a set of dimension sketched data instead of the original data set can be helpful for mitigating t…
Labelled data are often required to train an acoustic scene classification system. However, it is time-consuming and expensive to label the data manually. An unsupervised clustering algorithm can be used to facilitate the labelling process by dividing the acoustic data into different categories. Nev…
For a linear sensor array, using line spectra is a common technique for estimating directions of arrival (DOA) of single-tone sources. Yet, very few papers consider multitone sources. For the first time, we provide the optimal Bayesian inference for multi-line spectra, i.e. a superposition of line s…