In this paper, we propose a data-driven approach for the reconstruction of unknown room impulse responses (RIRs) based on the deep prior paradigm. We formulate RIR reconstruction as an inverse problem. More specifically, a convolutional neural network (CNN) is employed prior, in order to obtain a regularized solution to the RIR reconstruction problem for uniform linear arrays.
View Article and Find Full Text PDFBackground And Aims: The assessment of the genetic variability and the identification of isolated populations within a given species represent important information to plan conservation strategies on a genetic basis. In this work, the genetic variability in five natural populations of Juniperus phoenicea, three from Sardinia, one from Cyprus and the last one in the Maritime Alps was analysed by means of ISSRs, on the hypothesis that the latter could have been a refugial one during the last glaciation.
Methods: ISSRs were chosen because of their ability to detect variation without any prior sequence information.